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Forest fires are one of the most severe natural disasters facing global ecosystems, as they have a significant impact on ecological security and social development. As remote sensing technology has developed, burned areas can now be quickly extracted to support fire monitoring and post-disaster recovery. This study focused on monitoring forest fires that occurred in Chongqing, China, in August 2022. The burned area was identified using various satellite images, including Sentinel-2, Landsat8, Environmental Mitigation II A (HJ2A), and Gaofen-6 (GF-6). The burned area was extracted using visual interpretation, differenced Normalized Difference Vegetation Index (dNDVI), and differenced Normalized Burnup Ratio (dNBR). The results showed that: (1) The results of the three monitoring methods were very consistent, with a coefficient of determination R2 > 0.96. (2) A threshold method based on the dNBR-extracted burned area was used to analyze fire severity, with moderate-severity fires making up the majority (58.05%) of the fires. (3) Different topographic factors had some influence on the severity of the forest fires. High elevation, steep slopes and the northwestern aspect had the largest percentage of burned area. [ABSTRACT FROM AUTHOR]

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing's population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased. [ABSTRACT FROM AUTHOR]

[Display omitted] • Human activities played a dominant role in the vegetation restoration. • Population emigration made the greatest contribution to vegetation change (62.47%). • The effect of population migration on vegetation varied with elevation. • The Grain-for-Green program had a positive effect on vegetation. With the continuous increase in urbanization and non-farm wages, many rural labor forces have transferred to urban areas, significantly changing the population distribution and affecting vegetation restoration and ecological environment improvement. This study analyzed the spatiotemporal patterns of vegetation in Chongqing from 2000 to 2018 based on the MODIS EVI dataset, and 862 samples were randomly selected to quantitatively analyze the contribution degree of population emigration to vegetation greenness by using the multivariate linear regression model under the conditions of controlling climate, topography, and policy factors. The results showed that the vegetation in Chongqing presented a significant improvement trend. Human activities played a dominant role in the vegetation restoration in Chongqing from 2000 to 2018. The contribution of population spatial redistribution to vegetation changes was 62.47%, and the contributions gradually decreased with increasing elevation, which were 73.90%, 45.02%, and 17.87% in the low, medium, and high altitude areas, respectively. Furthermore, the Grain-for-Green program significantly affected vegetation variation, and the project had the greatest ecological benefits in medium-altitude areas. [ABSTRACT FROM AUTHOR]