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Multitemporal Land Use/Land Cover Change Detection for the Batena Watershed, Rift Valley Lakes Basin, Ethiopia

机译:埃塞俄比亚Rift Valley Lakes盆地Batena流域的多时相土地利用/土地覆被变化检测

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摘要

A majorityof therural population in Ethiopiadepends on agriculture. Land use changes during the past couple of decades are mostly linked to agricultural development attributed to factors such as population pressure and environmental changes. Mapping land use/land cover (LULC) to analyze the type, rate, and extent of changes in land use patterns has far reaching significance for policy/decision makers and resource managers to provoke the wide range of applications at regional scales for erosion, landslide, land planning, forest management, and ecosystem conservation. The focus of this chapter is to depict quick and practical approaches to generate spatially and temporally quantified information on land cover dynamics using high-resolution satellite images for the years (1973–2008) in Batena watershed and its environs in southwestern Ethiopia. To quantify the magnitude of LULC change, supervised classification technique was applied using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images employing Bayesian maximum likelihood classifier (MLC) with the aid of ground truth training sites. A majority/minority analysis was used for smoothing the classification results and the accuracy of image classification was carried out by means of a confusion matrix generated through geographic information system (GIS) overlay of the classified maps and the test samples. The classification accuracy was further verified by the strong kappa statistical estimate of more than 90 % as a measure of overall agreement between image and reference data. The final output of remote sensing imagery revealed five land cover classes: Grazing land, bush land, mixed forest, dominantly cultivated agricultural land, and water body. It has been discovered that, there were more active LULC change processes in the area in the first study period (1973–1984) than the second study period (1984–1995) and the third study period (1995–2003). On the other hand, areal extent of cultivated and uncultivated agricultural land has been on a steady decline from 39.7 % in 1995 to 41.4 % in 2003 and a mere 50.1 % in 2008. In the first period, nearly half of the landscape underwent land cover change with more than 17 % of the entire landscape experiencing agricultural expansion. In the second period, the extent of the changes was limited to less than 1/3 of the total area with a smaller amount of agricultural area expansion than before. Though the rate of land cover change was observed to vary across the three periods of study, a general decline of forest cover and amplified increase of agricultural lands of more than 41.7 % was found in the area.
机译:埃塞俄比亚的大多数农村人口依赖农业。在过去的几十年中,土地使用的变化主要与农业发展有关,这归因于人口压力和环境变化等因素。绘制土地利用/土地覆被图(LULC)以分析土地利用方式变化的类型,速度和程度,对政策/决策者和资源管理者在区域范围内侵蚀,滑坡的广泛应用具有深远的意义。 ,土地规划,森林管理和生态系统保护。本章的重点是描述使用高分辨率卫星图像多年来(1973-2008年)在埃塞俄比亚西南部的巴特纳流域及其周围地区生成土地覆盖动态的时空定量信息的快速实用方法。为了量化LULC变化的幅度,在地面真实训练站点的帮助下,采用Landsat主题映射器(TM)和增强型主题映射器(ETM +)图像,采用贝叶斯最大似然分类器(MLC),应用监督分类技术。多数/少数族裔分析用于使分类结果平滑,并且借助通过分类信息的地图和测试样本的地理信息系统(GIS)叠加生成的混淆矩阵来实现图像分类的准确性。通过超过90%的强卡伯统计估计值(作为图像和参考数据之间总体一致性的度量)进一步验证了分类准确性。遥感图像的最终输出显示了五个土地覆被类别:放牧地,灌木丛地,混交林,主要耕种的农业用地和水体。已经发现,在第一个研究期(1973-1984年),该地区的LULC变化过程比第二个研究期(1984-1995年)和第三个研究期(1995-2003年)活跃得多。另一方面,耕地和非耕地的面积从1995年的39.7%稳定下降到2003年的41.4%,2008年仅为50.1%。在第一时期,近一半的景观被土地覆盖。随着整个农业领域中超过17%的景观正在发生变化,这一变化正在发生。在第二阶段,变化的范围被限制在总面积的不到1/3,而农业面积的扩张却比以前少。尽管观察到的三个时期的土地覆被变化率各不相同,但该地区的森林覆盖率普遍下降,而农业用地却增加了41.7%以上。

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