Habitat quality is a key factor in regional ecological restoration and green development. However, limited information is available to broadly understand the role of natural and human factors in influencing habitat quality and the extent of their impact. Based on remote sensing monitoring data of land use over five time points (2000, 2005, 2010, 2015, and 2020), natural factors, and socioeconomic data, we applied the InVEST model to assess habitat quality in Guangdong Province. Using a multiscale geographically weighted regression (MGWR) model, we explored the spatial scale differences in the role of natural and human factors affecting habitat quality and the degree of their influence. The highlights of the results are as follows: ① From 2000 to 2020, land-use changes in the Pearl River Delta (PRD) region were particularly obvious, with the dynamic degree of construction land being higher than that of other land-use types. Construction land has gradually occupied agricultural and ecological land, causing damage to habitats. ② The overall habitat quality in Guangdong Province is decreasing; the areas with low habitat quality values are concentrated in the PRD region and the coastal areas of Chaoshan, Maoming, and Zhanjiang, while the areas with higher habitat quality values are mainly located in the non-coastal areas in the east and west of Guangdong and the north of Guangdong. ③ The MGWR regression results showed that the normalized vegetation index had the strongest effect on habitat quality, followed by road density, gross domestic product (GDP) per unit area, slope, and average elevation, and the weakest effect on average annual precipitation. ④ The effects of average elevation, GDP per unit area, and normalized vegetation index on habitat quality were significantly positively correlated, while road density was significantly negatively correlated. These results provide a scientific basis for adjusting spatial land-use planning and maintaining regional ecological security.
Beijing–Tianjin–Hebei, the main economic area in northern China, has seen significant changes in its regional economic and physical landscape as a result of the coordinated development strategy. Assessing the link between land use and land cover (LULC) change and carbon emissions in the Chaobai River region, which represents the growth of the Beijing–Tianjin–Hebei urban agglomeration, is crucial to achieve coordinated low-carbon development in this area. This study uses statistics from statistical yearbooks of Chinese provinces and cities along with land use change data to analyze the relationship between land use changes and carbon emissions in the Chaobai River region from 2001 to 2017 using dynamic land use attitudes and land use transfer matrices, combined with carbon emission factors based on the IPCC inventory method and carbon emission models for energy consumption. In addition, this study makes use of the LMDI model and geographical detectors to identify and assess the factors that influence changes in land use carbon emissions and the driving forces behind the regional differentiation of land use changes. The results show that: (1) The Chaobai River region’s predominant land use classes during the past 18 years have been agricultural land and construction land. In addition to the decrease in cropland and the increase in urban land, the land use patterns of other land classes also changed to a certain extent. (2) Carbon emissions from land use showed an increasing trend, from 6.1 × 106 tons in 2001 to 1.1 × 107 tons in 2017. (3) Carbon emission intensity, economic development level, land use efficiency, and construction land scale have a certain regularity in the evolution of carbon emissions, and economic development level has become the most important driving factor controlling the growth of land use carbon emissions. (4) Driving factors in different periods have different degrees of influence on land use change, among which socio-economic factors such as population density and GDP have the strongest explanatory power. In addition, the interactions of each factor mainly present a double factor enhancement. In the future, the Chaobai River region should be based on the coordinated development strategy and take the “double carbon” target as its guiding principle to promote the innovation of the regional development system and further achieve the optimization of the regional land use patterns.
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