The performance of vegetation indices for operational monitoring of CORINE vegetation types

被引:5
作者
Alexandridis, T. K. [1 ]
Oikonomakis, N. [2 ]
Gitas, I. Z. [2 ]
Eskridge, K. M. [3 ]
Silleos, N. G. [1 ]
机构
[1] Aristotle Univ Thessaloniki, Fac Agr, Lab Remote Sensing & GIS, Thessaloniki, Greece
[2] Aristotle Univ Thessaloniki, Fac Forestry & Nat Environm, Lab Forest Management & Remote Sensing, Thessaloniki, Greece
[3] Univ Nebraska, Dept Stat, Lincoln, NE USA
关键词
LEAF-AREA INDEX; BIOMASS ESTIMATION; VIEW ANGLE; SATELLITE DATA; CARBON SINKS; COVER TYPES; TM IMAGES; EOS-MODIS; SENSITIVITY; NDVI;
D O I
10.1080/01431161.2014.902548
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Vegetation monitoring has been performed using remotely sensed images to secure food production, prevent fires, and protect natural ecosystems. Recent satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), provide frequent wide-scale coverage in multiple areas of the spectrum, allowing the estimation of a wide range of specialized vegetation indices (VIs), each offering several advantages. It is not, however, clear which VI performs better during operational monitoring of wide-scale vegetation patches, such as CORINE Land Cover (CLC) classes. The aim of this work was to investigate the performance of several VIs in operational monitoring of vegetation condition of CLC vegetation types, using Terra MODIS data. Comparison among the VIs within each CLC class was conducted using the sensitivity ratio, a statistical measure that has not been used to compare VIs and does not require calibration curves between each VI and a biophysical parameter. In addition, the VI's sensitivity to factors such as the aspect, viewing angle, signal saturation, and partial cloud cover was estimated with correlation analysis in order to identify their operational monitoring ability. Results indicate the enhanced vegetation index as superior for monitoring vegetation condition among CLC types, but not always optimum in performance tests for operational monitoring.
引用
收藏
页码:3268 / 3285
页数:18
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