Changes in the Geographical Distributions of Global Human Settlements

doi:10.5814/j.issn.1674-764x.2021.06.011

Abstract

Abstract:

In recent decades, the continuous growth in the population has significantly changed the area of human settlements across the globe. The change of human settlements has brought great challenges to human development, environmental change, resource allocation, and disaster prediction and prevention. In the current paper, we integrate data products provided by the European Commission, Joint Research Centre with multi-source remote sensing data to analyze the changing trends of global human settlements under varying geographical distributions from 1990 to 2014. The results demonstrate that on the global scale, human settlements are generally distributed in Europe, East Asia, Southeast Asia, South Asia, the eastern United States, the Gulf Coast and the coast of Oceania, with most of them distributed in urban agglomerations and coastal areas. Global human settlements have continued to grow over the past 25 years, mainly in East Asia, Western Europe and the United States. The area of human settlements in eastern Europe has been slightly reduced. The distribution of human settlements is affected by climate, water and terrain conditions. Humans were more likely to have settled in temperate regions with wetter climates, and most of the human settlements are located within 500 km of the coastline and 30 km of land-based water sources. Our results can provide insights into further investigations of the spatio-temporal dynamics of human settlements and its connections to ecological and environmental issues in a changing world.

Key words: human settlements, protected area, temporal and spatial variation, GHSL

YE Hongtao, MA Ting. Changes in the Geographical Distributions of Global Human Settlements[J]. Journal of Resources and Ecology, 2021, 12(6): 829-839.

Figures/Tables 16

Fig. 1 Global area of human settlements over the past 30 years Note: AF-Africa; AS-Asia; EU-Europe; NA-North America; OA-Oceania; SA-South America.

Fig. 2 Distribution of human settlements in 2014

Fig. 3 Distribution of human settlements by longitude and latitude

Fig. 4 Top 20 countries in terms of human settlements and rank-size rule analysis

Fig. 5 Changes in human settlements (1990-2014)

Fig. 6 Changes in human settlements in Asia (1990-2014)

Fig. 7 Changes in human settlements in regions of North America (1990-2014)

Fig. 8 Variations in human settlements in Europe, Western Asia and the northern parts of Africa (1990-2014).

Table 1 Areas of human settlements within 10 and 50 km of protected areas

Distance (km)	Area (km²)
Distance (km)	1990	2000	2014
≤ 10	21475	25655	30010
≤ 50	86930	102020	117270

Fig. 9 Distribution of human settlement areas close to protected areas

Fig. 10 Distribution of human settlement area close to ocean

Fig. 11 Distribution of human settlement area close to land water

Table 2 Köppen-Geiger climate classification

Name	Representative characteristics
Af	Tropical, rainforest
Am	Tropical, monsoon
Aw	Tropical, savannah
BWh	Arid, desert, hot
BWk	Arid, desert, cold
BSh	Arid, steppe, hot
BSk	Arid, steppe, cold
Csa	Temperate, dry summer, hot summer
Csb	Temperate, dry summer, warm summer
Csc	Temperate, dry summer, cold summer
Cwa	Temperate, dry winter, hot summer
Cwb	Temperate, dry winter, warm summer
Cwc	Temperate, dry winter, cold summer
Cfa	Temperate, no dry season, hot summer
Cfb	Temperate, no dry season, warm summer
Cfc	Temperate, no dry season, cold summer
Dsa	Cold, dry summer, hot summer
Dsb	Cold, dry summer, warm summer
Dsc	Cold, dry summer, cold summer
Dsd	Cold, dry summer, very cold winter
Dwa	Cold, dry winter, hot summer
Dwb	Cold, dry winter, warm summer
Dwc	Cold, dry winter, cold summer
Dwd	Cold, dry winter, very cold winter
Dfa	Cold, no dry season, hot summer
Dfb	Cold, no dry season, warm summer
Dfc	Cold, no dry season, cold summer
Dfd	Cold, no dry season, very cold winter
ET	Polar, tundra
EF	Polar, frost

Fig. 12 Distribution of human settlements among the different Köppen-Geiger climatic classifications

Fig. 13 Human settlement area distribution relative to elevation

Fig. 14 Human settlement area distribution relative to slope

References 34

[1]	Abel N, Gorddard R, Harman B, et al. 2011. Sea level rise, coastal development and planned retreat: Analytical framework, governance principles and an Australian case study. Environmental Science & Policy, 14: 279-288.
[2]	Addo K A. 2013. Shoreline morphological changes and the human factor: Case study of Accra Ghana. Journal of Coastal Conservation, 17(1): 85-91. DOI URL
[3]	Allen G H, Pavelsky T M. 2018. Global extent of rivers and streams. Science, 361(6402): 585-588. DOI URL
[4]	Angel S, Parent J, Civco D L, et al. 2011. The dimensions of global urban expansion: Estimates and projections for all countries, 2000-2050. Progress in Planning, 75(2): 53-107. DOI URL
[5]	Antonioli F de Falco G, Lo Presti V, et al. 2020. Relative sea-level rise and potential submersion risk for 2100 on 16 coastal plains of the Mediterranean Sea. Water, 12(8): 2173. DOI: 10.339/w12082173. DOI URL
[6]	Baisero D, Visconti P, Pacifici M, et al. 2020. Projected global loss of mammal habitat due to land-use and climate change. One Earth, 2(6): 578-585. DOI URL
[7]	Beck H E, Zimmermann N E, McVicar T R, et al. 2018. Present and future Koppen-Geiger climate classification maps at 1-km resolution. Scientific Data, 5: 180214. DOI: 10.1038/sdata.2018.214. DOI URL
[8]	Cohen B. 2004. Urban growth in developing countries: A review of current trends and a caution regarding existing forecasts. World Development, 32: 23-51. DOI URL
[9]	Egan P J, Mullin M. 2016. Recent improvement and projected worsening of weather in the United States. Nature, 532(7599): 357-360. DOI URL
[10]	Esch T, Marconcini M, Felbier A, et al. 2013. Urban footprint processor—Fully automated processing chain generating settlement masks from global data of the TanDEM-X Mission. IEEE Geoscience and Remote Sensing Letters, 10(6): 1617-1621. DOI URL
[11]	Esch T, Taubenböck H, Roth A, et al. 2012. TanDEM-X mission—New perspectives for the inventory and monitoring of global settlement patterns. Journal of Applied Remote Sensing, 6(1): 061702-1. DOI: 10.1117/1.Jrs.6.061702. DOI
[12]	Fang Z H, Liu Z F, He C Y, et al. 2020. Will climate change make Chinese people more comfortable? A scenario analysis based on the weather preference index. Environmental Research Letters, 15(8): 084028. DOI: 10.1088/1748-9326/ab9965. DOI URL
[13]	Gong P, Li X C, Zhang W. 2019. 40-Year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing. Science Bulletin, 64(11): 756-763. DOI URL
[14]	Gray C, Mueller V. 2012. Drought and population mobility in rural Ethiopia. World Development, 40(1): 134-145. DOI URL
[15]	Haddad N M, Brudvig L A, Clobert J, et al. 2015. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Science Advances, 1(2): e1500052. DOI: 10.1126/sciadv.1500052. DOI URL
[16]	Haer T, Kalnay E, Kearney M, et al. 2013. Relative sea-level rise and the conterminous United States: Consequences of potential land inundation in terms of population at risk and GDP loss. Global Environmental Change, 23: 1627-1636. DOI URL
[17]	Hauer M E, Evans J M, Mishra D R. 2016. Millions projected to be at risk from sea-level rise in the continental United States. Nature Climate Change, 6(7): 691-695. DOI URL
[18]	Hauer M E, Hardy R D, Mishra D R, et al. 2019. No landward movement: Examining 80 years of population migration and shoreline change in Louisiana. Population and Environment, 40(4): 369-387. DOI URL
[19]	Hijmans R J, Cameron S E, Parra J L, et al. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15): 1965-1978. DOI URL
[20]	Hunter L M, Murray S, Riosmena F. 2013. Rainfall patterns and US migration from rural Mexico. International Migration Review, 47(4): 874-909. PMID
[21]	Hutyra L R, Yoon B, Hepinstall-Cymerman J, et al. 2011. Carbon consequences of land cover change and expansion of urban lands: A case study in the Seattle metropolitan region. Landscape and Urban Planning, 103(1): 83-93. DOI URL
[22]	Ibisch P L, Hoffmann M T, Kreft S, et al. 2016. A global map of roadless areas and their conservation status. Science, 354(6318): 1423-1427. DOI URL
[23]	Lehner B, Döll P. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology, 296(1-4): 1-22.
[24]	Leyk S, Runfola D, Nawrotzki R J, et al. 2017. Internal and international mobility as adaptation to climatic variability in contemporary Mexico: Evidence from the integration of census and satellite data. Population, Space and Place, 23(6): e2407. DOI: 10.1002/psp.2047. DOI
[25]	McDonald R I, Kareiva P, Forman R T T. 2008. The implications of current and future urbanization for global protected areas and biodiversity conservation. Biological Conservation, 141(6): 1695-1703. DOI URL
[26]	Nawrotzki R J, Hunter L M, Runfola D M, et al. 2015. Climate change as migration driver from rural and urban Mexico. Environment Research Letters, 10(11): 114023. DOI: 10.1088/1748-9326/10/11/114023. DOI URL
[27]	Nicholls R J, Leatherman S P. 1996. Adapting to sea-level rise: Relative sea-level trends to 2100 for the United States. Coastal Management, 24(4): 301-324. DOI URL
[28]	Pesaresi Martino, Ehrilch Daniele, Florczyk Aneta J, et al. 2015. GHS built-up grid, derived from Landsat, multitemporal (1975, 1990, 2000, 2014). European Commission, Joint Research Centre (JRC).
[29]	Seto K C, Fragkias M, Guneralp B, et al. 2011. A meta-analysis of global urban land expansion. Plos One, 6(8): e23777. DOI: 10.1371/journal.p one.0023777. DOI URL
[30]	Seto K C, Guneralp B, Hutyra L R. 2012. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Science of USA, 109: 16083-16088. DOI URL
[31]	Small C, Nicholls R J. 2003. A global analysis of human settlement in coastal zones. Journal of Coastal Research, 19: 584-599.
[32]	Strauss B H, Ziemlinski R, Weiss J L, et al. 2012. Tidally adjusted estimates of topographic vulnerability to sea level rise and flooding for the contiguous United States. Environment Research Letters, 7(1): 014033. DOI: 10.1088/1748-9326/7/1/014033. DOI URL
[33]	Wessel P, Smith W H F. 1996. A global, self-consistent, hierarchical, high-resolution shoreline database. Journal of Geophysical Research: Solid Earth, 101: 8741-8743.
[34]	Wittemyer G, Elsen P, Bean W T, et al. 2008. Accelerated human population growth at protected area edges. Science, 321(5885): 123-126. DOI PMID