Spatial Model of Canopy Density in Mangrove Forest of Percut Sei Tuan

N. Sulistiyono, K. Amri, P. Patana, A. S. Thoha
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引用次数: 1

Abstract

Information about canopy density is needed in many ways, for example, in estimating forest degradation and forest quality. Utilization of vegetation index values on satellite imagery can be used to predict canopy density distribution. This study aims to predict canopy density distribution in mangrove forests. The methodology used is using regression analysis by connecting Normalized Difference Vegetation Index (NDVI) value with canopy density values in the field. The NDVI value is derived from Landsat 8 satellite images, while the canopy density percentage is obtained by using a camera. The spatial distribution of canopy density is obtained through spatial modeling using Geographic Information System (GIS). The results showed that the NDVI value of the linear regression model could be used to predict the density distribution of mangrove forest canopy with r square value of 59.0% and sig value <0.005.
柏山团红树林冠层密度的空间模型
在许多方面都需要关于冠层密度的信息,例如在估计森林退化和森林质量方面。利用卫星影像上的植被指数值可以预测林冠密度分布。本研究旨在预测红树林的冠层密度分布。采用回归分析方法,将归一化植被指数(NDVI)值与野外冠层密度值联系起来。NDVI值来源于Landsat 8卫星图像,而冠层密度百分比则通过相机获得。利用地理信息系统(GIS)对林冠密度进行空间建模,得到林冠密度的空间分布。结果表明:线性回归模型的NDVI值可用于预测红树林冠层密度分布,r平方值为59.0%,sig值<0.005;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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