The occurrence and spread of forest fires are the result of the interaction of many factors. In cross-border areas, different fire management systems may lead to different forest fire driving factors. A comparative analysis of the forest fire driving factors in different countries can help to provide ideas for fire prevention and control. In this study, based on the logistic regression (LR) model and standardized coefficients, we determined the relative impact of forest fire driving factors in different countries, in the cross-border area between China, North Korea and Russia from 2001 to 2020, and established a forest fire probability and fire risk level division using a Kriging interpolation. The results show that the climate is the most important factor affecting the probability of forest fires in the cross-border area, followed by the topography and vegetation factors; human activities have the least influence. From a country-by-country perspective, the forest fires on the Chinese side were more affected by humans than on the North Korean and Russian sides and they were mainly concentrated in areas with a low altitude and high population density. The forest fires on the North Korean side and the Russian side were more affected by nature than on the Chinese side and were mainly concentrated in areas with a low altitude, high temperature and little rainfall. The high-risk areas for forest fires were mostly concentrated near the border between China, North Korea and Russia, where transboundary fires pose a great threat to forest resources and rare animals. This study shows that there is a significant difference between the impact of different forest fire management systems on fire conditions, and that active forest fire control policies can effectively reduce the damage caused by forest fires. Due to the complexity of the geopolitics in cross-border areas, transboundary firefighting faces certain difficulties. In the future, it will be necessary to strengthen the cooperation between countries and establish transboundary joint defenses against forest fires in order to protect the declining forest resources and the habitats of rare animals.

The continuous deterioration of terrestrial ecosystems has led to the destruction of many biological habitats in recent years. The Tumen River cross-border basin, an important biological habitat, is also affected by this changing situation. Assessing habitat quality (HQ) is crucial for restoring and protecting habitats, and vegetation plays a significant role in this process. In this study, we used geographical detector (GD) to extract fraction vegetation coverage (FVC) features and quantify the contribution of driving factors. By coupling vegetation cover and land use data, we assessed HQ. Our findings reveal a declining trend in FVC from 2000 to 2020, which mainly assumed a spatial pattern inclined from northeast and southwest to southeast. Human activities and natural factors interacted to cause these changes in FVC, with human activities having a more significant impact. Vegetation and land use changes led to a decline in the basin’s HQ index. This study highlights the crucial role of FVC in HQ and provides a relevant scientific reference for optimizing the evaluation of HQ in the Tumen River cross-border basin and promoting the sustainable development of regional ecology.

Understanding the dynamics of water bodies is crucial for managing water resources and protecting ecosystems, especially in regions prone to climatic extremes. The Tumen River Basin, a transboundary area in Northeast Asia, has seen significant water body changes influenced by natural and anthropogenic factors. Using Landsat 8 and Sentinel-1 data on Google Earth Engine, we systematically analyzed the spatiotemporal variations and drivers of water body changes in this basin from 2015 to 2023. The water body extraction process demonstrated high accuracy, with overall precision rates of 95.75% for Landsat 8 and 98.25% for Sentinel-1. Despite observed annual fluctuations, the overall water area exhibited an increasing trend, notably peaking in 2016 due to an extraordinary flood event. Emerging Hot Spot Analysis revealed upstream areas as declining cold spots and downstream regions as increasing hot spots, with artificial water bodies showing a growth trend. Utilizing Random Forest Regression, key factors such as precipitation, potential evaporation, population density, bare land, and wetlands were identified, accounting for approximately 81.9–85.3% of the observed variations in the water body area. During the anomalous flood period from June to September 2016, the Geographically Weighted Regression (GWR) model underscored the predominant influence of precipitation, potential evaporation, and population density at the sub-basin scale. These findings provide critical insights for strategic water resource management and environmental conservation in the Tumen River Basin.

Drought, as an extreme climatic event, is considered one of the most severe natural disasters worldwide. In Northeast Asia, the frequency and intensity of drought have been exacerbated by climate change, causing significant negative impacts on the region’s socioeconomic conditions and agricultural production. This study analyzed the spatiotemporal evolution and trends in drought in transboundary river basins in Northeast Asia from 1990 to 2020, using meteorological station data and remote sensing data. The Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Condition Index (VCI) were employed to assess drought characteristics, and a comprehensive analysis of the SPEI and VCI indices was conducted to evaluate drought severity under different land cover types. The results indicate that (1) in the past two decades, both the SPEI and VCI indices have shown an increasing trend in the basin, with moderate and mild droughts being predominant. (2) High and extreme droughts mainly occur in forest areas, accounting for 17.91% and 10.76%, respectively, followed by farmland.

Transboundary river basins combine spatially continuous ecological processes with nationally differentiated land use, development intensity, and environmental governance, yet it remains unclear how these asymmetries shape landscape ecological risk (LER) and whether alternative near-term land-use pathways can substantially modify the shared risk pattern. Taking the Sino–DPRK transboundary area of the Tumen River Basin as a case study, we assessed land-use and LER changes in 2000, 2010, and 2020 using a landscape-pattern-based LER index, global and local spatial autocorrelation, the geodetector, and geographically weighted regression (GWR), and simulated 2030 land use and LER under natural development (NDS), cropland protection scenario (CPS), and ecological conservation (EPS) scenarios using the Patch-generating Land Use Simulation (PLUS) model. Basin-wide mean LER increased from 0.0604 in 2000 to 0.0662 in 2010 and to 0.0666 in 2020, with most of the increase occurring during 2000–2010. In 2020, mean LER was higher on the DPRK side than on the Chinese side (0.0701 vs. 0.0646), and the combined proportion of relatively high- and high-risk units reached 40.22% and 27.03%, respectively. LER showed persistent positive spatial autocorrelation, with Moran’s I values of 0.6393, 0.6237, and 0.6347, and 55, 38, and 44 cross-border H-H adjacent pairs identified in the three periods. Slope consistently showed the highest explanatory power (q = 0.799–0.921), while the explanatory power of normalized difference vegetation index (NDVI) increased from 0.097 to 0.318; distance to roads was the strongest socioeconomic proxy (q = 0.131–0.202). GWR further indicated significant spatial non-stationarity in several major environmental relationships. For 2030, mean LER changed by +0.69%, −0.13%, and +0.60% under the NDS, CPS, and EPS, respectively, indicating only limited near-term divergence among scenarios. These results reveal persistent cross-border asymmetry together with recurrent H-H adjacency in boundary valley sections and suggest that near-term land-use adjustment alone may have limited capacity to substantially restructure basin-wide LER. The findings provide a spatial basis for prioritizing cross-border monitoring and coordinated land-use management in recurrent high-risk boundary valley segments.