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Remote sensing and GIS based assessment of soil erosion and soil loss risk around hill top surface mines situated in Saranda Forest, Jharkhand

机译:基于遥感和GIS的贾坎德邦萨兰德森林山顶地雷周围水土流失和土壤流失风险评估

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The quantitative analysis of soil erosion changes over 7 years due to mining operations in two neighboring hilltops in West-Singhbhum District, Jharkhand, are reported. CartoSat-1, ETM+ and LISS-IV satellites' data provided spatial inputs in Universal Soil Loss Equation (USLE) and Morgan, Morgan and Finney method (MMF) models, which were used to predict the average annual soil erosion during the period of 2001-2008 in a geographic information system (GIS), in six distinct classes. In the comparative analysis of the 7-year period, the MMF model revealed a lower coefficient of variation 0.71 (2001) and 0.84 (2008) in predicted average annual soil loss, which increased by 16% (81.3-94.2 t ha(-1)yr(-1)), whereas in the case of USLE, the coefficients of variation were 3.88 (2001) and 1.94 (2008), with an increase of 61% (48.56-78.38 t ha(-1)yr(-1)). The correlation coefficient of these models was 0.1 (2001) and 0.36 (2008), which shows that both models predicted significantly differently as a result of the different factors considered. Overall, the MMF model predicted a higher soil erosion rate but less variation than USLE. Both models showed soil erosion rates were drastically increased by anthropogenic activities in the area, hence careful consideration is needed. The same sensor and imaging data could not be maintained. Correction of errors may reduce erosion, but it will still remain significant for future planning.
机译:据报道,在贾坎德邦西部-Singhbhum区的两个相邻山顶上,由于采矿作业,对土壤侵蚀进行了长达7年的定量分析。 CartoSat-1,ETM +和LISS-IV卫星的数据为通用土壤流失方程(USLE)和Morgan,Morgan和Finney方法(MMF)模型提供了空间输入,这些模型用于预测2001年期间的年均土壤侵蚀-2008在六个不同类别的地理信息系统(GIS)中。在7年期的比较分析中,MMF模型显示预测的年均土壤流失的变异系数较低,分别为0.71(2001)和0.84(2008),增加了16%(81.3-94.2 t ha(-1 )yr(-1)),而在USLE中,变异系数为3.88(2001)和1.94(2008),增加了61%(48.56-78.38 t ha(-1)yr(-1 ))。这些模型的相关系数分别为0.1(2001年)和0.36(2008年),这表明由于所考虑的不同因素,两个模型的预测差异显着。总体而言,MMF模型预测的土壤侵蚀速率比USLE高,但变化较小。两种模型均显示该地区的人为活动使土壤侵蚀率急剧增加,因此需要仔细考虑。无法保持相同的传感器和成像数据。纠正错误可能会减少腐蚀,但对于将来的计划仍然很重要。

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