Is there a relationship between human population distribution and land surface temperature? Global perspective in areas with different climatic classifications

Whether pessimistic believing that overpopulation is the ultimate cause of many environmental problems or optimistic arguing for social justice and technological development, studying human population dynamics and their impacts on the environment is an important and ongoing field of study. This type...

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Veröffentlicht in:Remote sensing applications 2020-11, Vol.20, p.100435, Article 100435
1. Verfasser: Jaber, Salahuddin M.
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Sprache:eng
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Zusammenfassung:Whether pessimistic believing that overpopulation is the ultimate cause of many environmental problems or optimistic arguing for social justice and technological development, studying human population dynamics and their impacts on the environment is an important and ongoing field of study. This type of research should take advantage of the many benefits offered by indirect remote sensing, geographic information systems, and other related disciplines data that are based on relationships developed at the field. Nevertheless, many facets of the subject including the relationship between human population distribution (HPD) and land surface temperature (LST) in areas that have different climatic classifications are still lacking attention. Hence, this study focused on bridging this gap in order to provide supporting scientific evidence for planners and decision makers all over the globe. Four areas that represent the four main populated climate zones were randomly selected. They are: (1) El-Salvador for equatorial climate, (2) Kuwait for arid climate, (3) Lebanon for warm temperate climate, and (4) New Hampshire for boreal climate. For the years 2001, 2009, and 2017 for the four areas, HPD data were obtained from LandScan project while LST data were derived from MOD11C3 product. An integrated framework approach was implemented. This approach included: (1) basic descriptive non-spatial statistics, (2) spatial Global Moran's I Index and Anselin Local Moran's I Index, (3) non-spatial Pearson correlation coefficient (r) and ordinary least squares (OLS) regression, and (4) spatial lag model (SLM) and spatial error model (SEM) regressions. It has been observed that the strength and direction of the relationship between HPD and LST do not vary from time to time but vary from climate zone to another. The strongest relationship can be found in boreal climates, followed by warm temperate climates, and then arid and equatorial climates. In boreal, warm temperate, and equatorial climates the relationship is positive while in arid climates the relationship is negative providing indirect supporting evidence for the inversion of surface urban heat islands phenomenon in arid climates. Furthermore, it has been noticed that the relationship between HPD and LST is highly spatially dependent regardless the time and climate zone where some type of spatial diffusion or spillover processes might be present. Still, it is clear that this relationship is complex and not amenable to dire
ISSN:2352-9385
2352-9385
DOI:10.1016/j.rsase.2020.100435