SAGA GIS计算的基于距离的植被指数:LANDSAT TM图像垂直和转化土壤调整方法的比较

Polina Lemenkova
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引用次数: 1

摘要

利用SAGA GIS对覆盖冰岛(15.5°W-21°W, 64.5°N-67°N)的2001年Landsat-TM遥感数据进行了基于距离的植被指数(VIs)测试:垂直植被指数(PVI)的4种方法和土壤调整植被指数TSAVI的2种方法。土壤背景线上植被的PVI作为叶面积指数(LAI)表示健康状况。结果表明,植被反射率与土壤背景线呈线性关系。4个PVI模型和2个TSAVI模型显示了与LAI的决定系数。数据集显示了计算系数的变化。基于四种不同算法的PVI直方图中的模式差异为:-7.1,-8.36,2.78和7.0。TSAVI两种方法的数据集范围在4.4 -80.6之间,第一种算法的直方图呈钟形模式(8.09 - 23.29),第二种算法的数据集呈不规则形状,模式从0.11 - 0.2开始,逐渐减少到0.26。SAGA GIS允许基于植被与土壤背景相交的NDVI计算PVI和TSAVI。遮蔽NIR和R,使用SAGA GIS中嵌入的方程对网格进行线性回归。基于距离的PVI和基于坡度的TSAVI的优势在于,与基于坡度的PVI相比,基于距离的PVI调整了土壤亮度线上像素点的位置,使其更加精细。
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Distance-based vegetation indices computed by SAGA GIS: A comparison of the perpendicular and transformed soil adjusted approaches for the LANDSAT TM image
Landsat-TM of 2001 covering Iceland (15.5°W-21°W, 64.5°N-67°N) was processed using SAGA GIS for testing distance-based Vegetation Indices (VIs): four approaches of Perpendicular Vegetation Index (PVI) and two approaches of Transformed Soil Adjusted Vegetation Index TSAVI. The PVI of vegetation from the soil background line indicated healthiness as a leaf area index (LAI). The results showed that the reflectance for vegetation has a linear relation with soil background line. Four PVI models and two TSAVI shown coefficients of determination with LAI. The dataset demonstrate variations in the calculated coefficients. The mode in the histograms of the PVI based on four different algorithms show the difference:-7.1,-8.36, 2.78 and 7.0. The dataset for the two approaches of TSAVI: first case ranges in 4.4.-80.6 with a bell-shape mode of a histogram (8.09 to 23.29) for the first algorithm and an irregular shape for the second algorithm with several modes starting from 0.11 to 0.2 and decreasing to 0.26. SAGA GIS permits the calculation of PVI and TSAVI by computed NDVI based on the intersection of vegetation and soil background. Masking the NIR and R, a linear regression of grids was performed using an equation embedded in SAGA GIS. The advantages of the distance-based PVI and TSAVI consists in the adjusted position of pixels on the soil brightness line which refines it comparing to the slope-based VIs. The paper demonstrates SAGA GIS application in agricultural studies.
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