The urban clusters in the Middle Reaches of the Yangtze River (MRYR) in China include the Chang-Zhu-Tan urban agglomeration, the Wuhan metropolitan area, and the Poyang Lake urban agglomeration. While previous studies of urban expansion in China focused mainly on the coastal regions, this study aimed to investigate urban expansion patterns and factors in the MRYR, which are crucial for urban development in Central China. A neighborhood statistics analysis (NSA) method and a local-optimized threshold method were used to detect urban changes during 1992–2011 from the time-series Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime light (NTL) images. The evolution of urban expansion intensity and landscape metrics were analyzed at multiple spatial scales, including the whole region, urban agglomeration, and city scales. Finally, the expanded STochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model was built to explore the factors that controlled NTL intensity. The results revealed that urban areas extracted from the NTL data were consistent with those extracted from the Landsat Thematic Mapper data, with an overall accuracy of 81.74% and a Kappa of 0.40. A relatively slow urbanization pace was observed from 1992 to 2002 in the MRYR region, which then accelerated in the period of 2002 to 2007 and then slowed down between 2007 and 2011. Additionally, urban expansion exhibited a radial pattern. The results further indicated that major factors controlling NTL intensity were gross domestic product, followed by total investment in fixed assets, tertiary industry, urban construction area, non-agricultural population, and industrial output in the city clusters. The study provides important insights for further studies on the urbanization processes in the MRYR region.

Groundwater is closely related to hydrogeological structure and hydro-lithology, which mainly refers to the spatial distributions and properties of the environment where groundwater occurs. To analyze the constraints of hydrogeological structure and hydro-lithology on regional groundwater resources in the Eastern Henan Plain, China, we reconstructed the three-dimensional (3D) hierarchical models at two scales, hydrogeological structural models and hydro-lithological models, using hydrogeological cross-sections. First, the hydrogeological structural models of four aquifer groups, corresponding to four formations of the Quaternary in the study area, were reconstructed. Second, the hierarchical hydro-lithological model was built using SIS and IK estimation under the constraint of each aquifer group model space, respectively. Compared to global model, the variograms of hierarchical model captured more spatial characteristics of lithology in each aquifer group. The IK hierarchical model presents more continuities, clear boundaries, and realistic geometric shapes of the three lithologies, excluding the banding characteristics of the IK global model. The hierarchical SIS models reproduced the lithology distribution of each aquifer group and captured small changes in the lithology, with the smallest absolute percentage errors (APEs). Third, coupling the SIS hierarchical models and the groundwater levels, the groundwater resource in the study area was estimated to have a total volume of 1.2339 × 10⁴ m³. The shallow groundwater in the study area is mainly concentrated in Hebi City and the Puyang basin of the Yellow River, and deep groundwater is mainly concentrated in the northern Anyang City and Hebi City. Finally, the possible quantities of shallow and deep groundwater recharges were estimated for future groundwater management decision in the study area. The hierarchical hydrogeological model, groundwater resource assessment, and possible groundwater recharge estimation can also provide a basis for groundwater vulnerability, groundwater extraction, and land subsidence assessment.

The Yangtze River Delta Urban Agglomeration (YRDUA), which is located in the convergence zone of “The Belt and Road Initiative”, is one of the regions with the best urbanization foundations in China. Referring to the four five-year plans (China’s national economic plan), this study aimed to investigate the spatiotemporal patterns of urban expansion in the YRDUA from 2000 to 2020. To conduct a long-term analysis of urbanization, an extended time series (2000–2020) of a nighttime light (NTL) dataset was built from the multi-temporal Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data (2000–2013), and Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data (2014–2020); data from these sources are crucial to understanding the urbanization processes in the region in order for more effective decision making to take place. The support vector machine (SVM) method was used to extract urban clusters from the extended time-series NTL data and MODIS NDVI products. The evolution of the urban expansion intensity was detected at city scales, and the inequality of urban growth was demonstrated using the Lorenz curve and Gini coefficient. Finally, a quantitative relationship between urban NTL intensity and socio-economic data was built to explore the main factors that control urban intensity. The results indicated that the urban extents extracted from time-series NTL data were consistent with those extracted from Landsat data, with an average overall accuracy (OA) of 89%. A relatively fast urbanization pace was observed during the 10th five-year plan (from 2000 to 2005), which then declined slightly in the 11th five-year plan (from 2006 to 2010). By the 12th and 13th five-year plan (from 2011 to 2020), urban clusters in all cities tended to grow steadily. Urban expansion has presented a radial pattern around the main cities, with sprawl inequality across cities. The results further revealed that the primary factors controlling NTL brightness were gross domestic product (GDP), total fixed asset investment, tertiary industry, gross industrial output, urban area, and urban permanent residents in city clusters, but the same driving factors had a different contribution order on the NTL intensity across cities. This study provides significant insight for further urbanization study to be conducted in the YRDUA region, which is crucial for sustainable urban development in the region.

Urban area hotspots are considered to be an ideal proxy for spatial heterogeneity of human activity, which is vulnerable to urban expansion. Nighttime light (NTL) images have been extensively employed in monitoring current urbanization dynamics. However, the existing studies related to NTL images mainly concern detection of urban areas, leaving inner spatial differences in urban NTL luminosity poorly explored. In this study, we propose an innovative approach to explore the spatiotemporal trajectory of urban area hotspots using monthly Visible Infrared Imaging Radiometer Suite (VIIRS) NTL images. Firstly, multi-temporal VIIRS NTL intensity was decomposed by time-series analysis to obtain annual stable components after data preprocessing. Secondly, the support vector machine (SVM) regression model was utilized to identify urban area hotspots. In order to ensure the model accuracy, the grid search and cross-validation method was integrated to achieve the optimized model parameters. Finally, we analyzed the spatiotemporal migration trajectory of urban area hotspots by the center of gravity method (i.e., shift distance and angle of urban area hotspot centroid). The results indicate that our method successfully captured urban area hotspots with a regression coefficient over 0.8. Meanwhile, the findings give an intuitive understanding of coupling interaction between urban area hotspots and socioeconomic indicators. This study provides important insights for further decision-making regarding sustainable urban planning.