• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Soil Research >Soil erosion analysis by RUSLE and sediment yield models using remote sensing and GIS in Kelantan state, Peninsular Malaysia
【24h】

Soil erosion analysis by RUSLE and sediment yield models using remote sensing and GIS in Kelantan state, Peninsular Malaysia

机译：利用遥感和Kelantan国家的遥感和GIS的冲击和沉积物产量模型土壤侵蚀分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The present study used pixel-based soil erosion analysis through Revised Universal Soil Loss Equation (RUSLE) and a sediment yield model. The main motive of this study is to find soil erosion probability zones and accordingly prioritise watersheds using remote sensing and Geographic Information System (GIS) techniques in Kelantan state, Peninsular Malaysia. The catchment was divided into 82 watersheds and soil loss of the catchment was calculated. Soil loss and sediment yield were divided into five categories ranging from very low to very high. Maximum area of the very high soil-loss category was observed in uncultivated land and the maximum area of very low soil-loss category was in forest. Soil erosion probability zones were also divided into five categories in which 36.1% of the area experienced zero soil erosion and 20.1% and 17.8% represented very high and high probability zones respectively. The maximum very high and high probability zones were 61.6% and 28.5% of the watershed area respectively. Prioritisation was according to the area covered by very high and high soil erosion probability zones, which showed that out of 82 watersheds, two had the very high and high priority categories respectively. The overall results indicate that high rainfall and agricultural activities enhanced the soil erosion rate on steep slopes in the catchment. Pixel-based soil erosion analysis through remote sensing and GIS was a very effective tool in finding accurate causes of soil erosion. Furthermore, it was suggested that agricultural activities and deforestation should be stopped on steep slopes because of their contribution in increasing soil erosion.
机译：本研究采用了通过修订的通用土壤损失方程（风格）和沉积物屈服模型的映象的土壤侵蚀分析。本研究的主要动力是使用遥感和地理信息系统（GIS）在Kelantan State，半岛马来西亚的遥感和地理信息系统（GIS）技术优先考虑流域优先顺序。该集水区分为82分水岭，计算出集水区的土壤丧失。土壤损失和沉积物产量分为5个类别，从非常低到非常高。在未开垦的土地中观察到非常高的土壤损失类别的最大面积，森林中非常低的土壤损失类别的最大面积。土壤侵蚀概率区还分为五大类，其中该地区的36.1％经历了零土壤侵蚀，分别代表了20.1％和17.8％，分别代表非常高和高概率区。最大高概率区分别为分水岭区域的61.6％和28.5％。优先排序是根据非常高和高土壤腐蚀概率区所涵盖的面积，这表明出于82分水岭，两者分别具有非常高，优先的类别。总体结果表明，高降雨量和农业活动提高了集水区陡坡上的土壤侵蚀率。通过遥感和GIS的基于像素的土壤侵蚀分析是一种非常有效的工具，用于找到土壤侵蚀的准确原因。此外，有人建议由于他们对增加土壤侵蚀的贡献，应在陡坡上停止农业活动和砍伐砍伐。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号