Forestry work involves scientific management and the effective utilization of forest land resources, and finding economical, efficient and accurate acquisition methods for forest land resource information. In previous land-use classification research, machine learning algorithms have achieved good results, and Sentinel public data have been used in various remote sensing applications. However, there is a paucity of research using these data to evaluate the performance of machine learning algorithms in the extracting of complex forest land resource information.

Deforestation and forest degradation mostly caused by human interventions affect the capacity of the forest ecosystem to provide ecosystem services and livelihood benefits. Forest and landscape restoration (FLR) is an emerging concept that focuses on the improvement of the ecosystem as well as the livelihood of the people at the landscape level. Nepal has successfully recovered degraded forest land mainly from the hilly region through forest restoration initiatives, especially community-based forestry. However, the Tarai region is still experiencing deforestation and forest degradation.

The water quality of a basin is pronouncedly affected by the surrounding types of land use. Analyzing the impact of LULC and landscape patterns on water quality is critical for identifying potential drivers. To further study how LUCC affects the water quality in a typical plateau lake basin, this study investigated the impacts of land-use types on water quality in the Dianchi Lake Basin in Southwest China.

Understanding the complex human and natural processes that occur in watersheds and stream ecosystems is critical for decision makers and planners to ensure healthy stream ecosystems. This study aims to characterize the Han River watershed in Korea and extract key relationships among watershed attributes and biological indicators of streams using principal component analysis (PCA) and self-organizing maps (SOM). This study integrated watershed attributes and biological indicators of streams to delineate the watershed and stream biological status.

Habitat quality and ecosystem service value (ESV) are important foundations for sustainable development. Baoding, as the strategic hinterland of Beijing–Tianjin–Hebei, is of great significance to regional ecological conservation and sustainable urban development. Based on land-use data from 2000 to 2020, the land-use scenarios of natural development (ND), water protection (WP), forest rehabilitation (FR), and cultivated land protection (CP) in 2030 were predicted by the PLUS model and adopt the InVEST model and equivalent ESV table to assess ecological sustainability.

Modeling land use and land cover (LULC) change is important for understanding its spatiotemporal trends and plays a crucial role in land use planning and natural resources management. To this end, this study assessed the spatiotemporal characteristics of the LULC changes in Urumqi city between 1980 and 2020. In addition, future LULC was successfully projected for 2030 and 2050 under different scenarios based on the FLUS model. This model was validated using actual and simulated land use data for 2020.

Land degradation, especially natural forest land degradation (NFLD), is a severe environmental concern in China. This natural disaster itself and its derivative control policies have caused some impacts on surrounding farmers’ livelihood level and strategies, but the literature on the sustainable livelihood of different households in NFLD vulnerability is limited, and there is an urgent need to bridge the gap and conduct studies on the sustainable livelihood of Changting, Libo, Lixian, Menghai and Wuxi, the typical NFLD-prone areas in China.

Affected by the small scale of forest farmers’ land and the imperfect development of the forest land transfer market, China’s forest rights mortgage loans have suffered from more serious credit rationing. The application of financial linkage theoretically has the effect of solving credit rationing. However, previous studies on financial linkages have focused on the field of credit lending, whereas the applied studies in the field of mortgage lending are mainly case studies on transaction models, and empirical tests on the application of financial linkages in mortgage lending are lacking.

Habitat degradation and species range contraction due to land use/land cover changes (LULCC) is a major threat to global biodiversity. The ever-growing human population has trespassed deep into the natural habitat of many species via the expansion of agricultural lands and infrastructural development. Carnivore species are particularly at risk, as they demand conserved and well-connected habitat with minimum to no anthropogenic disturbance. In Pakistan, the snow leopard (Panthera uncia) is found in three mountain ranges—the Himalayas, Hindukush, and Karakoram.

To promote the sustainable development of agriculture and forestry economy, it is of great significance to guide farmers to consciously pursue pro-environmental behaviors in the development of the understory economy. Based on field survey data from Yong’an city of Fujian Province and Luoshan County of Henan Province, factor analysis and Oprobit models were mainly used to analyze the influencing factors and influencing the degree of the pro-environmental behaviors of farmer households participating in the understory economy.

Taking Erdaojiang and Dongchang District of Tonghua City, Jilin Province as examples, this paper studies the ecological environment restoration and governance model of their mining areas. In this paper, the vegetation cover (NDVI) data in the past ten years were selected from the study area. The Theil–Sen median and Mann–Kendall (MK) methods were used to analyze the time series of NDVI, and the vegetation cover change trend map of the study area was obtained.

Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021).