Sustainable Environmental Management: A Case of Assessment of Land Degradation Using Space Technologies in Longido District, Arusha Tanzania

M. Hagai
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Abstract

This study was conducted to assess land degradation in Longido District, Arusha, Tanzania using remote sensing techniques. Biophysical degradation indicators i.e. land use/land cover, land productivity level and soil erosion were used. Specifically, Landsat Satellite images of 1995 and 2015, together with soil data and digital elevation model were applied. Land cover maps of the study area over the study years were produced by supervised classification method. Soil erosion was assessed using RUSLE (Revised Universal Soil Loss Equation) model producing soil erosion map of Longido district, the inputs into the RUSLE model were rainfall, erosivity factor, soil erodibility factor, slope steepness and slope length factor, cover management factor and support practice factor. Biophysical land degradation map was produced by applying weighted overlay technique whereby soil erosion was given more weight followed by land use/land cover of 2015 and land productivity level of 2015. The findings show that about 38% of Longido district areas are highly vulnerable to land degradation which is above the international allowable level. It is being concluded that Longido District is at high risk of failure to sustain livelihood of and resilient for its communities, the earth in general, so it is timely for the district authorities to take steps towards mitigating further land degradation. It is being recommended that sustainable conservation and management strategies as well as policies must be affected by district authorities including farmers and pastoralists to improvise land degradation friendly cultivation and grazing methods.
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可持续环境管理:坦桑尼亚阿鲁沙Longido区利用空间技术评估土地退化的案例
这项研究是为了利用遥感技术评估坦桑尼亚阿鲁沙Longido区的土地退化情况。使用了生物物理退化指标,即土地利用/土地覆盖、土地生产力水平和土壤侵蚀。具体而言,应用了1995年和2015年的陆地卫星图像,以及土壤数据和数字高程模型。研究区域在研究年份的土地覆盖图是通过监督分类法绘制的。利用RUSLE(修正的通用土壤流失方程)模型对Longido地区的土壤侵蚀进行了评估,RUSLE模型的输入为降雨量、侵蚀力因子、土壤可蚀性因子、坡度和坡长因子、覆盖管理因子和支护实践因子。生物物理土地退化图是通过应用加权叠加技术绘制的,通过加权叠加技术对土壤侵蚀给予更大的权重,然后是2015年的土地利用/土地覆盖和2015年的土壤生产力水平。调查结果显示,朗吉多区约38%的地区极易受到土地退化的影响,这一程度高于国际允许水平。得出的结论是,Longido区面临着无法维持其社区(整个地球)生计和恢复能力的高风险,因此地区当局采取措施缓解进一步的土地退化是及时的。有人建议,包括农民和牧民在内的地区当局必须影响可持续的养护和管理战略以及政策,以临时制定有利于土地退化的耕种和放牧方法。
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