case study of counter urbanisation

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Counter-urbanisation

Counter-urbanisation is the movement of people out of cities, to the surrounding areas. Since 1950 this process has been occurring in HICs (high-income countries). There are four main reasons for counter-urbanisation :

1. The increase in car ownership over the last 40 years means people are more mobile. This has led to an increase in commuting. Also, the growth in information technology (E-mail and video conferencing) means more people can work from home.

2. Urban areas are becoming an increasingly unpleasant place to live. This is the result of pollution, crime and traffic congestion .

3. More people tend to move when they retire.

4. New business parks on the edge of cities (on greenfield sites) mean people no longer have to travel to the city centre. People now prefer to live on the outskirts of the city to be near where they work.

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Did the pandemic bring new features to counter-urbanisation? Evidence from Estonia

Tiit tammaru.

a University of Tartu, Department of Geography, Estonia

c Estonian Academy of Sciences, Estonia

Jaak Kliimask

b Estonian University of Life Sciences, Institute of Agricultural and Environmental Sciences, Estonia

Jānis Zālīte

Associated data.

The authors do not have permission to share data.

This paper aims to shed new light on changes in counter-urbanisation over the past three decades. A specific focus will be placed on new features of domestic migration to non-metropolitan rural areas which have become apparent during the global coronavirus pandemic. We focus on the intensity, origins, and destinations of counter-urban moves, and on the individual characteristics of counter-urban movers. Based on a case study of Estonia, our main findings show, firstly, that urbanisation has been the predominant migration trend across the past thirty years, with the main destination of domestic migrants being the capital city and its urban region. Secondly, we find that counter-urban moves have gained importance over time and especially during the periods of economic bust. The most important new features of counter-urbanisation during the pandemic relate to the increased migration of families with children and people who have high-income occupations to non-metropolitan rural areas. These new features of domestic migration could serve to slow down or even reverse the long-term problem of population aging in the countryside and the loss of educated people there.

1. Introduction

The global coronavirus pandemic has generated renewed interest in counter-urbanisation ( Klocker et al., 2021 ; McManus, 2022 ). An urban exodus has been detected during the periods of pandemic-induced lockdowns, as people temporarily move out to the countryside to reduce their risk of becoming infected ( Willberg et al., 2021 ). However, it is less clear what changes in domestic migration patterns will emerge in the longer run. Would the urban exodus remain a temporary phenomenon? Would the pandemic bring with it an increased level of attraction when it comes to having second homes in rural areas, along with the related spread of the multi-local life-style amongst urban residents ( Greinke and Lange, 2022 ), or a strengthening of counter-urban migration as more people seek a home in the countryside ( McManus, 2022 )? A parallel discussion revolves around changes in the geography of working life as the opportunities to work from home have improved, potentially reducing the need to live in cities among some occupational groups.

The aim of this paper is to shed new light on counter-urbanisation during the pandemic, and whether we can uncover any new features of demographic and socio-economic change in the countryside. In order to better capture changes in domestic migration, we will compare pandemic-period migration against long-term trends of urbanisation and counter-urbanisation over the thirty-year period that includes different periods of economic boom and bust. We define counter-urban migration as any move from higher levels of the settlement system to lower levels of the settlement system. We are particularly interested in moves to non-metropolitan rural areas (cf. Berry, 1976 ; Fielding, 1989 ; Mitchell, 2004 ; McManus, 2022 ). The most common explanations for counter-urbanisation refer to economic hardships in the cities ( Berry, 1976 ) and increased preference for a rural lifestyle ( Halfacree, 2008 ). The e-lifestyle of the digital era could further contribute to lifestyle-based migration to the countryside ( McManus, 2022 ). These drivers reveal a certain tension between necessity-driven motives and motives which can be related to a desire for a more pleasant living environment. Qualitative studies aim to shed light on such motives by carrying out in-depth interviews with counter-urban movers using a case study approach ( Gkartzios, 2013 ). Quantitative studies focus on the individual characteristics and destinations of the counter-urban movers, based on census and register data, in order to trace any new features in domestic migration ( McManus, 2022 ). This study takes a quantitative approach when it comes to tracing potential changes in domestic migration during the past three decades, with the goal being to discover new features in counter-urbanisation during the pandemic. More specifically, we seek answers to the following research questions:

• (a) What changes have there been in the intensity of migration within the settlement system during the past three decades that includes different periods of economic boom and bust?
• (b) How has the balance changed between urban and counter-urban migration during the various periods of economic boom and bust over the past three decades?
• (c) What new features have become apparent in migration to non-metropolitan rural areas during the pandemic when compared to earlier periods of economic boom and bust?

Data for the study comes from Estonia, a country which has undergone major social transformation in the past three decades. Our study is based on individual-level census and registration data, with people being linked across censuses. Such individual-level linked database makes it possible for us to provide in-depth insights into the long-term changes in domestic migration, and how the counter-urbanisation has changed with time and between the population groups. In the empirical sections of the paper we will analyse migration intensity in the settlement system, and will calculate the migration concentration index and net migration rates, both for the different levels of the settlement system as well as for the smallest spatial planning units. In addition to analysing migration levels in the total population, we will also calculate all of the measures by selected population groups in terms of age, gender, mother tongue, level of education, and occupation. Our main interest relates to the changes in the domestic migration of families and occupational groups in order to uncover new features of counter-urbanisation and how such new features may relate to demographic and socio-economic changes in non-metropolitan rural areas. The paper ends with a summary and discussion of the main findings.

1.1. Literature review: changing patterns and explanations for counter-urbanisation

Counter-urbanisation as a form of migration within the settlement system serves to characterise moves down the urban hierarchy ( Klocker et al., 2021 ; McManus, 2022 ). A rich body of research has emerged on counter-urbanisation that deals with origins, destination and individual characteristics of counter-urban movers ( Mitchell 2004 , 2019 ). Counter-urbanisation may be triggered both by domestic migration as well as by people arriving from abroad (see, for example, Eimermann et al., 2012 ; Hedberg and Haandrikman, 2014 ). The term micropolitan centres has been introduced in order to refer to the diversity of settlements of different sizes and locations in the counter-urbanisation process, as counter-urban movers seek out a level of balance between urban and rural amenities ( Bjarnason et al., 2021 ; Vias, 2012 ).

In this paper, we focus on counter-urban moves as related to domestic migration from higher levels of the settlement system to lower levels of the settlement system, with a particular focus on migration into non-metropolitan rural areas. We also use the terms ‘rural areas’ and ‘countryside’ in order to refer to non-metropolitan rural areas to diversify language use within this paper. Five key drivers have been identified in moves to non-metropolitan rural areas: a) aspiration towards a rural lifestyle; b) environmental considerations; c) housing-related motives; d) economic considerations; and most recently e) health-triggered motives within the context of the global spread of COVID-19 in recent years ( Halfacree, 2008 ; McManus, 2022 ; Mitchell, 2004 , 2019 ). Geyer and Kontuly (1993) argue that preferences towards a rural lifestyle, along with environmental and housing-related motives, form a group of environmental motives which are mainly responsible for counter-urban migration. Halfacree (2008) further argues that people searching for a rural lifestyle or the ‘rural idyll’ are the most typical counter-urban movers. The desire towards a less stressful rural lifestyle tends to increase alongside the progression of the life course ( Jauhiainen, 2009 ). It has been found, for example, that the pre-elderly and elderly population in England share retirement-related quality of life considerations as an impetus for counter-urban migration ( Stockdale, 2006 ). In the Nofsinger (2012) have detected pleasant physical environment as playing the most significant role in choosing to move to the countryside. Similarly, Šimon (2014) claims that a pleasant rural environment and lifestyle-orientated motives predominate over economic reasons when it comes to the counter-urbanisation within the Czech Republic.

While environmental reasons are often found to be the main trigger for counter-urban migration, Berry (1976) introduced the term ‘counter-urbanisation’ by noting that the global oil crises of the early 1970s, which hit the cities particularly hard, was crucial in reversing the long-term trend towards urbanisation in developed countries. Similarly ( Tammaru, 2003 ), found that counter-urbanisation took the form of a survival strategy for urban households where jobs had been lost or where householders had suffered from a lowering of their income during the large-scale social transformations of the 1990s in Estonia, as the country transformed from a central planning economy to a market economy. The study by Gkartzios (2013) reveals that the main narrative in Greece relates to ‘crisis counter-urbanisation’ which has largely been triggered by the high levels of unemployment in cities rather than by pro-rural motivations and idyllic constructions of rural life. Hence, economic cycles in general and the economic hardship being experienced in urban households in particular may affect the intensity of urbanisation and counter-urbanisation; a dynamic labour and housing market during economic booms tend to attract people to move into the cities, while the push factors which encourage people to move away from those cities may tend to gain a level of importance at times of economic bust.

A tightly related discussion revolves around the social, occupational, or income groups which contribute to counter-urbanisation ( Šimon, 2014 ; Sandow and Lundholm, 2020 ). Necessity-driven counter-urban moves tend to be related to more vulnerable population groups. For example, house price growth in cities makes housing less affordable for low-income families and medium-income households, pushing families which may be in need of more spacious homes out from urban housing markets ( Hochstenbach and Musterd, 2018 ; Karsten, 2020 ). Likewise, jobs which are suitable for lower-skilled workers are also being relocated away from city centres towards more affordable suburban locations ( Delmelle et al., 2021 ). These suburban jobs can be reached not only by local inhabitants but also by travelling from more distant locations which are outside metropolitan areas, especially when these jobs are located close to easily-accessible transportation junctions, thereby reducing the need for urban living.

People from higher-income households may be more likely to be amenity-seekers in the countryside. However, while the gentrification of the creative class is well documented in cities around the globe ( Atkinson and Bridge, 2005 ; Van Ham et al., 2021 ), what is less clear is how big of a role is being played by higher income households and rural gentrification within the process of counter-urbanisation ( Phillips, 1993 ; 2004 ; Phillips et al., 2022 ). For example, the study by Herslund (2012) in Denmark documented the migration of well-educated urban dwellers to less stressful rural environs so that they could start their own business there. A recent study in Sweden also provides evidence that people who are working in the public sector and in creative industries within the knowledge economy do tend to move to non-metropolitan rural areas ( Sandow and Lundholm 2020 ). Phillips et al. (2022) find that diverse groups of gentrifiers are moving to rural England, including creative, technical, and welfare professionals. However, the study by Kozina and Clifton (2019) within the Slovenian context reveals that members of the creative class are clearly under-represented in the more peripheral non-metropolitan areas, while being over-represented in the cities. Sandow and Lundholm (2020) further detect that working in the knowledge economy does not significantly increase the chances of becoming a counter-urban mover, with such movers more likely being lower-income families. Similar evidence can be found in other contexts. In Australia, counter-urbanisation is more common amongst lower-income socio-economic groups ( Hugo and Bell, 1998 ; Argent and Plummer, 2022 ). In the Czech Republic it has been found that experience of salary decline tends to elevate the probability that those who are suffering such a decline will undertake a counter-urban move ( Šimon, 2014 ). In other words, while some well-educated and higher-income families, and members of the creative class do opt for rural living, they are not necessarily over-represented amongst those occupational groups which contribute to counter-urban migration.

The effects of the coronavirus pandemic upon counter-urbanisation are less clear in the existing body of research which is only just about beginning to emerge. The most important lasting effects of the pandemic in terms of migration to non-metropolitan areas may stem from improved opportunities of working from home ( Phillipson et al., 2020 ). Since opportunities to switch to telecommuting differ between occupational groups, there is a further expectation that white-collar office workers have more flexibility in residential choice and distant working when compared to blue-collar workers. Based on data from the United States, Dingel and Neiman (2020) have found that more than one third of jobs can be carried out entirely from home. These jobs mainly include higher-paying jobs such as those at a managerial level, as well as people who are working in the IT or financial sectors. However, teleworking also requires high-quality internet connections, both in terms of the speed of such connections (including upload speeds) and in terms of connection stability ( Budnitz and Tranos, 2021 ). Internet quality levels in rural areas tends to lag behind quality levels in major cities, thereby limiting opportunities for telecommuting outside of metropolitan areas, despite the improvement of software solutions and skills. The daily logistics of families with school-age children may be also challenging in the countryside, where public and sustainable transportation options are less readily available when compared to those of metropolitan areas ( Tao et al., 2019 ).

To conclude, previous research provides diverse and sometimes contrasting views on counter-urban migration, both when it comes to the temporal dynamics during times of economic growth and decline, and in relation to the population groups which are involved in such processes (see also Rowe et al., 2019 ). An important debate revolves around occupational differences when it comes to the characteristics of counter-urbanisers. Working from home allows for preference-based moves to non-metropolitan areas by high-income households, while high house prices in cities could push lower-income families to seek affordable housing outside the metropolitan areas. It may also be the case that, even if differences in counter-urbanisation do not vary between population groups, their destinations may differ due to the fact that high-income households look for rural amenities, while low-income households look for areas with more affordable housing. Based on the case study of Estonia, we will seek to shed more light on the potential new features of counter-urbanisation.

1.2. Material and methods

1.2.1. estonian context.

Information for the current study originates in Estonia. This country was part of the Soviet Union between 1944 and 1991, regaining its independence in 1991 and joining the European Union in 2004. With its 1.3 million inhabitants and a population density of 29.4 people per square kilometre, Estonia is both one of the smallest and the most sparsely-populated member state of the European Union. In administrative terms, the country is divided into seventy nine municipalities and fifteen counties ( Fig. 1 ). County seats and their surrounding municipalities form the urban regions of Estonia. Tallinn, Jõhvi, Tartu and Pärnu act as regional centres for north-west, north-east, south-east and south-west Estonia. The capital city of Tallinn with its 450,000 inhabitants is by far the biggest of these four cities and, therefore, the Estonian settlement system could be considered to be monocentric ( Sooväli-Sepping and Roose, 2020 ). Saaremaa, Hiiumaa, Läänemaa, south-eastern Pärnumaa, and northern Lääne-Virumaa are Estonia's most attractive coastal regions. The coastline was densely populated by Soviet military forces between 1944 and 1991, but has become increasingly residential over the past three decades. Raplamaa, north-eastern Pärnumaa, Viljandimaa, Järvamaa, Jõgevamaa, and southern Lääne-Virumaa are mainly flat agricultural areas which lie in central Estonia. Ida-Virumaa is a traditional oil-shale mining-based industrial county which borders Russia. The county has become attractive for tourism during the past three decades. The county centre of Tartumaa is Tartu, which is the country's second-largest city and the main university town, hosting University of Tartu. Põlvamaa, Valgamaa, and Võrumaa form a hilly cluster of counties in south-eastern Estonia with many tourist attractions.

Estonia's main geographical units.

The country's domestic migration flows can be better understood by comparing them with migration flows in the centrally-planned past, or when Estonia was part of the Soviet Union ( Palang, 2010 ). Only a third of the country's population lived in cities prior to 1944. The urban population grew rapidly during the Soviet period, and the share of people living in the cities reached seventy-one percent of the total population by the time of the 1989 census. However, this urban expansion occurred mainly due to the inwards-migration of Russian-speaking industrial workers from Russia or the other then Soviet republics ( Tammaru et al., 2004 ). Migrants settled mostly Tallinn and in the industrial cities of Ida-Virumaa. Due to the inefficiency of the centrally-planned economy, a large part of the labour force had to work in agriculture and, therefore rural-to-urban migration was modest in Estonia like in most of Europe's centrally-planned countries (cf. Kornai, 1992 ). Moreover, urban-to-rural migration turnaround took place in Estonia in the 1980s. As food shortages grew in the former Soviet Union in the 1970s and 1980s, agriculture became increasingly important. Large agricultural production units (called kolhoos and sovhoos ) received greater degrees of resources from the central planners, which allowed them to attract young families to live in the countryside with high wages and opportunities to get a house for free ( Marksoo, 1995 ). The most important areas of agricultural production were in the central parts of Estonia with its flat landscapes and fertile soils.

Estonia regained independence in 1991, and the rural social and economic transformations which followed that in the 1990s completely changed the rural way of life, eroding its Soviet-era agricultural base. The large and inefficient agricultural productions units collapsed, leading to high levels of unemployment, loss of solidarity, and also the loss of hope in a bright future in the countryside ( Annist, 2017 ). New, more attractive jobs emerged in the urban service sector, especially in the capital city of Tallinn, which triggered a rural exodus of young people ( Tammaru et al., 2004 ). Likewise, the attraction of different geographic areas changed within the countryside. The central Estonian counties suffered most from the collapse of the big agricultural production units. The departure of Soviet troops from the islands and the coastal regions brought along post-productionist changes in rural areas, attracting urbanites who were looking for the combination of rural idyll and an urban way of life (cf. Argent et al., 2007 ; Phillips et al., 2022 ).

1.2.2. Data, definitions, and units of analysis

This paper takes a long view to domestic migration in order to better understand the new features of counter-urbanisation during the global coronavirus pandemic. We will focus on the intensity, destinations and individual characteristics of counter-urban movers. Following the classic ( Fielding, 1989 ; Champion, 1999 ; Geyer and Kontuly, 1993 ) as well as the more recent ( Bjarnason et al., 2021 ; Vias, 2012 ) studies, we define counter-urbanisation as moves from higher levels of a settlement system to the lower levels of a settlement system. We distinguish between five levels of the settlement system: the Tallinn capital city urban region; regional-centre urban regions; country-seat urban regions; small towns outside urban regions; and rural areas outside urban regions. Our main focus is on moves which take place towards non-metropolitan rural areas.

Our study covers the period between 1989 and 2021. Estonia was modestly urbanised in 1989, but since then it has undergone a rapid population concentration to higher levels of the settlement system, with the mainstream flow of domestic migrants targeting the capital city's urban region ( Kontuly and Tammaru, 2006 ). However, counter-urbanisation has also been important. In this paper we will focus on changes in domestic migration over four time-intervals. These intervals include the 1989–2000 and 2000–2011 inter-census periods, as well as periods between 2011 and 2014, 2015–2019, and 2020. The year 2020 represents the first year of the global coronavirus pandemic. We are interested in whether it is possible to identify any changes in domestic migration in 2020 compared to earlier time intervals, and especially compared to earlier periods of economic bust (1989–2000 and 2011–2014).

Our study is based on individual-level census data (for the years 1989, 2000, and 2011), and on individual level register data (for 2015 and 2020). More specifically, we use the harmonised data of the Estonian Infotechnological Observatory (2022) , which was developed by the three main Estonian universities together with Statistics Estonia. We link people who were living in Estonia in two consecutive census years in order to be able to study domestic migration in each inter-census period through individual identification codes. For example, when studying migration flows during the 1989–2000 inter-census period, we connect people who lived in Estonia during both of these census dates, and we compare any change in the place of residence for each person in the 2000 census relative to the 1989 census. A person who relocated to another municipality between the census years is defined as a domestic migrant. Our study has some limitations though. Although we are able to capture the residential changes of all of those people who are present at both census dates, our approach still misses some migratory movement. Firstly, we miss any moves by those who were either born or who died during the inter-census period. Secondly, we miss people who either emigrated from or immigrated into Estonia during the inter-census period. Thirdly, we miss out on multiple residential relocations by the same person during the inter-census period.

Any study which aims to uncover patterns of domestic migration over time has to deal with changes in administrative borders; there have been extensive changes between 1989 and 2021 in terms of Estonian municipality borders. In order to be able to achieve comparability over time, our data preparation included an extensive multi-year geocoding exercise (at the level of individual house addresses), which makes it possible for us to flexibly aggregate data into desired spatial units. The main spatial unit of analysis is the municipality, based on 2011 municipality borders which best reflect the nature of the Estonian settlement system. The main feature of administrative changes in Estonia has been the aggregating of municipalities into bigger units. We apply the 2011 administrative division to each census date, since the pre-2011 administrative divisions were characterised with very small municipalities, while post-2011 municipalities are too big to make it possible to effectively distinguish between metropolitan and non-metropolitan areas.

We aggregate municipalities into urban regions based on daily commuting. Urban regions consist of county seats together with surrounding municipalities that send at least thirty percent of their workers to work in this county seat (see Fig. 1 ). Non-metropolitan small towns are small but compact settlements outside urban regions, and non-metropolitan rural areas include sparsely populated regions outside urban regions. We will also undertake a more detailed study of the geography of counter-urban moves. For this purpose, we aggregate the geocoded census data into the smallest Estonian planning units, or kants or localities (cf. Drudy, 1978 ). We overlay locality maps with the borders of fifteen Estonian counties and four regional centres (Tallinn, Tartu, Pärnu, and Jõhvi) in order to provide points of reference when discussing the geographic diversity of the destinations of counter-urban movers.

1.2.3. Study methods

We start our analysis by calculating ‘Migration Intensity’ (MI) in the settlement system to be able to understand temporal changes in domestic migration. Migration intensity shows the number of moves which occurred for each thousand inhabitants between the five levels of the settlement system. We proceed with the ‘Migration Concentration Index’ (MCI) analysis which was developed by Kontuly and Tammaru (2006) . MCI measures the balance between upwards and downwards moves within the settlement system between pairs of system levels. In our five-level settlement system, four moves can be made upwards and four moves can be made downwards within the system. The four upwards moves include moves from: a) non-metropolitan rural areas to non-metropolitan small towns; b) from non-metropolitan small towns to county seat metropolitan areas; c) from county seat metropolitan areas to regional city metropolitan areas; and d) from regional city metropolitan areas to capital city metropolitan areas. Downwards moves within the settlement system are the opposites to upwards moves. The MCI values are expressed in terms of percentages, varying from zero to a hundred. A value of zero implies that all moves take place from lower-to-higher levels of the settlement system. A value of a hundred implies that all moves take place from higher-to-lower levels of the settlement system. If the MCI values are higher than fifty this will imply that more than half of moves are upwards within the settlement system, and urbanisation is taking place. If the MCI values are less than fifty then this would imply that less than half of moves are downwards within the settlement system, and counter-urbanisation is taking place. Finally, we will calculate the ‘Net Migration Rate’ (NMR) within the settlement system which expresses the number of moves between the levels of the settlement system for each thousand inhabitants. We also calculate the NMR for localities, and visualise them in a series of maps. The three indices are calculated by using the following formulas:

where IM refers to in-migration, OM to out-migration, UM to upward moves, DM to downward moves and P to population size.

The time periods available for this study depend on the years in which the censuses were taken and therefore vary in length (1989–2000, 2000–2011, 2011–2014, 2015–2019, and 2020–2021). In order to enhance comparability over time, we standardised the values of all three indices by taking into account the length of each period in terms of years. The indices for the periods 1989–2000 and 2000–2011 are therefore divided by eleven in order to reflect the length of the inter-census periods in terms of years. The indices for the 2011–2014 period are divided by three, for the 2015–2019 period by four, and for the 2020–2021 period by one. In other words, we communicate per annum values of all indices in each time period within the empirical part of the paper. All three indices are calculated for the total population of Estonia as well as for selected population groups by gender, age, mother tongue, education, and occupation. We use the three main categories for measuring the level of education: primary, secondary, and tertiary. We also distinguish between three occupational groups which are aggregated from the nine main ISCO-89 categories. Highly-skilled occupations include managers and professionals, while low-skilled occupations include unskilled workers, and all other occupations are defined as being medium-skilled. Both level of education and occupation, as well as age, are time-varying personal characteristics, and we measure all of those characteristics at the beginning of each inter-census period or prior to an individual making their move.

We also present the NMR maps for highly-skilled occupations and low-skilled occupations by localities in order to detect differences in destinations for counter-urban movers. The islands and coastal areas form the most attractive rural destinations, while the agricultural areas in central Estonia provide less desirable rural destinations. The limitation in our study relates to a lack of knowledge in terms of migration-related motives. We interpret moves to islands and coastal areas as being driven mainly by amenity-related motives, and moves to central areas of Estonia as being driven mainly by necessity-related motives. Hence, we also expect to find that high-income households are attracted more by islands and coastal areas, and low-income households by the country's central areas.

1.3. Changing patterns of urbanisation and counter-urbanisation in Estonia

1.3.1. migration intensity within the settlement system.

We start by analysing changes in migration intensity or the number of moves between the levels of the settlement system for each thousand inhabitants each year, and how this varies over time and between population groups. We find that migration intensity for Estonia's total population was at 12‰ per annum, both during the 1989–2000 and the 2000–2011 inter-census periods ( Table 1 , first row). This means that in each year an average of twelve people out of every thousand relocated between the five levels of the Estonian settlement system. A significant drop in residential relocation within the settlement system took place in the 2011–2014 period of economic bust, when migration intensity fell to 7‰ per annum. However, recovery from the economic crises was rapid in Estonia, with the result that the intensity of domestic migration increased to 17‰ per annum in 2015–2019. Interestingly, we are not able to detect any drop in migration intensity at the beginning of the pandemic in 2020, meaning that the first corona year did not bring with it any major shifts in the number of moves within the settlement system for each thousand people.

Annual number of moves per 1000 inhabitants in the settlement system for the total population and for selected population groups (‰), 1989–2021.

However, migration intensity varies significantly between population groups. Ethnicity-wise, the migration intensity was 16‰ for Estonians and 5‰ for the mainly Russian-speaking ethnic minorities during the 1989–2000 inter-census period ( Table 1 ). Migration intensity for Estonians is systematically higher throughout the overall thirty-year period. This implies that the migration of native Estonians has a bigger impact on domestic migration within the settlement system when compared to migration activities for ethnic minorities. This is not surprising since members of the ethnic minority population were already highly clustered in higher levels of the settlement system in the end of the Soviet period, reducing the need to move for new economic opportunities in the cities that opened up in the 1990s. Age-wise, young adults aged between 30 and 49 have a much higher migration intensity when compared to other age groups, something which can be expected. What is more interesting is that migration intensity for young adults has been significantly higher (37‰) since 2015 when compared to earlier periods. For example, during the 2000–2011 inter-census period, when the Estonian economy was experiencing a boom, migration intensity was 19‰ per annum for young adults. There are no major differences in migration intensity between men and women over the entire thirty-year period.

The last two individual characteristics in Table 1 include education and occupation. These individuals characteristics include people fifteen years of age or older (in the case of education), and people who have a job (in the case of occupation). Education-wise, we find that the higher the level of education, the lower is migration intensity throughout the entire thirty-year period. Migration intensity increased significantly across all occupational groups in 2015–2019 when compared to earlier periods, and particularly amongst highly-skilled and medium-skilled individuals who seem to have had more opportunities on the labour market during this period of economic boom. For example, migration intensity for highly-skilled people increased to 25‰ per annum in 2015–2019 when compared to a figure of 7‰ per annum during earlier periods. As the pandemic took hold in 2020, the mobility of highly-skilled and medium-skilled people dropped, but this was not the case for low-skilled workers, with the overall consequence being that there were no differences in migration intensity between occupational groups in 2020, varying within the range of 19–20‰ per annum.

1.3.2. Migration up and down in the settlement system

We find less temporal variations in migration flows, either upwards or downwards, between the five levels of the settlement system when compared to temporal changes in migration intensity. ‘Migration Concentration Index’ (MCI) values are over fifty in all periods, implying that the number of upwards moves in the settlement system (urbanisation) outnumber downwards moves in the settlement system (counter-urbanisation). The MCI value for the total population was at fifty-nine during the 1989–2000 inter-census period ( Table 2 , first row). This implies that fifty-nine percent of moves were from lower-to-higher levels in the Estonian settlement system. The trend towards urbanisation strengthened during the 2000–2011 inter-census period, with the MCI value increasing to sixty-eight. This was an economic boom period in Estonia. During the subsequent economic bust in 2011–2014, the MCI figure dropped to sixty, while it increased to sixty-three during the next period of economic boom in 2015–2019, and again dropped, to fifty-six, during the first year of the pandemic. We therefore find clear evidence of an increase in urbanisation during periods of economic boom, and an opposing increase in the importance of counter-urbanisation during periods of economic bust. The MCI value of fifty-six for the first year of the pandemic is very close to the break-even value of fifty, meaning that upwards and downwards moves within the settlement system were almost equal in size.

Migration Concentration Index (MCI), total population and selected population groups, 1989–2021.

Some important differences in MCI values can be detected between population groups. The MCI value was higher for Estonians (60) than it was for Russian-speaking minorities (53), but only during the 1989–2000 inter-census period ( Table 2 , second row). Since then, MCI values have become bigger for ethnic minorities. In addition, during the first year of the pandemic, the MCI value for ethnic minorities is significantly higher (65) when compared to Estonians (54). This implies that the growth of counter-urban moves during the pandemic is due mainly to changes in migration of Estonians. Age-wise, only young adults aged between 15 and 29 have clearly contributed to urbanisation during the entire thirty-year period. This also applies to the first year of the pandemic, when the MCI value for young adults was at sixty-eight. MCI values vary more for other age groups. It is interesting to single out the MCI values for children aged up to fourteen years of age, which have changed more than any other age group during the thirty-year period. As under-aged children move together with their parents, this serves to indicate changing migration patterns for entire families. During the 1989–2000 and 2000–2011 inter-census periods, the MCI value for children aged up to fourteen years of age was over seventy, indicating strong urbanisation. The MCI value for children (and therefore entire families) dropped to fifty-four during the economic downturn in 2011–2014, and to forty-seven during the first year of the pandemic, referring to the dominance of counter-urbanisation. Counter-urbanisation has also become more common amongst people within the older working age and retired people.

There are no major gender-differences in migration within the settlement system, although men have contributed slightly more to counter-urban migration than have women during the overall thirty-year period. The gender gap in counter-urbanisation was especially big during the 2011–2014 economic bust, but it narrowed down during the pandemic, with MCI values being at fifty-six and fifty-seven, respectively, for men and women. This implies that the intensity of urbanisation has also slowed down for women. Education-wise, people with a primary education contributed most to urbanisation until the mid-2000s, with MCI values being greater than sixty, probably reflecting intense education-related migration amongst them. People with a tertiary education contributed least to urbanisation, with MCI values being lower than sixty, reflecting the fact they are already residing in cities while they obtain their university degrees. Since 2015, educational differences have decreased in terms of moving up and down the settlement hierarchy, with MCI values dropping below sixty for all educational groups in the first year of the pandemic. Occupation-wise, migration flows for highly-skilled and medium-skilled individuals up and down the settlement system are more responsive to periods of economic boom and bust when compared to the figures for low-skilled individuals. Migration of low-skilled people is characterised mainly by urbanisation, both in times of economic boom and bust. Highly-skilled and medium-skilled people urbanise more rapidly during times of economic boom, while counter-urbanisation becomes more important for the same groups during economic bust. To illustrate this fact, the MCI value for highly-skilled individuals was seventy-one, the highest figure out of the three occupational groups during the economic boom period in 2015–2019. Both during the 2011–2014 economic bust and during the first year of the pandemic, the MCI values for highly-skilled individuals came closest to the break-even value of fifty out of the three occupational groups, or fifty-one and fifty-seven respectively.

1.3.3. Origins and destinations in the settlement system

More than half of moves within the settlement system relate to the capital city's urban region and non-metropolitan rural areas. For example, twenty-nine percent of all moves were related to non-metropolitan rural areas during the 1989–2000 inter-census period ( Table 3 ), and twenty-four percent were linked to the Tallinn urban region. In the 2000–2011 inter-census period, the biggest share of moves between the levels of the settlement system were related to Tallinn urban region (28%), followed by non-metropolitan rural areas (25%). Let us now turn to the analyses in the changes in the annualised net migration rate. We find that the net migration gain was 3‰ per annum in the Tallinn urban region in the 1989–2000 inter-census period ( Fig. 2 ). The net migration loss was −4‰ per annum in rural areas, which implies that non-metropolitan rural communities lost an average of four people out of every thousand each year during the 1990s as a result of domestic migration. Since then, urbanisation and counter-urbanisation processes have fluctuate according to the cycle of economic boom and bust. The decade of major societal transformations which took place in the 1990s was followed by rapid economic growth in the 2000s, which then strengthened the trend towards urbanisation. The negative net migration rate was −9‰ per annum in non-metropolitan rural areas during the 2000–2011 inter-census period, while the positive net migration rate was 7‰ per annum in the capital city's urban region.

Migration origins and destinations within the settlement system, 1989–2020.

Net migration rate in non-metropolitan rural areas and in the Tallinn urban region (‰), 1989–2021.

Source: Estonian Infotechnological Mobility Observatory, own calculations.

The global economic recession of 2009 had a significant impact on the Estonian labour and housing markets. This period of economic bust weakened urbanisation and strengthened counter-urbanisation in 2011–2015. Tallinn's urban region still remained the main net gainer of domestic migrants at the expense of other urban regions, but the net positive migration rate dropped significantly when compared to figures for the previous decade, or to 3‰ per annum, while the net migration rate for non-metropolitan rural areas was close to zero ( Fig. 2 ). Recovery from the global economic recession was rapid in Estonia that brought along a strengthening of urbanisation trend. In 2015–2019, non-metropolitan rural areas experienced high migration losses (−7‰ per annum) and the Tallinn metropolitan area experienced high migration gains (9‰ per annum). The first year of the global pandemic in 2020 again reversed this pattern, with net migration for non-metropolitan rural areas being close to zero, and migration gains in Tallinn urban region decreasing to 3‰. It follows that counter-urbanisation has gained more importance in all periods of economic bust, including the one which was driven by the global pandemic.

1.3.4. The geography of counter-urbanisation

These shifts between periods of intense urbanisation and the increased importance of counter-urbanisation is also reflected in changes in the net migration rate for Estonian localities ( Fig. 3 ). Most localities suffered from intense out-migration during the 2000–2011 inter-census period, especially those that are located in central and south-eastern parts of Estonia. These were areas of intense agricultural production during the Soviet period, but they lost their economic importance after Estonia regained its independence in 1991. Many localities on the islands of Saaremaa and Hiiumaa also lost people in the 2000s. Only the suburban areas around the three regional centres of Tallinn, Tartu, and Jõhvi gained migrants.

Net migration rate by localities (‰), 2000–2021.

This extensive rural exodus ended during the economic bust in the first half of the 2010s when migration to non-metropolitan rural areas became widespread. About half of non-metropolitan rural localities enjoyed positive net migration during the 2011–2015 period, while the rest suffered only from modest outwards-migration at that time. The economic boom within the 2015–2019 period brought along again migration losses non-metropolitan rural localities, but we can detect also important variations between them. Firstly, migration losses were concentrated mainly in the main agricultural areas in central Estonia. Secondly, many localities still gained migrants. In addition to positive net migration in the suburban areas around Tallinn and Tartu, the same positive net migration could also be found in western parts of Estonia, most notably on the two main islands of Saaremaa and Hiiumaa, as well as in rural areas along the western coast between Pärnu and Tallinn. As with the economic bust in 2011–2014, the first year of the pandemic reveals widespread change which favours rural-ward migration; about half of non-metropolitan rural localities enjoyed positive net migration, and pockets of localities with positive net migration can be found everywhere in the countryside. In short, counter-urbanisation has not been a dominant migration trend in Estonia during the last thirty years, but non-metropolitan rural areas in general―and the islands and coastal regions in particular―have certainly become more attractive residential destinations to domestic migrants.

The MCI values revealed that the migration of highly-skilled individuals has been more responsive to cycles of economic boom and bust. The maps which are provided in Fig. 4 add more geographic detail in regards to migration for high-skilled and low-skilled individuals. We find that positive net migration rates of both high-skilled and low-skilled people are clustered around the four regional centres, while differences between the two occupational groups exist in non-metropolitan areas. We detect a more intense out out-migration of high-skilled people in central parts of Estonia, and more intense in-migration of low-skilled people in south-east Estonia. The period of economic bust in 2011–2014 brought along a more intense migration of highly-skilled people to non-metropolitan rural areas. The highest net migration values could be found on the islands of Saaremaa and Hiiumaa, and in the coastal areas between Pärnu and Tallinn. These are the most attractive non-metropolitan rural destinations in Estonia. Interestingly, the new period of economic growth in the 2015–2019 period again brought with it a major exodus of high-income households from almost all non-metropolitan rural localities, with the most notable exceptions being the islands of Saaremaa and Hiiumaa. A geographically similar but weaker pattern characterised the migration of low-skilled people at the same time. Finally, negative net migration rates either decreased or became positive across most non-metropolitan rural localities during the first year of the global pandemic with no major differences between high-skilled and low-skilled people. Overall, we can conclude the net migration rate of both high-skilled and low-skilled people tends to become negative during economic boom in most non-metropolitan rural municipalities, and positive during periods of economic bust. What is different is the magnitude of change as the migration of high-skilled people tends to be more responsive to periods of economic boom and bust compared to the migration of low-skilled people.

Net migration rate of low-skilled and high-skilled people by locality (‰), 2000–2021.

1.4. Summary and discussion

The aim of this paper was to shed new light upon the process of counter-urbanisation during the pandemic, in comparison with long-term changes in domestic migration during various periods of economic boom and bust. We defined counter-urbanisation as a process of moving from higher levels of a settlement system to lower levels of that same settlement system, and we were particularly interested in moves to non-metropolitan rural areas during the global coronavirus pandemic. As the pandemic brought about a slow-down in economic growth, our first research questions investigated potential changes in the intensity of migration within the settlement system during the past three decades, and how such migration tends to differ during periods of economic boom and bust, including at a time of a pandemic. We found that migration intensity has been generally responsive to the periods of economic boom and bust but not at times of pandemic. The number of moves per each thousand people was did not decrease in 2020 compared to the earlier period of quick economic growth. As could be expected, young adults aged up to thirty were the most mobile group throughout the length of the thirty-year study period but, more importantly, the mobility of young adults increased to a significantly greater degree than it did for other age groups in the second half of the 2010s, again with no change being registered during the first year of pandemic. Other groups with higher-than-average migration intensity levels during the entire thirty-year study period include members of the ethnic majority population and people with a primary education. Some interesting changes relate to moves being made in terms of occupation groups over time, as mobility increased significantly amongst highly-skilled and medium-skilled people during the economic boom in the 2015–2019 period, but it dropped again during the pandemic, with the overall result being that all occupational groups were equally mobile during the first year of the pandemic.

Our second research question investigated how the balance has changed between urban and counter-urban moves during the last three decades. We found that ‘Migration Concentration Index’ (MCI) values exceed fifty for the entire study period, implying that upward moves within the settlement system (urbanisation) outnumber downward moves within the settlement system (counter-urbanisation). The intensity of urbanisation and counter-urbanisation processes also fluctuates along with periods of economic boom and bust. At a time of economic boom, urbanisation prevails. At times of economic bust, including the first year of pandemic, counter-urbanisation becomes more important, and the migration gains in non-metropolitan rural areas are widespread. The migration of the high-skilled people is somewhat more responsive to periods of economic boom and bust compared to low-skilled people.

Our third research question seeked to find out what are the potential new features in the population composition and geography of moves into non-metropolitan rural areas during the pandemic when compared to earlier periods of economic boom and bust. The results show that the migration intensity of young adults increased, with this being the only age group to contribute to urbanisation. Age-wise, the most notable new feature that emerged during the pandemic was the counter-urbanisation of children under the age of fourteen, indicating that entire families were seeking homes in the countryside more often than they were seeking homes in metropolitan areas. Likewise, the first year of the pandemic reveals an increase in counter-urban migration amongst Estonians. Estonians living in cities have more connections to rural areas compared to ethnic minorities as their parents or grandparents may live in the countryside, or they may have inherited properties or second homes in rural areas (cf. Sandow and Lundholm, 2020 ). Finally, we did not detect any differences in counter-urbanisation between people with different levels of education and occupation during pandemic. However, high-skilled people move more often to attractive destinations in the countryside that include islands and coastal areas.

What could be possible explanations for such changes in domestic migration? A shift from a productionist to a post-production lifestyle (cf. Phillips et al., 2022 ), something which began in Estonia in the 1990s, has had two long-term impacts on rural migration, impacts which intensified during the pandemic. On the one hand, the increase in the share of young adults in each consecutive generation which has been seeking out a better education or working life in the cities has contributed to the rural exodus, as can also be found in other countries such as Sweden ( Bjerke and Mellander, 2017 ), the Czech Republic ( Vaishar and Pavlů, 2018 ), or Spain ( Llorent-Bedmar et al., 2021 ). On the other hand, both families with children and also retired people are now contributing to migration into non-metropolitan rural areas, especially since the start of the pandemic. Therefore, as has been found in Canada ( Mitchell, 2019 ), our analysis also reveals that while mainstream migration tends towards urbanisation, counter-urban migration has become more important as a substream movement at the national scale, and as a mainstream flow in many parts of the countryside.

The spread of counter-urbanisation among people in the family ages may be due to two reasons. Housing affordability in Estonian cities has significantly declined in the capital city urban region (cf. Hess et al., 2022 ). The housing affordability issue has become pressing also in many cities around the globe (van Ham et al., 2021), and seems to have an especially strong effect on families with children. By way of a comparison, a study university graduates in Sweden shows that having children is the single strongest predictor of leaving the cities ( Bjerke and Mellander, 2017 ). Our findings are very similar. Counter-urbanisation is more common amongst children aged up to fourteen years when compared to people who fall within the family bracket of 30–49. Since underaged children move with their parents rather than on their own, this implies that families with children are increasingly seeking homes outside the major metropolitan areas.

However, motives of counter-urbanisation may be very diverse for families. For example, while Elshof et al. (2017) find that families in the Netherlands are attracted by the rural idyll, Bjerke and Mellander (2017) argue that role of rural amenities are modest in Sweden in shaping the migration of families. Instead, they relate counter-urban moves of families to high local levels of welfare, such as the availability of good schools. The importance of well-being for families with children when moving to rural areas has been also found in Norway ( Berg, 2020 ). Karsten (2020) takes a longer view to explain that the scarcity of affordable housing in Amsterdam first led to urbanisation by families and, more recently, to counter-urbanisation.

Her results also show a diversity of mover types among families leaving the cities, including pragmatic movers, displaced families and happy movers ( Karsten, 2020 ). The intensification of moves of families into rural areas due to a wide range of reasons during the pandemic has also been found in Bulgaria ( Pileva and Markov, 2021 ). In short, there is growing evidence that families with children―both return migrants and newcomers―are seeking homes in non-metropolitan rural areas, which may potentially also help to mitigate the long-term problem of aging in the countryside (cf. Bjerke and Mellander, 2017 ). However, inner differences within rural areas are still a concern ( Vaishar et al., 2020 ) as our study also reveals that not all rural localities do gain from counter-urbanisation. What seems to be common across different countries, though, is the modest role of employment-related considerations as a defining feature of migration in post-productionist societies even for people who are of family and working ages: counter-urbanisers move due to the countryside various reasons and more often settle in post-productivist settlement types in the countryside (cf. Mitchell, 2019 ). Estonian case reveals that those rural areas with stronger agricultural base suffer from out-migration while coastal areas and islands gain migrants.

In addition to demographic change, there is also some evidence of socio-economic change taking place in rural areas. The combination of our findings that high-skilled people are more likely to counter-urbanise but their migration is more responsive to economic cycles in a way that moves to non-metropolitan areas intensify at periods of economic bust leads us to mixed interpretations. Firstly, the counter-urbanisation of better-off people does not necessarily reflect a solely preference-driven migration. As the economy slows down, access to long-term mortgages becomes more difficult and people tend to become more cautious in buying expensive homes in cities (cf. Nofsinger, 2012 ). Periods of economic bust could rather make families earning decent incomes to broaden the geographic reach of desired housing. In Estonia, these families seek homes that are located close to the waterfront, which is no different from gentrification processes in Tallinn that is also taking place at the waterfront. Parents earning higher incomes and relocating to rural areas can adapt their work and family life by switching partially to working from home and helping their kids to commute to school ( Pileva and Markov, 2021 ). As a consequence, the importance of rural areas as sites of employment continue to decrease, and the pandemic has reinforced this trend.

To conclude, the global pandemic has increased the attraction of rural living, just as earlier periods of economic bust had done. Pandemic did not only increase temporary moves out of the city ( Willberg et al., 2021 ) or purchases of second homes ( Greinke and Lange, 2022 ), but it also brought along an increase of residential relocations to non-metropolitan rural areas as shown by this study. Counter-urban migration during the pandemic became widespread amongst families, and the better-educated and highly-skilled people are also seeking homes in rural areas. These new features may serve to slow down or even reverse the long-term problems of an aging population loss of educated people in the countryside.

This project has received fuding from Estonian Research Council (PRG306, Infotechnological Mobility Laboratory) and from Estonian Academy of Sciences (research-professorship of Tiit Tammaru).

Author statement

Hereby we state that this paper is our original work and has not been submitted or will be submitted elsewhere for considering of publication.

Declaratin of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

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Counter Urbanisation as Refuge During the COVID-19 Pandemic: A Case Study from Turkey

• Levent Memiş Giresun University, Turkey
• Sönmez Düzgün Giresun University, Turkey
• Semih Köseoglu Giresun University, Turkey

Migration is one of the most fundamental features of human history. Migration still plays an important role today and can occur between countries and settlements for different reasons. Migration activities bring various problems and needs regarding the everyday components of life. In this context, one of the types of migration is counter-urbanisation. Counter-urbanisation refers to moving from the city to the countryside or small settlements with predominantly rural characteristics. Urban areas maintain their attractiveness for individuals and organisations. However, living conditions and the city's structure bring ruralisation to the agenda. This study focuses on counter-urbanisation, a phenomenon that has been reshaped with the COVID-19 pandemic. It examines the impact of this counter-urbanisation on transforming the countryside's communal needs and physical structure. In this context, semi-structured interviews were conducted with 84 people in 17 villages of three districts in Giresun province located in the Black Sea Region of Turkey, and the observation method was utilised. According to the research findings, retirees carry out counter-urbanisation. However, the tendencies of these people covering the pandemic bring on the concept of counter-urbanisation as a refuge. Counter-urbanisation renders the existing organisational structures inadequate regarding communal services and brings new needs to the agenda. On the other hand, efforts to improve existing housing and create new housing bring new situations to the agenda for villages. With policies that will overcome the limitations of these new situations, it will be possible to support the elderly policies carried out by the country and contribute to sustainable development goals by supporting the production in rural areas. This potential calls for regulations and holistic policies that consider life and production functions in rural areas.

• Memiş et al.

ISSN (Online) 1849-2150

ISSN (Print)  1848-0357

DOI: https://doi.org/10.31297/hkju

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COUNTER-URBANISATION EXPERIENCE IN DEVELOPING COUNTRIES: THE CASE OF ISTANBUL METROPOLITAN AREA

2022, VII. INTERNATIONAL CITY PLANNING AND URBAN DESIGN CONFERENCE CPUD '22 CONFERENCE PROCEEDINGS

Urbanization is the popular phenomenon in the 1950s that was replaced with counter-urbanization in the 1970s, which defines the population movement from metropolitan areas to rural settlements. The counterurbanization mobility that is directly shaped by economic development, legal regulations, technological developments, causes the socio-economic and spatial transformation of rural settlements. although there are exceptions, the counter-urbanization process is generally associated with economic development. The research aims to reveal the differences of the counter-urbanization movement in developed and developing countries in terms of process, causes, and effects, and how Turkey's counter-urbanization experience differs from the world examples. With this aim, the method of the research is to examine the counter-urbanization literature in-depth, to put forward the counter-urbanization conceptually. While rural development, gentrification, and sustainability are the focus of rural research in Turkey, the counter-urbanization which has a direct impact on rural areas, has not been sufficiently researched yet. In this way, this research contributes to the counterurbanization literature. However, rural areas are ignored by the legal regulations, rural settlements which are the basis of the country's socio-economic and spatial sustainability are transformed from production centers to consumption centers with the effects of counter-urbanization. The differentiation of the counter-urbanization process according to country, region, and metropolitan scale and blurring of rural-urban borders in metropolitan cities make it difficult to define the counter-urbanization movement. In this context, the definition of the counter-urbanization process within the borders of the metropolitan area, the driving forces causing counterurbanization, and its socio-economic and spatial effects on rural settlements were examined through the example of Istanbul, one of the most important metropolises of Turkey. As seen in the example of Istanbul, the transformation process of the rural life model and the rural economy, the social relations in rural areas, and the counter-urbanized social group differ from the world examples. While the counter-urbanization process emerged with the individual preferences of the households who are ready to adopt the rural life model, in developing countries such as Turkey is managed by mega-scale public and private investments, plan decisions, transformation in legal and administrative structure, and rent. While the rural life form is preserved in developed countries, the urban and rural population acts with a collective consciousness and social integration is ensured. For example, while the rural population transfers the place-specific knowledge to the urban population, the urban population supports rural production models with the integration of information technologies and contributes positively to the socio-economic development of the rural areas. In Turkey, legal regulations, directing public and private investments to rural areas by planning tools resulted in urban sprawl and rural areas and population urbanized with real-estate and construction-oriented development model. Moreover, counterurbanized groups in Turkey even if the movement reason is natural and rural idly, they prefer to isolate themselves from the rural population socio-spatially and deepen the social segregation. Although the counterurbanization process in Turkey started at the local level in the 2000s, factors such as the socio-economic problems experienced in the recent period, the increase in density in the cities and urban problems, the change in the urban demographic structure, and the pandemic trigger the desire for life in the rural areas, and it is observed that the counter-urbanization trend will continue. In this context, to define the counter-urbanization concept clearly and examine the counter-urbanization process in the world is so important to guide the counterurbanization process in Turkey.

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Effects of counter-urbanization on Mediterranean rural landscapes

• Review Article
• Open access
• Published: 29 August 2023
• Volume 38 , pages 3695–3711, ( 2023 )

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• C. Herrero-Jáuregui 1 &
• E. D. Concepción 2  

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Counter-urbanization, or the reverse migration from the city to the countryside, is a well-known demographic trend associated with rural restructuring since the 1980s. Counter-urbanization is particularly relevant in social-ecological systems with a long history of human land use, such as the Mediterranean ones. However, the extent and impacts of this phenomenon are largely unknown, particularly in this region.

We aim to review the state of the issue of counter-urbanization in the Mediterranean region. We focus on the particular determinants and outcomes of this phenomenon in Mediterranean landscapes.

We conducted a bibliographic review using the Web of Science. We summarized and classified the main findings in different categories according to the socio-economic drivers of this process and its impacts on the landscape along the land sharing-sparing gradient.

We found 31 studies that met the criteria to be reviewed and classified them as follows: a first group of studies focused on counter-urbanization as an urban sprawl driver; a second group linked counter-urbanization to rural gentrification. These two groups point to a twofold trend of land intensification or abandonment resulting in land-sparing landscapes. A third group of studies explored the urban–rural migration motivated by economic crisis and rural areas’ role as refugees that support land-sharing landscapes. A fourth group focused on multi-functional, land-sharing landscapes enhanced by rural newcomers.

Conclusions

Although counter-urbanization can follow the usual path of urbanization and gentrification, it may also constitute an alternative way to reverse the current trends of rural abandonment and land-use intensification in Mediterranean landscapes. Public policies play a major role to drive this movement toward the maintenance or recovery of multifunctional landscapes, and to minimize their undesirable impacts.

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Introduction

Social-ecological systems (SES) are complex adaptive systems that are constituted by networks of constant and reciprocal interactions between the socio-economic and biophysical structures of the territories and landscapes (Berkes and Folke 1998 ; Folke et al. 2016 ; Herrero-Jáuregui et al. 2018 ). Ecological systems within any given social-ecological structure supply a series of services or goods to the social system which are essential for human wellbeing. In turn, the social system affects the structure and functioning of the ecological system through the management of natural resources and land uses, based on its values and through the institutions and governance systems with which it is endowed (Morán-Ordóñez et al. 2013 ). These interactions give rise to patterns, structures, and dynamics that feedback through complex loops into the processes that generated them in a continuously evolving manner, thus constituting co-evolving systems (Levin et al. 2013 ). Spatially, these systems are reflected in landscapes with a given composition and configuration, which can be quantified by metrics, so that the study of the structure of the landscape can provide information on the functionality of socio-ecosystems (Herrero-Jáuregui et al. 2019 ). The dynamics of SES and the landscapes they are reflected on are subject to changes generated by direct and indirect drivers that operate synergistically and are very intense in the current process known as Global Change (MEA – Millennium Ecosystem Assessment 2005 ). Under particular socioeconomic and policy contexts, changes in demography promote changes in land use and land cover (LULC) and, consequently, alter ecosystem services (ES) supply (Bruno et al. 2021 ).

Land conversion to achieve the demands of the world’s growing population is one of the main drivers of LULC change (Foley et al. 2005 ; Mendenhall et al. 2014 ). The need to reconcile biodiversity conservation with human activities has given rise to an intense debate in science and policy on what landscape model is more suitable to better achieve both objectives: at one extreme, the model known as ‘land sparing’ advocates occupying less land with intensive land use and taking advantage of the rest of the land for biodiversity conservation (Loconto et al. 2020 ). This model is favored by the global trend of rural–urban migration (> 55% of the world’s population lives now in cities; ONU 2018 ; Liu et al. 2020 ) and associated rural abandonment, and subsequent forest transition and rewilding (Navarro and Pereira 2012 ; Perino et al. 2019 ; Bruno et al. 2021 ), while intensifying productive land in the most appropriate places (i.e., intensive farms vs extensive cattle ranching). In this way, the increase in forest mass would be linked to an increase in regulating services such as carbon sequestration, erosion control, and increased forest species richness (Green et al. 2005 ; Balmford et al. 2019 ). At the other extreme, the ‘land sharing’ conceptual and operational model describes a heterogeneous landscape shaped by a multi-functional agricultural matrix that contributes to biodiversity conservation via wild-life friendly or high nature value (HNV) farming (Lomba et al. 2020 ). Both landscape models are correlates of agri-food models that are an important determinant of population movements. However, studies emerge suggesting that this debate polarizes two solutions that are not necessarily opposed and that evidence indicates that the largely mixed solutions depend on the context (Grass et al. 2019 ). Indeed, non-intensive agriculture is not necessarily less productive than intensive one (Badgley and Perfecto 2007 ), domestic cattle can play the role of large wild herbivores (Gordon et al. 2021 ), and there are other variables at stake besides biodiversity conservation and food production, which would be better reflected using the ecosystem services framework (Tscharntke et al. 2012 ; Loss and Von Wehrden 2018 ). Moreover, in distinctly cultural landscapes, such as Iberian landscapes, the abandonment of agro-silvopastoral systems implies the irreversible loss of biological and cultural diversity (Rescia et al. 2008 ; Morán-Ordóñez et al. 2013 ; Arnaiz-Schmitz et al. 2018 ; Herrero-Jáuregui et al. 2019 ; Pili et al. 2019 ; Schmitz et al. 2021 ). However, other studies argue that even including imperfections, a land-sparing landscape is more effective in reconciling food production with biodiversity conservation (Balmford et al. 2019 ), thus rendering the debate open and alive.

Very recently, an alternative pathway to the forest transition has been described, which has to do with counter-urbanization or the reverse migration phenomenon, from the city to the countryside (Jiménez et al. 2022 ). These authors refer to peri-urbanization as the flow of outmigration of inhabitants settling in existing (and partially abandoned) rural nucleus or hamlets as opposed to the urban overspill that jointly takes place with urban migration and estate development widely studied in the 1980–1990s (Ravetz et al. 2013 ; Serra et al. 2014 ; Shaw et al. 2020 ). Since the 1980s, counter-urbanization is the most well-known demographic trend associated with rural restructuring, affecting countries in different ways (e.g. Weekley 1988 ; Sant and Simons 1993 ; Dahms and McComb 1999 ). Often, counter-urbanization is linked to amenities, leisure activities, and second-home ownership that present rural environments as home places, even when no permanent relocation has taken place (Halfacree 2014 ). According to the global-scale study of Jiménez et al. ( 2022 ), neo-rurals would favor the forest transition by moving to the countryside with an idyllic vision of nature, although often resulting in conflicts with the local population, not only because of the disparity of visions about the rural environment (Martín-Forés et al. 2020 ; Elbakidze et al. 2021 ) but also by generating an increase in land prices that expel the local population (rural gentrification). However, the movement of the population from the city to the countryside in the double aspect of urbanites seeking another type of life (Halfacree 2009 ) and foreign migrants settled in rural areas (Camarero et al. 2009 ; Papadopoulos 2011 ; Sampedro and Camarero 2018 ), could also be a driver of rural development through several pathways: indirectly, by reinforcing local production through their consumption patterns, or directly, by them initiating agricultural activities, mainly part-time (Duguma et al. 2021 ). In this case, the phenomenon of counter-urbanization would favor a heterogeneous landscape immersed in an agricultural matrix (land sharing), contributing to the conservation of biocultural and landscape diversity.

Counter-urbanization is particularly relevant in times of economic crisis and in SES with a long history of human use, such as the Mediterranean ones (Remoundou et al. 2016 ). A ‘back to the countryside’ process has been documented in Greece during the economic recession of 2008–2014, which did not result in a forest transition, but rather took advantage of the rural way of life, products, and activities in the primary sector in the face of the economic crisis (Gkartzios 2013 ; Salvia et al. 2020 ). This reverse migration process incorporated elements of modernity and tradition: new methods of work and organization along with the rediscovery of traditional crops, products, and cultures. In Portugal, too, the role of the rural environment as a safety net in times of economic adjustment has been documented (Silva and Cardoso 2017 ). However, not only economic crises but also health crises such as the recent COVID pandemic can trigger counter-urbanization. According to the Spanish Ministry of Ecological Transition and Demographic Challenge, since 2018 population from small municipalities has been increasing, a phenomenon that has been reinforced by the COVID pandemic, but that was already apparent before (MITERD 2022 ). As per this report, the population that immigrates to small municipalities mainly comes from urban areas. Although not all small municipalities (less than 5000 or even 1000 inhabitants, in the case of Spain, though these figures can vary among countries) can be considered rural, all rural municipalities are small. Thus, results from this report are relevant to explore a recent change of trend in the outmigration movement from small municipalities. Notably, the protagonists of this migration are young people and women. This could reverse the continuous outflow of the young and female population that has predominated until recently and further aggravated the problem of depopulation in rural areas. This positive trend has to be consolidated so that it can compensate for the negative vegetative growth in small municipalities (MITERD 2022 ). Among the causes that may explain these population movements towards rural areas, two key factors are the proximity to cities (up to 1 h) and digital connectivity, that is, the availability of high-speed internet that enables one to work remotely. Recent results in the Spanish case point to an increase of people in municipalities further away from the main city in Madrid region enhanced by teleworking (Belzunegui-Eraso and Erro-Garcés 2020 ; Herrero-Jáuregui et al. 2021 ).

Only a few studies have documented however the effects of this reverse migration process on the landscape structure, biodiversity, and ecosystem services. Some of them have concluded that, although the re-occupied rural environment was more resilient in the face of the economic crisis, the classic biodiversity conservation strategies, through protection figures and restrictive access regulations, were not as solid (Troumbis and Zevgolis 2020 ). A recent study has evinced an incipient expansion of urbanized land into protected areas throughout the European Union (EU) over the last decades, which may compromise their conservation, especially in densely populated areas and vulnerable systems, such as Mediterranean ones (Concepción 2021 ). Besides the recently published work of Jiménez et al. ( 2022 ), which presents a single case study in the Mediterranean basin, there is no other evidence at a global scale of the effects of counter-urbanization on the structure and configuration of landscapes and therefore on the functionality of SES. Thus, the scope and extent of this phenomenon in the Mediterranean basin are largely unknown. Moreover, it may not be appropriate to transfer the rural idyll concept from Anglo-Saxon countries to the Mediterranean region (Hoggart and Paniagua 2001 ). Also, studies suggest that the dispersed city will not be the city of the future in Mediterranean European urban areas mainly due to the failure of suburbia as a space for maintaining social frameworks and family welfare (Dura-Guimera 2003 ).

According to the mentioned above, the overall aim of this paper is to review the state of the art on counter-urbanization in the Mediterranean region, their socio-ecological particularities, in terms of drivers and context, concerning to similar processes occurring in other parts of the world, and their impact on the landscape and the ecosystem services it provides.

We hypothesize that the current counter-urbanization phenomenon in Mediterranean countries will shape different landscapes along the land sharing-sparing gradient, depending on a variety of factors operating at different scales, from local to global: the profile of migrants, the geographical characteristics of rural areas, the economic cycles, the global markets, the socio-political context and the public policies operating in each case. Counter-urbanization effects on the landscape will not be the same if triggered by a teleworking neo-rural population that goes shopping once a month at large supermarkets and is disconnected from local activities, as by those who do so regularly in local markets and are involved in agricultural activities, even on a part-time basis, strengthening short marketing circuits and the valorization of local produce and culture. Neither will be the proliferation of new housing developments that results in urban sprawl or dispersion into the countryside with the subsequent impacts on biodiversity and ecosystems, as opposed to the restoration and reoccupation of empty houses that maintain compact villages and towns surrounded by a cultural landscape made of agricultural and natural elements.

We conducted a bibliographic review on the drivers and effects of counter-urbanization or urban–rural migration on Mediterranean landscapes, summarizing the main findings. First, we conducted a literature search in the Web of Science database looking for all entries which included in the topic the following search terms: (counter-urbanization OR counter-urbanisation OR counterurbanization OR counterurbanisation OR urban–rural migration OR urban emigration OR urban outmigration OR rural immigration OR amenity migration) AND (landscape OR land use) AND (Mediterranean OR Iberian).

We defined the knowledge areas to which all the entries belonged and read all abstracts to select the publications that met the criteria for deeper analyses (Fig. 1 ). We then read all the articles and summarized the information according to the following variables: (1) type of study (discussion paper, empirical research, review); (2) site of study (geographic reference); (3) type of area (coast, mountain, rural, metropolitan area); (4) spatial scale (local, regional, national, continental); (5) time period; (6) methods and type of analysis (LULC analysis, spatial analyses, interviews, and questionnaires, review); (6) research question and (7) conclusions. We defined a spatial scale as local when case studies were restricted to a small area within the same social-ecological unit (similar social and ecological characteristics and relationships between them). The spatial scale was considered regional when case studies belonged to more than one social-ecological unit. We classified conclusions in different categories according to the main effects on the landscape found in each case: whether rural immigration promoted rural gentrification, urban sprawl or suburbanization dynamics, tourism development, disconnection from rurality, and land or ecosystem degradation due to unsustainable resource use and unbalance demand/supply of Ecosystem Services. We also included socio-economic drivers and considered whether public administrations, economic and work markets, or leisure and lifestyle played an active role in each process. We summarized the main findings and discussed them in light of further results and reports about urban–rural migration.

Systematic review flow diagram based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA, Moher et al. 2009 )

We found 68 results from 1999 to September 2022, 50% of which were published after 2016. The most represented areas were environmental sciences and ecology (72%), geography (56%), business economics (44%), and biodiversity conservation (43%).

From the 68 publications, only 31 publications reporting 36 case studies met the criteria for a deeper analysis: this is, studies that analyzed landscape composition and/or configuration in the light of urban–rural migration and/or the socio-economic drivers of this process (Table 1 ).

Spain was the country with the most case studies (31%), followed by Italy, Turkey, and Greece (17% each), Portugal (5%), and Romania, Syria, Austria, and France (2% each). Notably, no African country or any of those located in the most oriental region of the Mediterranean were studied (Fig.  2 ).

Geographic location and the number of case studies included in the bibliographic review. Pie chart size is proportional to the total number of studies in each country. They show the percentage of studies focusing on the topics classified in group I (urban sprawl and suburbanization), II (rural gentrification), III (safety net in times of crisis) and IV (recovery of multi-functional landscapes). See below for details of the group description

The spatial scale mostly used in the analyses was regional (58%), followed by local (19%), national (16%), and continental (6%). Regarding the type of region analyzed, most of them studied metropolitan areas (26%) followed by rural areas and the whole region (with no distinction of the area, 23%). A particular distinction was made between mountain areas (16%) and coastal areas (12%) (Table 1 ).

The temporal scale most commonly analyzed was a time span of a 40-year period (33.33%), followed by a period of 10 (26.67%) and 20 years (20%). Less than 10% of studies analyzed longer periods (60 or 80 years). Notably, none of the 31 studies analyzed population movement enhanced by the COVID pandemic (Table 1 ).

Regarding the type of data used, two types of empirical studies can be identified, each comprising half of the total studies: Those using LULC spatially explicit data and/or public statistics and those using semi-structured interviews and sometimes supporting public statistics. Remarkably, there was only one study that combined LULC analysis (spatially explicit) with interviews with local stakeholders (Acebes et al. 2021 ). There was only one review and discussion study (Dura-Guimera 2003 ).

Based on the main focus and results of the studies revised, they can be divided into four groups (Table 1 ): (I) a group of studies focuses on the effects of urban sprawl and suburbanization enhanced by counter-urbanization (29%). This category encompasses some of the others, but deserves a category for itself, as the main focus of these studies is the urban overspill that jointly takes place with urban migration and estate development; (II) some studies conclude that the process of counter-urbanization generally by amenity migrants, generates rural gentrification through the revalorization of housing heritage which expels local population due to the increment in prizes. This is usually accompanied by a displacement of rural activities by tourism and leisure and by a general process of disconnection from nature (38%). These two groups of studies point to landscapes of land-sparing type, with an intensification of rural activities in the most productive sites and abandonment of rural activities elsewhere; (III) A third group of studies, mainly from Greece, explores the urban–rural migration motivated by economic recession and highlights the role of rural areas as a safety net that support people livelihoods in times of crises (6%), mainly on a land sharing basis; (IV) A fourth group shows results of a land sharing type of landscape being supported and maintained by rural newcomers that revitalize local economies and promote the recovery of cultural and multi-functional landscapes (25%). In this last group, the difference of origin of newcomers (young people, amenity migration, or refugees) is an important aspect regarding the use of the territory and possibilities of land use change. Finally, 16% of studies point to public policies as a main factor defining the outcomes of contra-urbanization at the landscape level (see details on addressed issues and main findings of each study included in this review in Appendix S1).

Our research reviews the existing literature on the relationship between counter-urbanization and landscape structure in the Mediterranean region. Although global counter-urbanization literature, particularly in northern countries dates back to 1978, it is striking the paucity of literature on the effects of counter-urbanization on the landscape, particularly in the Mediterranean region: only 31 studies have been identified that tackle somewhat the issue and just one of them has used an empirical approach to both measure counter-urbanization and landscape configuration (i.e., through landscape metrics) (Satir and Erdogan 2016 ).

A reason for that could be that rural immigration does not directly generate changes in land use that are reflected in the landscape. Indeed, if rural immigrants resume agricultural activities that were being already performed, such as pastoralism, the change of actors will not be reflected in a change in land use, as pasturelands will continue being pasturelands. This happens in some regions in Spain, where cattle ranching activities have almost completely been undertaken by north African immigrants, with no noticeable landscape change (Nori 2017 ; Nori et al. 2020 ). Similarly, if rural immigrants are attracted by a natural environment characterized by a low level of human intervention, they will promote the current re-wildering process going on across Europe (Jiménez et al. 2022 ), and their arrival into rural areas will not be noticed at the landscape level, in another way than through an increment of building areas (Concepción 2021 ).

Another reason could be that although rural immigrants do generate a change in land use, either directly or indirectly through their consumption behavior of locally produced products, this change has taken place very recently and thus it is still unnoticeable in the landscape. Considering the Spanish report that shows a change in depopulation tendency since 2018 (MITERD 2022 ), 4 years could be a too short period for land use changes to be effectively reflected in a change in landscape structure. However, as several of the reviewed studies point out (e.g., Dura-Guimera 2003 ; Benessaiah 2021 ; Kocabiyik and Loopmans 2021 ) there is an important need to analyze the effects of rural immigration on Mediterranean landscapes and its relation with the balance supply/demand of ecosystem services. Through this section we develop the main conclusions found in the literature review, divided into the four groups described in the results.

Urban sprawl and suburbanization

There is evidence all across Europe and particularly in Mediterranean countries of a process of urban sprawl and agricultural intensification in flat and irrigable areas, together with a process of land abandonment and forest expansion in uplands and more remote areas (Salvati et al. 2017 ). Also, tourism and leisure activities are replacing traditional economies. This is perceived as a threat to the cultural heritage and linkage with the territory of rural people (Acebes et al. 2021 ). Those land use changes are driven by a global economy, demographic trends, and joint effects of diverse EU policies (van der Sluis et al. 2019 ). Overall, particularly Mediterranean countries are suffering a shift from a spatially-balanced, structurally-complex and functionally-diversified agricultural landscape to a homogeneous, simplified, and fragile system (Zambon et al. 2018 ), while diffuse urbanization is co-occurring with intensive cropland expansion over mosaic and extensive cropping systems. Thus, counter-urbanization could be a rebound effect of urbanization and peri-urbanization processes in agricultural areas. Dispersed urban expansion frequently reflects the spatial relocation of economic activities in search of cheaper land (Venanzoni et al. 2017 ).

This movement of people from urban to rural areas, in search of a quieter lifestyle and more in contact with nature, might jeopardize the maintenance of traditional agriculture and foster an overall decrease in human-nature connectedness (Pacheco-Romero et al. 2021 ), together with the ongoing rewilding process (Jiménez et al. 2022 ). If this was the case, counter-urbanization should correlate with the rate of loss of traditional agricultural activities, which would reflect in a land-sparing type of landscape and upset the balance between supply and demand of ecosystem services (Herrero-Jáuregui et al. 2019 ). Indeed, the intense urbanization process recorded along the European Mediterranean coast enhanced by second home urbanization of retirees from the UK and the EU has had far-reaching impacts on landscapes and ecosystem services, such as lower agricultural production, the reduction of groundwater recharge, soil degradation, and salination, marginalization of natural vegetation, disruption of habitats or microclimatic changes due to either the widespread expansion of impervious surfaces or an exacerbated overconsumption of natural resource (Zasada et al. 2010 ). These impacts were in turn reinforced by the Spanish housing bubble (Burriel de Orueta 2016 ). Fuerteventura, an island of the canary archipelago (Spain), has shown a ‘deruralization” transition from a local socio-ecological system based on traditional land-use practices to one based on coastal tourism (Schmitz et al. 2018 ). Likewise, the economic growth in the coastal region of Syria has driven the diversification of rural activities, especially in the service sector, which has resulted in agricultural intensification, industrialization, and urban sprawl, and all this in turn in a rural population disconnected from rurality (Khadour et al. 2021 ). Counter-urbanization thus entails the risk of transferring the residential and touristic growth model of the Mediterranean coast, which implies massive development and the extensive occupation of the territory, to the inland municipalities (Solana-Solana 2010 ).

Rural gentrification

Parallel to counter-urbanization processes, there is evidence of rural gentrification and the expulsion of local people through the rise of prizes of rural properties (Alonso-González 2017 ; Uysal and Sakarya 2018 ), but also through changes in leisure and retail activities, consumption patterns, and valuation of rural properties, whether used for housing or other purposes (Phillips 2002 ). For example, in Turkey, the designation of a national park promoted the creation of second-home or amenity real estate market within or around their villages, while their traditional inhabitants migrated to other towns and most or nearly all households and land parcels were sold to amenity in-migrants (Hurley and Ari 2018 ). Other studies show how in rural areas where tourism facilities have been improved, gentrification occurs in parallel. The migration of the middle class to the villages transforms the traditional land use and rural landscape. In Turkey, the increase in the demand for new housing threatens the olive groves and increasing real estate prices makes it difficult for local people to acquire property in the villages (Uysal and Sakarya 2018 ), while in some Spanish regions increasing housing demand has triggered a significant bubble in real estate prices with important consequences for the local economy and ways of life (Alonso-González 2017 ).

Rural gentrification in emerging economies may contribute to the local economy but at the expense of the displacement of the local inhabitants that continue migrating to cities (Kaya 2007 ; Kocabiyik and Loopmans 2021 ). In Turkey, public investment and policies to promote that people come back to rural areas have not been effective to reverse the effect of mass subventions to tourism and industrial facilities that together with security problems encouraged rural inhabitants to migrate to cities in the recent past (Satir and Erdogan 2016 ). Also, economic growth in the coastal region of Syria has driven the diversification of rural activities, especially in the service sector, agricultural intensification, urban sprawl and industrialization, which has resulted in a rural population disconnected from rurality (Khadour et al. 2021 ). The decline in the rural population and the abandonment of lands has increased the forest areas and, thus, favoring land-sparing (Ünal et al. 2019 ). Overall, the replacement of the agricultural sector by the service sector and change in land use creates post-productive rural landscapes, which shift from areas of production to spaces of consumption with a mismatch between the demand and supply of ecosystem services (e.g., food production or recreational activities) (Alonso-González 2017 ; Uysal and Sakarya 2018 ; Bianchini et al. 2021 ).

Rural refuge in time of crisis

However, as some researchers have suggested, the transfer of the rural idyll concept from other countries (notably Anglo-Saxon) to Spain is not appropriate (Hoggart and Paniagua 2001 ), and there are limits to the applicability of Anglo-American theories of deconcentration for the Mediterranean city (Dura-Guimera 2003 ), that would result in a land sparing type of landscape. One of the reasons might be typical Mediterranean expanded family networks and a continuum between urban and rural landscapes (Salvati et al. 2017 ; Benessaiah 2021 ). For example, in Greece, going back to the land enhanced by the 2008 economic recession was facilitated by high rates of rural housing and land ownership, mainly through family networks linking rural and urban areas, that maintained a rural land-sharing type of landscape through small-scale family farming (Salvia et al. 2020 ; Benessaiah 2021 ). Indeed, the resilience to external shocks (in this case, economic recession) of such land-sharing landscapes shaped by small-scale family farming seems to be higher than that of land-sparing types, such as urban, industrial, and intensive agriculture, as happened in Greece (Serra et al. 2014 ; Salvati 2018 ). After the 2008 financial crisis, a trend for the return to the land appeared in Mediterranean countries. The awakening of the rural areas creates the need for additional research into the concepts of rural, rurality, and rural revitalization, amongst others. Images of remote rural areas across Europe show depopulation, revealing the impact of politics on a particular place and the ensuing development of public policies (Paniagua 2010 ). This is in contrast to the rural renaissance arising from the return to the land where the countryside is presented as a refuge for the people of the towns (Hilmi and Burbi 2016 ). Also, the economic dependency on agriculture and direct connection to nature results in a greater awareness of the landscape among the inhabitants living in rural places, with lifestyle contributing to the preservation of the landscape’s character and identity (Khadour et al. 2021 ).

Lastly, even though none of the studies analyzed population movement enhanced by the COVID pandemic, we believe that during the pandemic, new perceptions have arisen about living in the village. In most countries of the world, the imposition of lockdown pushed populations to relocate from cities to rural areas to the localities of their origins (e.g. Denis et al. 2020 ) something that has given rise to scenarios for the future of the cities and the revitalization of the villages (Beria and Lunkar 2021 ). Thus, further studies in the Mediterranean region are needed that help develop locally rooted theories of counter-urbanization that take into account the specificities of Mediterranean cultures and landscapes.

Rural newcomers as change actors

Current rural newcomers, usually part-time or hobby farmers, frame their “dwelling” on moral discourses and see their land as cultural heritage rather than as a personal ownership of productive land (Orsini 2013 ). The majority of these newcomers, many of whom have children, are either self-employed or telecommuters. They often implement innovative business ideas and thus create local jobs in the vicinity of their new residences (e.g., handicrafts, art, or executive functions in tourism and agriculture) (Löffler et al. 2016 ). This can be a driver of change toward land-sharing landscapes, at least avoiding them from the ongoing trend of abandonment-intensification-urbanization described above. Several studies show how a new type of agriculture is being developed by rural newcomers that is resulting in the expansion or maintenance of a cultural landscape, particularly in mountain areas. In a study in peripheral Alpine areas, Löffler et al. ( 2016 ) found that newcomers, with the support of both new and long-established residents, are revitalizing arable land and terraces and regenerating ancient cultural paths. Besides, the restoration of vernacular farm buildings contributes to rural landscape sustainability and the return to traditional agriculture that boosts stable ecosystem balances (Cillis et al. 2020 ). In the Western Balkans, the rehabilitation of traditional houses has contributed to rural socio-cultural and economic sustainability, preserving the heritage and further improving the ecological quality of housing units and their adjustment to present standards (Kosanović et al. 2019 ; Ntassiou 2022 ). Counter-urbanization process close to protected areas shows that, despite the risk of gentrification and urban sprawl (Hurley and Ari 2018 ; Concepción 2021 ), may promote sustainable local development and rural multifunctionality through environmentally added value activities (Tulla et al. 2017 ; Moren-Alegret et al. 2018 ). In these areas, finding a balance between socioeconomic growth and environmental protection is key. An evaluation of the extent to which regional nature parks in France were associated with the development of their territories indicates these protected areas were not detrimental to local economic development, but even positive to attract population, tourism, business, and employment (Cremer-Schulte and Dissart 2015 ).

On the other side, previous research has shown that migrants living in rural areas and working in agriculture can have a fundamental role in sustaining certain types of agricultural production in constant demand for temporary work. Migration is already playing an important role in slowing down aging in some member states, and immigrants share a relevant part of the agricultural workforce in several European countries, where the proportion of rural employment that is filled by migrant workers has gradually increased over time. However, these facts are often coupled with low integration outcomes both in rural areas in general, and in the agricultural sector in particular, where migrants are more likely to work in elementary occupations, to be employees, and to have temporary forms of recruitment than locals (Kalantaryan et al. 2021 ).

The role of administrations

Current urban–rural migration is a highly distinctive phenomenon, as it is immersed in the context of worldwide concern for global change, livelihood sustainability, circular economy, internet access, and flexibility through telework (Duguma et al. 2021 ). The counter-urbanization movement driven by the recent pandemic contains differential aspects concerning previous movements, at least in the Mediterranean context. The concept of rurality is being redefined (Rich 2021 ), and better communications and services are in place as are also opportunities for jobs not necessarily related to the primary sector. Teleworking thus can become a very important tool for rural reoccupation, in parallel to current discussions for the relocation of private firms and public administration. COVID-19 has proved that people can work remotely even from the village. In a post-COVID era, we anticipate new working conditions that allow everyone to work from everywhere, enabling the return to the village. At the same time, in many cases, there are conditions of associationism, internet connection, and knowledge for the local product to easily reach new consumers. Furthermore, this is all taking place at a time of great concern for Global Change, with the modification of consumption habits, the circular economy and short marketing circuits, new forms of associationism and producer–consumer relations, and the agro-ecological revitalization of the territories becoming progressively more important to ensure the socioecological viability of multifunctional rural landscapes (Lomba et al. 2020 ). Also, multi-functional agricultural landscape provision responds to a social demand (Sayadi et al. 2009 ). This is taking place all across Europe, with regional and local heterogeneities that do not neglect these generic trends (Pinto-Correia et al. 2018 ). However, while these back-to-the-land trends contribute to enhancing people’s resilience and may play a role in the growth of sustainable farming and rural revitalization, much remains unknown regarding the processes involved (Benessaiah 2021 ).

Public initiatives to facilitate the integration of rural immigrants within local communities can help the long-term establishment of this new population engaging in rural activities, not only as employees but as self-employed. The manifold experiences of the integration performed by community action in Austria, Italy, and Romania pointed to three main aspects as crucial to integration: the presence of a supportive social environment, the engagement of local actors who broker contacts between the groups, and the availability of appropriate meeting spaces (Gretter et al. 2017 ). Public administration can easily facilitate these processes.

Finally, small-scale farming activities are key elements in shaping multifunctional landscapes made up of a mosaic of heterogeneous land uses. As some studies show, local initiatives in the management of traditional and cultural landscapes can be very effective when they focus on small-scale areas and specific landscape qualities (such as management of the traditional elements of a Mediterranean agricultural landscape) (Selman 2004 ; Orsini 2013 ). However, Common Agricultural Policy (CAP) regulations and subsidies have been historically designed for large exploitations, thus promoting the intensification and homogenization of landscapes and the abandonment of less profitable small-scale farms (Concepción et al. 2020 ; Pardo et al. 2020 ). Administrations should promote legislation specifically designed for small exploitations so that they can cope with the procedures and bureaucracy associated with them. Recently new legislation has arisen in Spain (Royal Decree, RD 1086 /2020), which aims at adapting EU regulations to small-scale farming. Besides, the new CAP (EU Regulation 2021 /2116) will include from 2023 onwards a redistributive payment, this is an additional income support for the first hectares of each farm, to support small and medium-sized exploitations, most of which are family and professional farms. It is necessary to explore whether these initiatives facilitate rural activities thus maintaining and shaping Mediterranean multifunctional landscapes.

Although counter-urbanization in the Mediterranean can follow the already described path of urbanization, touristification, gentrification, and loss of rural identity, there is evidences that Mediterranean countries share some differences with Anglo-Saxon and northern European countries where most literature on counter-urbanization and rural idyll has been developed. There is currently a new impulse of counter-urbanization supported by the extended net of socio-economic linkages along the rural–urban gradient still existing in Mediterranean countries that can reverse the trend of rural abandonment and land-use intensification that shapes land-sparing landscapes. Counter-urbanization, even with the risk of gentrification and urban sprawl, may foster sustainable rural development and multifunctionality. For this purpose it is crucial to find a balance between socioeconomic growth and environmental protection.

Public administrations can play a pivotal role in riding this new wave of rural occupation by different types of migrants (amenity migrants, refugees, young people, families with kids, etc.) and promoting a certain type of landscape. First, more studies are needed that look at the factors that are triggering this change to promote this movement from administrations interested in reverting population loss. Also, it is necessary to look at the effects that this change in demography is having on landscapes and associated ecosystem services. If administrations are interested in preserving Mediterranean multifunctional landscapes and preventing further outmigration from rural areas, maintaining local agricultural activities, recovering abandoned fields and traditional elements of the rural landscape, and including them in existing recreational programs of rural tourism, are among the strategies to take full advantage of this aesthetic landscape potential, and to foster sustainable development of these regions.

Finally, to offer scientifically based guidelines towards the maintenance or renaissance of multifunctional landscapes, and minimize the negative impacts of rural immigration, it is crucial to understand this movement, its drivers, and the consequences on landscapes.

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Herrero-Jáuregui, C., Concepción, E.D. Effects of counter-urbanization on Mediterranean rural landscapes. Landsc Ecol 38 , 3695–3711 (2023). https://doi.org/10.1007/s10980-023-01756-1

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Where is it located in regards to London?

100km north of London

How long do trains take to Kings Cross, London?

What % of the population commute to London everyday?

Have the shops and services in the town changed? if so what have they changed into?

Yes, designer clothes shops and restaurants (high-status services)

Whats the problem with the housing stock?

pressure to increase it

If a development is made what must it do?

make a positive contribution to the character of the area

Is there an increasing gap between the commuters and farmers?

Is there a problem with traffic?

yes, congestion especially on A14 during rush hour

What did the average price of a house rise from and to in 2000 - 2010?

From £130,000 in 2000 to £291,000 in 2010

Whats a problem with being located on the River Great Ouse?

Houses are being built on the floodplain

Due to a changing population structure to becoming more youthful, what has pressure been put on?

How much was the bus way link from St Ives to Huntington and Cambridgeshire in hope to reduce congestion?

£116million

What plans were approved in 2010?

to build 200 new homes (75 of which are affordable)

How many more places will be available at primary schools once expanded?

240 new places

Flood protection works costing how much were built after flooding in both 1998 and 2003?

£8.8million

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ORIGINAL RESEARCH article

Evaluating the impact of urban landscape elements on the sense of security and local belonging-case study: tongdejie, china provisionally accepted.

• 1 Yangzhou University, China
• 2 Keio University, Japan

The final, formatted version of the article will be published soon.

The urban landscape as one of the shaping elements of the urban space and a part of physical perception leaves a significant impact on the desirability or undesirability of the urban space. Urban space has the most connection with people and living environment, and as a result, it plays a significant role in giving identity and feeling of peace to citizens. Security is also considered as one of the basic needs in the urban structure, which becomes more important with the expansion of the urbanization process and the increase in population density. If the image of urban spaces is confusing, hateful or monotonous, it has an adverse effect on the citizens and their feelings and reduces the sense of security. Also, the urban landscape is a tool that can have a positive impact on urban life by planning for its optimal design, increasing the sense of belonging of citizens to the city and the surrounding envi-ronment. In this research, the relationship between the urban landscape components on the sense of local belonging and the relationship between the sense of security and the urban landscape was investigated. Based on the results, sense of local belonging and sense of security had a positive and significant correlation. Therefore, living in a safe, attractive and desirable environment creates and strengthens the feeling of belonging to the envi-ronment. Strengthening the feeling of belonging to the environment will increase the satisfaction of the residents and will increase the quality of life in the cities.

Keywords: urban landscape, Urban landscape elements, Sense of security, Sense of local belonging, security

Received: 17 Nov 2023; Accepted: 21 Mar 2024.

Copyright: © 2024 Zhu and Du. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Ruichao Du, Keio University, Minato, Japan

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Title: enhancing llm factual accuracy with rag to counter hallucinations: a case study on domain-specific queries in private knowledge-bases.

Abstract: We proposed an end-to-end system design towards utilizing Retrieval Augmented Generation (RAG) to improve the factual accuracy of Large Language Models (LLMs) for domain-specific and time-sensitive queries related to private knowledge-bases. Our system integrates RAG pipeline with upstream datasets processing and downstream performance evaluation. Addressing the challenge of LLM hallucinations, we finetune models with a curated dataset which originates from CMU's extensive resources and annotated with the teacher model. Our experiments demonstrate the system's effectiveness in generating more accurate answers to domain-specific and time-sensitive inquiries. The results also revealed the limitations of fine-tuning LLMs with small-scale and skewed datasets. This research highlights the potential of RAG systems in augmenting LLMs with external datasets for improved performance in knowledge-intensive tasks. Our code and models are available on Github.

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