Soil erosion by water is a major cause of land degradation. Agricultural practices and many other ecological environmental problems contribute to land degradation worldwide, especially in arid and semi-arid areas. Miyun County, which is located in a mountainous region of North China, is an important natural ecological zone and surface source of drinking water for Beijing and is very vulnerable to soil erosion due to its thin soil layer and human activities. Landsat images from 2003 and 2013 were used to analyze the land-use and land-cover change (LULCC) over this period. The revised universal soil loss equation (RUSLE) model integrated with Geographic Information System (GIS) was used to quantify soil loss and to map erosion risk. In addition, the response of soil erosion to LULCC was evaluated. The results showed that the areas under cropland, forest, and water bodies increased over the study period by 66.03, 243.44, and 9.01 km², respectively. The increase in forested land indicated that the improved ground vegetation cover was due to the implementation of active ecological measures. Between 2003 and 2013, light soil erosion increased by 587.46 km², and extremely severe soil erosion increased by 9.57 km². The extents of slight, moderate, severe, and very severe soil erosion, however, decreased by 8.02, 445.21, 142.69, and 1.11 km², respectively. A total of 57.5% of land with moderate soil erosion has been converted to light soil erosion, which could be highly beneficial for the improvement of vegetation control of soil and water losses. In terms of area, forestland exhibited the greatest increase, while moderate soil erosion exhibited the greatest decrease over the study period. Land-use change led to an alteration in the intensity of soil erosion due to changes or loss of vegetation. The conversion from high intensity soil erosion to low intensity was attributed to the implementation of ecological environmental protection. The results generated from this study may be useful for planners and land-use managers to make appropriate decisions for soil conservation.

The largest area of tropical rainforests in China is on Hainan Island, and it is an important part of the world’s tropical rainforests. The structure of the tropical rainforests in Hainan is complex, the biomass density is high, and conducting ground surveys is difficult, costly, and time-consuming. Remote sensing is a good monitoring method for biomass estimation. However, the saturation phenomenon of such data from different satellite sensors results in low forest biomass estimation accuracy in tropical rainforests with high biomass density. Based on environmental information, the biomass of permanent sample plots, and forest age, this study established a tropical rainforest database for Hainan. Forest age and 14 types of environmental information, combined with an enhanced vegetation index (EVI), were introduced to establish a tropical rainforest biomass estimation model for remote sensing that can overcome the saturation phenomenon present when using remote sensing data. The fitting determination coefficient ${\mathrm{R}}^2$ of the model was 0.694. The remote sensing estimate of relative bias was 2.29%, and the relative root mean square error was 35.41%. The tropical rainforest biomass in Hainan Island is mainly distributed in the central mountainous and southern areas. The tropical rainforests in the northern and coastal areas have been severely damaged by tourism and real estate development. Particularly in low-altitude areas, large areas of tropical rainforest have been replaced by economic forests. Furthermore, the tropical rainforest areas in some cities and counties have decreased, affecting the increase in tropical rainforest biomass. On Hainan Island, there were few tropical rainforests in areas with high rainfall. Therefore, afforestation in these areas could maximize the ecological benefits of tropical rainforests. To further strengthen the protection, there is an urgent need to establish a feasible, reliable, and effective tropical rainforest loss assessment system using quantitative scientific methodologies.

Introduction: The plain marsh wetland ecosystems are sensitive to changes in the natural environment and the intensity of human activities. The Sanjiang Plain is China’s largest area of concentrated marsh wetland, the Small Sanjiang Plain is the most important component of the Sanjiang Plain. However, with the acceleration of the urbanization and development of large-scale agricultural reclamation activities in the Small Sanjiang Plain in Northeast China, the wetland has been seriously damaged. In light of this degradation this study examines the Small Sanjiang Plain.Methods: From the four aspects of area, structure, function, and human activities, we try to construct a wetland degradation comprehensive index (WDCI) in cold region with expert scoring methods and analytic hierarchy process (AHP), coupled with network and administrative unit. The objective was to reveal the degradation of wetlands in Northeast China over three decades at a regional scale.Results: The results showed that (1) the overall wetland area decreased between 1990 and 2020 by 39.26×10³ hm². Within this period a significant decrease of 336.56×10³ hm² occurred between 1990 and 200 and a significant increase of 214.62×10³ hm² occurred between 2010 and 2020. (2) In terms of structural changes, the fractal dimension (FRAC) has the same trend as the Landscape Fragmentation Index (LFI) with little change. (3) In terms of functional changes, the average above-ground biomass (AGB) increased from 1029.73 kg/hm² to 1405.38 kg/hm² between 1990 and 2020 in the study area. (4) In terms of human activities, the average human disturbance was 0.52, 0.46, 0.57 and 0.53 in 1990, 2000, 2010 and 2020, with the highest in 2010. (5) The composite wetland degradation index shows that the most severe wetland degradation was 49.61% in 2010 occurred between 1990 and 2020. (6) Among the severely deteriorated trajectory types in 2010–2020, mild degradation → serious degradation accounted for the largest area of 240.23×10³ hm², and the significant improvement trajectory type in 1990–2000 accounted for the largest area of 238.50×10³ hm².Discussion: In brief, we conclude that the degradation of the Small Sanjiang Plain wetland was caused mainly by construction, overgrazing, deforestation, and farmland reclamation. This study can also provide new views for monitoring and managing wetland degradation by remote sensing in cold regions.