Global regional conflicts are on the rise, threatening both local and global stability and development. This paper used monthly and daily nighttime light (NTL) imagery from December 2021 to April 2022 to analyze NTL dynamics during the initial period of the Russia-Ukraine conflict at the national and sub-national (oblast and city) levels. In addition, a novel method was proposed to quantify the direct impact of the conflict at the pixel level. In this study, a new Conflict Effect Index (CEI) was constructed to distinguish Conflict-Damaged Area (CDA) and Conflict-Recovered Area (CRA) and to quantify the direct damage and subsequent recovery caused by the conflict. The results indicate that the outbreak of the conflict led to a significant decrease in NTL intensity of about 56% across Ukraine. The pixel-level CEI indicated that the onset of the conflict had a broad impact across Ukraine, with the affected area shrinking as the conflict progressed. Damaged areas accounted for 12% of Ukraine at the start of the conflict, but decreased at an average rate of 2963.25 km ² /day over the following week, while the size of recovered areas peaked at 9258.75 km ² during the conflict, but decreased to a low of 3750 km ² . The maximum rate of change in the area of the CDA and CRA was -67% and 135% respectively. The study demonstrates that NTL data can capture the direct destruction of conflict and help to support humanitarian relief and post-disaster reconstruction efforts.

Multi-sensor image matching is a key technology to fully exploit complementary information on images from multiple sources. In particular, the nonlinear radiance distortion between optical and SAR images makes image matching very difficult. Focusing on satellite optical and SAR image matching, this paper proposed an oriented edge-based template image matching, namely Multiple Orientation Edge Feature Correlation (MOEFC). Firstly, the edge feature was extracted by the Sobel operator to construct oriented gradient channels on optical and SAR images. Then spatial filtering was performed separately by a two-dimensional and a one-dimensional kernel. Finally, the similarity was determined by stacking the normalized cross correlation (NCC) of each oriented gradient channel. To validate the new method, it was compared with other four edge-based template image matching methods detected by Sobel, Canny, Laplacian and phase congruency-based methods on satellite optical-SAR image pairs, which were tested in rural and urban areas. And the results show that the proposed MOEFC method can obtain the largest number of correct matching (NCM) with the least root mean square error (RMSE) in both areas. In the rural area, the NCM of the MOEFC method is higher than the other four methods, and the improvement ranges from 54.1% to 74.3%. And the RMSE of the MOEFC method is 0.645 pixel. In the urban area, the NCM of the MOEFC method can also be improved by 3.6% to 46.4%. And the RMSE of the MOEFC method equals 0.489 pixel.

Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.

Economic development is a cornerstone of national development, and sustainable economic development is a key focus for achieving broader sustainable development goals. Existing economic studies based on nighttime light remote sensing often center on gross domestic product (GDP) as the primary parameter. This study introduces a comprehensive framework based on the economics’ “growth, poverty, and inequality” (GPI) trilemma to generate the first long-term, high-resolution maps of China’s economic sustainability. Then, the spatiotemporal evolution pattern of China’s economic sustainability was deeply explored at multiple scales. The results reveal that China has made substantial strides in economic sustainability since 2001, with over 317 million people transitioning out of low-sustainability areas. However, marked spatial variations existed across China. The eastern regions have experienced the largest increase, while the central regions showed the highest growth potential. The western regions have been steadily developing, whereas the northeast faces challenges with negative growth in some areas. Uneven population distribution across various sustainability levels was found. The highest population density is concentrated in medium–high sustainability level, with more than 41.7% population inhabiting only 4.1% of the country’s area in 2021. While unbalanced development persisted, there are signs of alleviation, as evidenced by stronger linkage between provinces and less directional expansion within each regional zone. The generated long-term, high-resolution economic sustainability maps and multiscaled spatiotemporal analysis provide valuable insights into the realization of China’s economic development and sustainability goals. These findings can assist the government in making decisions on economic policies.