Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia

Q2 Environmental Science Cogent Environmental Science Pub Date : 2020-01-01 DOI:10.1080/23311843.2020.1778998
Dires Tewabe, Temesgen Fentahun Adametie
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引用次数: 81

Abstract

Abstract Land use land cover (LULC) change detection based on remote sensing data is an important source of information for various decision support systems. Information derived from land use and land cover change detection is important to land conservation, sustainable development, and management of water resources. This purpose of this study is therefore concerned with identifying the change in land use and land cover detection of the Tana basin. To identify land cover changes detection; remote sensing data, satellite imagery and image processing techniques had done within three dates of 1986, 2002 and 2018 using Land sat TM 30 m resolution images. ENVI and Arc GIS soft wares had used to identify the changes. The classification had done using six land cover (water body, bushland, grassland, forestland, cultivated, and residential land) class. Preprocessing and classification of the images had analyzed carefully and accuracy assessment was tested separately using the kappa coefficient. The results showed that overall accuracy in the basin was 84.21%, 83.32% and 91.40% and kappa coefficient of 79.02%, 83.32%, 89.66% for the years 1986, 2002 and 2018 respectively. This study indicated that in the last 32 years period, agricultural land and residential areas had significantly increased by 15.61% and 8.05% respectively in the basin. Therefore, proper land management practices, integrated watershed management, and active participation of the local community should be advance to protect undesirable LULC change in the basin.
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利用遥感评估埃塞俄比亚西北部塔纳湖盆地的土地利用和土地覆盖变化检测
基于遥感数据的土地利用土地覆被变化检测是各种决策支持系统的重要信息来源。从土地利用和土地覆盖变化监测中获得的信息对土地保护、可持续发展和水资源管理具有重要意义。因此,本研究的目的是确定塔纳盆地的土地利用变化和土地覆盖检测。识别土地覆盖变化检测;遥感数据、卫星图像和图像处理技术在1986年、2002年和2018年三个日期内使用陆地卫星TM 30米分辨率图像完成。利用ENVI和Arc GIS软件对变化进行了识别。采用水体、灌木林、草地、林地、耕地、居民点6个土地覆盖等级进行分类。对图像的预处理和分类进行了仔细的分析,并分别使用kappa系数进行了精度评估。结果表明,1986年、2002年和2018年,流域整体精度分别为84.21%、83.32%和91.40%,kappa系数分别为79.02%、83.32%和89.66%。研究表明,近32 a来,流域农业用地和居民居住面积分别显著增加了15.61%和8.05%。因此,应推进适当的土地管理实践、流域综合管理和当地社区的积极参与,以保护流域的不良LULC变化。
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Cogent Environmental Science
Cogent Environmental Science ENVIRONMENTAL SCIENCES-
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