Land use/land cover changes in the central part of the Chitwan Annapurna Landscape, Nepal

PeerJ

article

Jagan Nath Adhikari¹  Bishnu Prasad Bhattarai¹  Maan Bahadur Rokaya³  Tej Bahadur Thapa¹ 

[1] Central Department of Zoology, Institute of Science and Technology, Tribhuvan University Kathmandu;Department of Zoology, Birendra Multiple Campus, Tribhuvan University;Global Change Research Institute, Czech Academy of Sciences;Institute of Botany, Czech Academy of Sciences

关键词: Accuracy assessment;    Habitat change detection;    Image classification;    Landsat image;    Remote sensing;   

DOI  :  10.7717/peerj.13435

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Background Land use/land cover assessment and monitoring of the land cover dynamics are essential to know the ecological, physical and anthropogenic processes in the landscape. Previous studies have indicated changes in the landscape of mid-hills of Nepal in the past few decades. But there is a lack of study in the Chitwan Annapurna Landscape; hence, this study was carried out to fill in study gap that existed in the area. Methods This study evaluates land use/land cover dynamics between 2000 to 2020 in the central part of the Chitwan Annapurna Landscape, Nepal by using Landsat images. The Landsat images were classified into eight different classes using remote sensing and geographic information system (GIS). The accuracy assessment of classified images was evaluated by calculating actual accuracy, producer’s accuracy, user’s accuracy and kappa coefficient based on the ground-truthing points for 2020 and Google Earth and topographic maps for images of 2010 and 2000. Results The results of land use/land cover analysis of Landsat image 2020 showed that the study area was composed of grassland (1.73%), barren area (1.76%), riverine forest (1.93%), water body (1.97%), developed area (4.13%), Sal dominated forest (15.4%), cropland (28.13%) and mixed forest (44.95%). The results of land cover change between 2000 to 2020 indicated an overall increase in Sal dominated forest (7.6%), developed area (31.34%), mixed forest (37.46%) and decrease in riverine forest (11.29%), barren area (20.03%), croplands (29.87%) and grasslands (49.71%). The classification of the images of 2000, 2010 and 2020 had 81%, 81.6% and 84.77% overall accuracy, respectively. This finding can be used as a baseline information for the development of a proper management plan to protect wildlife habitats and forecasting possible future changes, if needed.

【 授权许可】

CC BY