Characterizing the relationship between land use land cover change and land surface temperature

Abstract

Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi* statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi* statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

Application of Remote Sensing Techniques and Geographic Information Systems to Analyze Land Surface Temperature in Response to Land Use/Land Cover Change in Greater Cairo Region, Egypt

“…Confusion matrices were computed to evaluate the relationship between the reference data used and the resulting classified LULC maps. Confusion matrices are one of the most popular ways to evaluate the overall classification accuracy providing information about producer's accuracy or errors of omission (percentage of a specific LULC class on the ground which is correctly classified) and user's accuracy or error of commission (percentage of a certain pixel class on the produced map corresponding to the actual class on the ground) [13] [51].…”

“…Nevertheless, an increase in land surface temperatures (LST) is one of the key effects of LULC changes [6]- [11]. Increases in LST over the past several decades are considered a major issue in urban regions, due to the conversion of vegetation cover to impervious cover [12], which in turn has a negative impact on people [13], affects many environmental processes and modifies the degree of solar radiation's absorption, evaporation rates, desertification, air pollution, albedo, heat storage, wind turbulence and many aspects of the water balance [14]. Therefore, the impact on environmental processes cannot be well-understood and mitigated without understanding the impacts of climate change, the interaction between the earth and the atmosphere and knowledge of land use/land cover change at various scales that drive them [2].…”

Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy

“…Different scholars in different time periods attempted to draw a correlation between LST in UHIs and some land use/land cover (LU-LC) indices for different study area (Chen et al, 2006;Deilami & Kamruzzaman, 2017;Estoque, Murayama, & Myint, 2017;Ma, Wu, & He, 2016;Mathew, Sreekumar, Khandelwal, Kaul, & Kumar, 2016;Mushore, Mutanga, Odindi, & Dube, 2016;Nie, Man, Li, & Huang, 2016;Tran. et al, 2017;Weng & Yang, 2004).…”

Spatiotemporal Variations in the Impacts of Urban Land Use Types on Urban Heat Island Effects: The Case of Riyadh, Saudi Arabia

“…Though the need for more studies on the estimation of UHI parameters had been emphasized by Weng (2003), the studies on the relationship between LST and urban land use/land cover still prevail. Time series and statistical analysis and modelling (Fu and Weng, 2016;Li et al, 2017;Tran et al, 2017) have been used to better understand the influence of the characteristics of urban surfaces on UHI.…”