首页> 外文期刊>Modeling Earth Systems and Environment >Application of forest canopy density model for forest cover mapping using LISS-IV satellite data: a case study of Sali watershed, West Bengal
【24h】

Application of forest canopy density model for forest cover mapping using LISS-IV satellite data: a case study of Sali watershed, West Bengal

机译:森林覆盖林覆谱法应用Liss-IV卫星数据的应用 - 以西孟加拉邦萨利流域为例

获取原文
获取原文并翻译 | 示例
           

摘要

Investigation of forest canopy density has become an important tool for proper management of natural resources. Vegetation cover density can identify the exact forest gaps within a particular area which in turn will provide the appropriate management strategies for future. Forest canopy density has become an essential tool for identifying the exact areas where the afforestation or reforestation programmes needs to be implemented. The aim and objective of this article is to show up the existing density of forest cover using remote sensing and geographic information system tools. Weighted overlay analysis method has been adopted for investigating forest canopy density of Sali river basin, Bankura district, West Bengal. Several indices likewise normalized difference vegetation index, bareness index, shadow index and perpendicular vegetation index etc. have been used for this study. Higher the weight was assigned for greater concentration of vegetation and lower the weight was assigned for lesser concentration of vegetation. Southern part of the region has very high density of forest coverage in comparison with the northern part of the region. It has been observed that 7.48% of the area is at very low density, 12.63% of low density, 24.84% of medium density, 23.92% of high density and 31.13% of very high forest canopy density.
机译:调查森林冠层密度已成为适当管理自然资源的重要工具。植被覆盖密度可以识别特定区域内的确切森林差距,这反过来将为未来提供适当的管理策略。森林冠层密度已成为识别需要实施造林或再造林方案的确切领域的重要工具。本文的目的和目标是使用遥感和地理信息系统工具来显示森林覆盖的现有密度。加权覆盖分析方法采用了西孟加拉邦巴里河流域森林冠层密度。这项研究已经使用了几种归一化差异植被指数,良心指数,阴影指数和垂直植被指数等的指标。为更高浓度的植被分配重量越高,较低的重量被分配出较少植被浓度的重量。与该地区北部相比,该地区南部具有非常高的森林覆盖密度。已经观察到,该面积的7.48%处于非常低的密度,低密度的12.63%,中密度的24.84%,高密度的23.92%,占极高的森林冠层密度的31.13%。

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