Natural forces and anthropogenic activities greatly alter land cover, deteriorate or alleviate forest fragmentation and affect biodiversity. Thus land cover and forest fragmentation dynamics have become a focus of concern for natural resource management agencies and biodiversity conservation communities. However, there are few land cover datasets and forest fragmentation information available for the Dhorpatan Hunting Reserve (DHR) of Nepal to develop targeted biodiversity conservation plans. In this study, these gaps were filled by characterizing land cover and forest fragmentation trends in the DHR. Using five Landsat images between 1993 and 2018, a support vector machine algorithm was applied to classify six land cover classes: forest, grasslands, barren lands, agricultural and built-up areas, water bodies, and snow and glaciers. Subsequently, two landscape process models and four landscape metrics were used to depict the forest fragmentation situations. Results showed that forest cover increased from 39.4% in 1993 to 39.8% in 2018. Conversely, grasslands decreased from 38.2% in 1993 to 36.9% in 2018. The forest shrinkage was responsible for forest loss during the period, suggesting that the loss of forest cover reduced the connectivity between forest and non-forested areas. Expansion was the dominant component of the forest restoration process, implying that it avoided the occurrence of isolated forests. The maximum value of edge density and perimeter area fractal dimension metrics and the minimum value of aggregation index were observed in 2011, revealing that forests in this year were most fragmented. These specific observations from the current analysis can help local authorities and local communities, who are highly dependent on forest resources, to better develop local forest management and biodiversity conservation plans.

自然力量和人为活动极大地改变了土地覆盖，恶化或减轻了森林破碎化并影响了生物多样性。因此，土地覆盖和森林碎片化动态已成为自然资源管理机构和生物多样性保护社区关注的焦点。但是，尼泊尔的Dhorpatan狩猎保护区（DHR）缺乏制定目标明确的生物多样性保护计划的土地覆盖数据集和森林破碎信息。在这项研究中，通过描述DHR中的土地覆盖和森林破碎化趋势来填补这些空白。使用1993年至2018年之间的五张Landsat图像，使用支持向量机算法对六种土地覆盖类别进行分类：森林，草原，荒地，农业和建筑面积，水体以及雪和冰川。随后，使用两个景观过程模型和四个景观度量来描述森林破碎状况。结果表明，森林覆盖率从1993年的39.4％增加到2018年的39.8％。相反，草地从1993年的38.2％减少到2018年的36.9％。覆盖减少了森林与非森林区域之间的连通性。扩张是森林恢复过程的主要组成部分，这意味着它避免了孤立森林的发生。2011年观测到边缘密度和周边区域分形维数的最大值，以及聚集指数的最小值，这表明今年的森林是最零散的。