Surface temperature variations and their relationships with land cover in the Pearl River Delta

Surface urban heat island and its relationship with land cover change in five urban agglomerations in China based on GEE

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban-rural dichotomy, analyzes their trends through the Sen + M-K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land.

The relationship between land use land cover and land surface temperature using remote sensing: systematic reviews of studies globally over the past 5 years

The land surface temperature (LST) has been increased worldwide from time to time with the rapid increase of impervious surfaces such as built-up areas, parking lots, and asphalt and concrete roads. Several studies have examined the impacts of spatial dynamics of land use land cover (LULC) on the spatial variability of LST. However, there have not been systematic reviews conducted about the relationship between LULC and LST. Therefore, this study was conducted to investigate the relationship between LULC and LST with the main objective of synthesizing the relationship between LULC and LST using remote sensing data. An extensive literature search was conducted from the most familiar electronic databases such as Science Direct, Scopus, Web of Science, and Google Scholar between 27/08/2021 and 28/08/2021. The studies that are focussed on the relationship between LULC and LST and/or the impacts of LULC change on the LST using remote sensing were included for the analysis. Besides, papers conducted over the last 5 years (January/2016 to August/2021) were selected in this systematic study since this study focused on the most recent studies. In this systematic review, 100 studies were included for the study analysis. Based on the analysis of this study, built-up land has the first highest LST from the thirteen LULC types. Besides, bare land has a higher LST next to built-up land. On the other side, snow cover has the lowest LST among the LULC types. Lastly, waterbodies have a lower LST compared to vegetation cover.

Macro analysis of spatiotemporal variations in ecosystems from 1996 to 2016 in Xishuangbanna in Southwest China

This study used remote sensing images from 1996 to 2016 as the main data source, and selected the average annual ecosystem type net change rate, ecosystem type transfer matrix, and comprehensive index of land development degree, to analyze the macro change of the ecosystem pattern in Xishuangbanna Dai Autonomous Prefecture in the past 20 years. Quantitative analysis was performed on amplitude, rate, type of transition, and degree of disturbance of human activities. The results reveal the spatial and temporal changes of the Xishuangbanna ecosystem and their regional differentiation. The results showed that (1) from 1996 to 2016, Xishuangbanna as a whole was dominated by forest ecosystems and rubber ecosystems, followed by tea, farmland, built-up area, and water ecosystems. (2) During 1996-2016, the ecosystem in Xishuangbanna accounted for more than 99% of the total area has not changed. From 1996 to 2003, the transfer of ecosystem types in Xishuangbanna was mainly between forest and rubber ecosystem. (3) The extent of land development and utilization in Xishuangbanna in the past 20 years is relatively low, slightly lower than the national average, and the overall level of land use is at a medium level of utilization, and over time, the degree of disturbance of human activities has shown an increasing trend.

Driving Factors of Land Surface Temperature in Urban Agglomerations: A Case Study in the Pearl River Delta, China

Land surface temperature (LST) in urban agglomerations plays an important role for policymakers in urban planning. The Pearl River Delta (PRD) is one of the regions with the highest urban densities in the world. This study aims to explore the spatial patterns and the dominant drivers of LST in the PRD. MODIS LST (MYD11A2) data from 2005 and 2015 were used in this study. First, spatial analysis methods were applied in order to determine the spatial patterns of LST and to identity the hotspot areas (HSAs). Second, the hotspot ratio index (HRI), as a metric of thermal heterogeneity, was developed in order to identify the features of thermal environment across the nine cities in the PRD. Finally, the geo-detector (GD) metric was employed to explore the dominant drivers of LST, which included elevation, land use/land cover (LUCC), the normalized difference vegetation index (NDVI), impervious surface distribution density (ISDD), gross domestic product (GDP), population density (POP), and nighttime light index (NLI). The GD metric has the advantages of detecting the dominant drivers without assuming linear relationships and measuring the combined effects of the drivers. The results of Moran’s Index showed that the daytime and nighttime LST were close to the cluster pattern. Therefore, this process led to the identification of HSAs. The HSAs were concentrated in the central PRD and were distributed around the Pearl River estuary. The results of the HRI indicated that the spatial distribution of the HSAs was highly heterogeneous among the cities for both daytime and nighttime. The highest HRI values were recorded in the cities of Dongguan and Shenzhen during the daytime. The HRI values in the cities of Zhaoqing, Jiangmen, and Huizhou were relatively lower in both daytime and nighttime. The dominant drivers of LST varied from city to city. The influence of land cover and socio-economic factors on daytime LST was higher in the highly urbanized cities than in the cities with low urbanization rates. For the cities of Zhaoqing, Huizhou, and Jiangmen, elevation was the dominant driver of daytime LST during the study period, and for the other cities in the PRD, the main driver changed from land cover in 2005 to NLI in 2015. This study is expected to provide useful guidance for planning of the thermal environment in urban agglomerations.