Günlü Alkan, Keleş Sedat, Ercanlı İlker, Şenyurt Muammer
Çankırı Karatekin University, Faculty of Forestry, 18200, Çankırı, Turkey.
Environ Monit Assess. 2017 Oct 4;189(11):538. doi: 10.1007/s10661-017-6254-2.
The objective of this study is to estimate the leaf area index (LAI) of a forest ecosystem using two different satellite images, WorldView-2 and Aster. For this purpose, 108 sample plots were taken from pure Crimean pine forest stands of Yenice Forest Management Planning Unit in Ilgaz Forest Management Enterprise, Turkey. Each sample plot was imaged with hemispherical photographs with a fish-eye camera to determine the LAI. These photographs were analyzed with the help of Hemisfer Hemiview software program, and thus, the LAI of each sample plot was estimated. Furthermore, multiple regression analysis method was used to model the statistical relationships between the LAI values and band spectral reflection values and some vegetation indices (Vis) obtained from satellite images. The results show that the high-resolution WorldView-2 satellite image is better than the medium-resolution Aster satellite image in predicting the LAI. It was also seen that the results obtained by using the VIs are better than the bands when the LAI value is predicted with satellite images.
本研究的目的是利用两颗不同的卫星图像——WorldView-2和Aster，估算森林生态系统的叶面积指数（LAI）。为此，从土耳其伊尔加兹森林管理企业耶尼塞森林管理规划单元的纯克里米亚松林分中选取了108个样地。每个样地用鱼眼相机拍摄半球形照片以确定叶面积指数。这些照片借助Hemisfer Hemiview软件程序进行分析，从而估算出每个样地的叶面积指数。此外，采用多元回归分析方法对叶面积指数值与从卫星图像获得的波段光谱反射值及一些植被指数（Vis）之间的统计关系进行建模。结果表明，在预测叶面积指数方面，高分辨率的WorldView-2卫星图像优于中分辨率的Aster卫星图像。还发现，当用卫星图像预测叶面积指数值时，使用植被指数得到的结果比波段更好。
