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.

In recent years, the rent-free farmland transfer has become increasingly prominent in rural China. By employing multiple data sources, this study estimates the extent of rent-free land transfer from 1986 to 2015 and develops a multilevel logit model to identify its drivers. The results show that the extent of rent-free land transfer has been increasing, especially since 2002, and 30% to 50% of the land that has been transferred does not receive any rent, both in terms of the number of land parcels and the land area. There are obvious regional differences for the rent-free phenomenon in the process of land transfer, especially in mountainous areas, where the proportion is more than 70%. The cost-benefit analysis at the land parcel level shows that the average net income of rent-free land per mu that has been transferred (1 mu = 1/15 ha) is at a loss of 66 yuan, at 35 yuan. The rent-free land transfer is affected by factors at the levels of the land parcel, farmer and village. The land parcel size, quality level and irrigation condition are the key factors at the land parcel level; the ratio of the non-agricultural income in the family and land fragmentation are the key factors at the farmer level, and the inter-village gap is the key factor at the village level. The land parcel features account for approximately 40% of the variation in the rent-free land transfer. In sum, the increase in the labour cost is the direct reason for the rent-free land transfer, and land parcel features and the marginalization of mountainous areas are the preconditions for the rent-free land transfer. A rent-free land transfer is reasonable to some extent, but it is not an informal land transfer, and land rent does not play an effective role in allocating land resources. In this process, the idle or abandoned land resources in mountainous areas become relatively rich. The government should reasonably introduce urban capital and fully tap relatively rich land resources to realize the land capital appreciation and develop the local economy, and it should further regulate the land rental market and lay an emphasis on the integration of land resources, while moderating scale operations in mountainous areas.

Land urbanization (LU) and population urbanization (PU) maintain the nature of spatiotemporal heterogeneity in China. As a municipality directly administered by the central government in the mode of “large cities and large rural areas”, Chongqing’s urbanization process is the epitome of China’s urbanization process. This paper examines the spatiotemporal variability of LU and PU in Chongqing on the basis of nighttime light data, the elasticity coefficient of the coupling relationship, and GWR. The results show that (1) the urban land and urban population in Chongqing grew notably from 2008 to 2018, with average annual growth rates of 9.4% and 2.3%, respectively. (2) The coupling coordination coefficient of LU and PU in Chongqing was 0.24, and the total number of districts and counties with uncoordinated development increased, but the overall uncoordinated situation gradually improved over the period. (3) The influence of PU on LU in each district and county increased year by year, and it showed a decreasing trend from southwest to northeast in Chongqing, which indicates that LU was increasingly adapted to the construction needs of PU. The gap between LU and PU widened due to the household registration system, land fiscal policies and other policies. After the reform of the household registration system and the adjustment of new pilot policies targeting the construction of new-type urbanization, the coupling relationship between LU and PU was gradually improving to the coordinated mode. The findings indicate that Chinese urban areas should adhere to the principle of new-type urbanization construction and carry out scientific land planning strategies, strictly controlling land expansion to promote the reasonable development of population growth.

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.

Currently, whether the urban development in China satisfies Zipf’s law across different scales is still unclear. Thus, this study attempted to explore whether China’s urban development satisfies Zipf’s law across different scales from the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data. First, the NPP-VIIRS data were corrected. Then, based on the Zipf law model, the corrected NPP-VIIRS data were used to evaluate China’s urban development at multiple scales. The results showed that the corrected NPP-VIIRS data could effectively reflect the state of urban development in China. Additionally, the Zipf index (q) values, which could express the degree of urban development, decreased from 2012 to 2018 overall in all provinces, prefectures, and counties. Since the value of q was relatively close to 1 with an R² value > 0.70, the development of the provinces and prefectures was close to the ideal Zipf’s law state. In all counties, q > 1 with an R² value > 0.70, which showed that the primate county had a relatively stronger monopoly capacity. When the value of q < 1 with a continuous declination in the top 2000 counties, the top 250 prefectures, and the top 20 provinces in equilibrium, there was little difference in the scale of development at the multiscale level with an R² > 0.90. The results enriched our understanding of urban development in terms of Zipf’s law and had valuable implications for relevant decision-makers and stakeholders.