Lake Dianchi is one of the most eutrophic lakes in China. The decline in water quality and the occurrence of massive algal blooms pose a significant threat to the health and environmental safety of the water ecosystem, making Lake Dianchi a key concern for algal bloom management in China. Obtaining the spatiotemporal dynamics of algal blooms for the longest time possible is crucial to algal bloom management and future prediction. However, it is difficult to acquire a long-term record of algal blooms from a single sensor in order to cover a more extended period of eutrophication in the lake due to the limitation of the spatial and temporal resolution of the sensors. In this study, Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) images were combined with the Floating Algae Index (FAI) to reconstruct a unified time series of bloom areas to analyze the algal bloom dynamics in Lake Dianchi in recent decades. Regarding the interannual variation, the bloom area showed an increasing trend from 1987 to 2021, with larger bloom areas in 1991–1992, 2000–2003, 2012–2013, and 2020–2021. In terms of seasonal characteristics, the bloom area was significantly more prominent in the rainy season compared with the dry season during the year. The spatial distribution of the bloom frequency showed a pattern of higher frequencies in the north and lower frequencies in the south. From 2000 to 2021, the initial bloom time and bloom duration showed a trend of delaying and then advancing and decreasing and then increasing, respectively. We analyzed the importance of long-term records of algal blooms and found that the percentage of rainy season images is an essential factor in reconstructing time series based on different sensors. In addition, the relationship between environmental factors and algal blooms was analyzed. The results show that wind speed and air temperature were the main meteorological factors controlling the interannual variation in algal blooms in Lake Dianchi. Water quality factors such as nutrients have less of an influence on the variation in algal blooms because the algal growth demand has been met. Environmental management measures taken by local governments have led to improvements in the lake’s trophic state, and continued strengthening of environmental pollution control is expected to curb the algal blooms in Lake Dianchi. This study provides a long-term record of algal blooms in Lake Dianchi, which provides essential reference information for a comprehensive understanding of the development process of algal blooms in Lake Dianchi and its sustainable development.

Rapid urbanization has fostered the proliferation of urban villages (UVs), high-density informal settlements that pose unique challenges for environmental management. Despite their prevalence, the dynamics of pollutant accumulation in these transitional neighborhoods remain underexplored. This study investigated nitrogen and phosphorus accumulation in road-deposited sediment (RDS) within Shenzhen, a representative megacity in southern China, utilizing field sampling and statistical analysis to identify dominant drivers. The results indicate that UVs function as significant pollution hotspots, with RDS accumulation rates approximately 3.7 times higher than in formal built-up areas. Analysis revealed that pollution intensity is primarily driven by natural factors such as slope, whereas pollution load is controlled by anthropogenic supply factors. This creates a critical input–output imbalance where high pollutant inputs exceed the natural removal capacity. Consequently, effective mitigation of urban non-point source pollution requires shifting from traditional engineering solutions to spatially sensitive planning strategies, offering practical guidance for enhancing urban sustainability in rapidly urbanizing regions.

Remote sensing is a powerful tool for monitoring ecological changes in lake reservoirs. This paper uses Landsat-OLI and Sentinel-MSI images to obtain algal dynamics information in a reservoir, which has reference value and some details need to be im...