Building height is important information in disaster management and damage assessment. It is also a key parameter in studies such as population modeling and urbanization. Relatively few studies have been conducted on extracting building height in rural areas using imagery from China’s Gaofen-7 satellite (GF-7). In this study, we developed a method combining photogrammetry and deep learning to extract building height using GF-7 data in the rural area of Pingquan in northern China. The deep learning model DELaMa was proposed for digital surface model (DSM) editing based on the Large Mask Inpainting (LaMa) architecture. It not only preserves topographic details but also reasonably predicts the topography inside the building mask. The percentile value of the normalized digital surface model (nDSM) in the building footprint was taken as the building height. The extracted building heights in the study area are highly consistent with the reference building heights measured from the ICESat-2 LiDAR point cloud, with an R² of 0.83, an MAE of 1.81 m and an RMSE of 2.13 m for all validation buildings. Overall, the proposed method in this paper helps to promote the use of satellite data in large-scale building height surveys, especially in rural areas.

Glacial hazards pose significant threats to millions globally, especially with rapid climate warming drawing increased attention. Understanding past glacial hazards on both global and regional scales is crucial for early warning systems. This study quantified glacier and glacial lake changes on the Tibetan Plateau (TP) over recent decades and analyzed the spatial and temporal distribution of major glacial hazards. It also focused on glacial lakes that have experienced outburst events by reconstructing long-term data for 48 lakes. Key findings include: (1) TP glaciers have generally shrunk, with glacier area decreasing from 57,100 km² in the first inventory to 44,400 km² in the second, primarily in the middle and eastern Himalayas between 5000 and 6000 m. Meanwhile, the number of glacial lakes increased from 14,487 in 1990 to 16,385 in 2020, expanding towards higher elevations and glacier melt zones. (2) Since 1900, 283 glacial hazards have occurred, including 97 glacier surges, 36 glacier-related slope failures, and 150 glacial lake outburst floods (GLOFs). Hazard frequency increased post-2000, especially in the Karakoram and eastern Himalayas, during June to September. (3) Changes in glacier numbers contribute most to hazard frequency (11.56%), followed by July’s temperature change (10.24%). Slope and June’s temperature changes combined have the highest interaction effect (37.59%). (4) Of the 48 lakes studied, four disappeared after outbursts, 38 remained stable, and six expanded. These insights aid in monitoring, early warnings, and disaster management.