The Yellow River Delta (YRD), known for its vast and diverse wetland ecosystem, is the largest estuarine delta in China. However, human activities and climate change have significantly degraded the wetland ecosystem in recent decades in the YRD. Therefore, an understanding of the land use modifications is essential for the efficient management and preservation of ecosystems in this region. This study utilized time series of remote sensing data and the extreme gradient boosting method to generate land use maps of the YRD from 2000 to 2020. Several methods, including transition matrix, land use dynamic degree, and standard deviation ellipse, were employed to explore the characteristics of land use transitions. The results underscore significant spatial variations in land use over the past two decades. The most rapid increase was observed in built-up area, followed by terrestrial water and tidal flats, while unutilized land experienced the fastest decrease, followed by forest–grassland. The spatial distribution patterns of agricultural land, built-up area, terrestrial water, and forest–grassland demonstrated stronger directionality compared to other land use types. The wetlands have expanded in size and improved in structure. Unutilized land has been converted into artificial wetlands comprising ponds, reservoirs, salt ponds, shrimp and crab ponds, and natural wetlands featuring mudflats and forest–grassland. The wetland conservation efforts after 2008 have proven very effective, playing a positive role in ecological and environmental preservation, as well as in regional sustainable development.

Extreme heat events, or heatwaves, exert significant impacts on human society, ecosystems, and the economy. The continuous development of remote sensing technology has facilitated the acquisition of high-quality data for assessing health risks associated with these extreme heat events. This study systematically reviews the evaluation factors and assessment framework for a spatially explicit assessment of heat-related health risks. The contribution of geospatial big data, with a particular focus on satellite observations, to these assessments was investigated. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat surface temperature (LST) are identified as the two most widely utilized data sources for mapping heat hazards. The incorporation of multi-sensor observations, along with the implementation of spatiotemporal fusion and downscaling techniques, enhances both the spatial resolution and temporal frequency of heat hazard characterization. It is essential to consider issues of justice and equality in heat-resilient planning and mitigation practices. Integrating heatwave risk assessment results with analyses of urban morphology, land use functions and infrastructure can provide critical information for government agencies to strategically plan urban layout, functions, and public service facilities while optimizing and enhancing urban green infrastructures.