基于地理空间技术的埃塞俄比亚Omo Gibe河流域Abelti流域土地利用/覆被变化动态与预测

IF 1.8 Q2 AGRONOMY Advances in Agriculture Pub Date : 2022-08-29 DOI:10.1155/2022/1862461
Melkamu Ateka Derebe, Samuel Dagalo Hatiye, Ligalem Agegn Asres
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引用次数: 1

摘要

埃塞俄比亚是一个正在发展的国家,它需要土地利用规划和以农业为基础的经济的科学依据。土地利用/土地覆盖变化的评价有助于根据国家,特别是研究地区的时间和动态人口增长,对自然资源进行适当的调度和使用,并进行安全管理。开发土地利用评价和分类地图的详细和有用的方法之一是使用地理空间技术,如遥感和地理信息系统(GIS)。本研究的主要重点是评估埃塞俄比亚Omo-Gibe河流域Abelti流域土地利用和土地覆盖(LULC)变化的动态。利用卫星数据,采用极大似然算法和监督分类方法识别流域LULC变化,了解流域的LULC变化情况。利用2000年、2010年和2017年3幅卫星影像,利用地球资源与发展系统(ERDAS)软件进行监督分类,量化土地利用/覆被变化的时空动态,最后利用ArcGIS 10.3应用分类后变化检测技术进行分类后变化检测。从LULC分析来看,从2000年到2017年,农业面积和定居面积都有所增加。另一方面,灌丛地在研究期内呈下降趋势。森林和裸地在2000 - 2010年呈下降趋势,2010 - 2017年呈上升趋势;裸地在2000 - 2010年呈上升趋势,2010 - 2017年呈下降趋势。一般来说,这种变化背后的驱动力是人口增长、快速城市化和森林砍伐,这导致了广泛的环境影响,包括流域栖息地质量的退化。
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Dynamics and Prediction of Land Use and Land Cover Changes Using Geospatial Techniques in Abelti Watershed, Omo Gibe River Basin, Ethiopia
Ethiopia is a growing country which is in need of scientific ground for land use planning and agricultural-based economy. Evaluation of land use/land cover (LULC) changes helps for proper scheduling and use of natural resources with safe administration in accordance with time and dynamic population growth of the country, specifically in the study area. One of the detailed and useful ways to develop land use evaluation and classification maps is the use of geospatial techniques such as remote sensing and geographic information systems (GIS). The main focus of this study is to evaluate the dynamics of land use and land cover (LULC) changes in the Abelti Watershed, Omo-Gibe River basin, Ethiopia. Maximum likelihood algorithm approach supervised classification method was used for identifying the LULC changes using satellite data to know LULC changes in the watershed. Quantifications of spatial and temporal dynamics of land use/cover changes were accomplished by using three satellite images of 2000, 2010, and 2017 and classifying them via a supervised classification algorithm by using Earth Resources and Development System (ERDAS) software and finally applying the postclassification change detection technique was performed by using ArcGIS 10.3. From the LULC analysis, the increase was observed in the agricultural area and settlement area from 2000 to 2017. On the other hand, shrub land followed a declining trend during the study period. However, forest and bare land followed variable trends during the study period in which forest declined from 2000 to 2010 but increased from 2010 to 2017 and bare land increased from 2000 to 2010 and declined from 2010 to 2017. Generally, the driving force behind this change was population growth, rapid urbanization, and deforestation which resulted in a wide range of environmental impacts, including degraded habitat quality in the watershed.
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来源期刊
Advances in Agriculture
Advances in Agriculture Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
2.60
自引率
0.00%
发文量
100
审稿时长
18 weeks
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