Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications

被引:1539
作者
Xue, Jinru [1 ]
Su, Baofeng [1 ]
机构
[1] Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
LEAF-AREA INDEX; WATER-STRESS INDEX; INFRARED REFLECTANCE SPECTROSCOPY; SPECTRAL REFLECTANCE; CHLOROPHYLL CONTENT; BIDIRECTIONAL REFLECTANCE; COVER PHOTOGRAPHY; PIGMENT CONTENT; SOIL; CANOPY;
D O I
10.1155/2017/1353691
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications. These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV). Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used. Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface. In the real-world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground. The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed. This paper reviews more than 100VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision. Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas.
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页数:17
相关论文
共 137 条
[1]   Irrigation Timing in Maize by Using the Crop Water Stress Index (CWSI) [J].
Anda, A. .
CEREAL RESEARCH COMMUNICATIONS, 2009, 37 (04) :603-610
[2]  
[Anonymous], 1994, P 6 INT S PHYS MEAS
[3]  
Arkebauer T.J., 2005, MICROMETEOROLOGY AGR, P93, DOI [10.2134/agronmonogr47.c5, DOI 10.2134/AGRONMONOGR47.C5]
[4]  
Ashburn P, 1979, NASA P TECH, V1
[5]  
Badhwar G., 1981, Q TECHN INT M NASA J
[6]   Characterization of Vitis vinifera L. Canopy Using Unmanned Aerial Vehicle-Based Remote Sensing and Photogrammetry Techniques [J].
Ballesteros, Rocio ;
Fernando Ortega, Jose ;
Hernandez, David ;
Angel Moreno, Miguel .
AMERICAN JOURNAL OF ENOLOGY AND VITICULTURE, 2015, 66 (02) :120-129
[7]  
Bannari A, 2002, INT GEOSCI REMOTE SE, P3053, DOI 10.1109/IGARSS.2002.1026867
[8]  
Bannari A., 1994, P 1 INT AIRB REM SEN, P12
[9]   POTENTIALS AND LIMITS OF VEGETATION INDEXES FOR LAI AND APAR ASSESSMENT [J].
BARET, F ;
GUYOT, G .
REMOTE SENSING OF ENVIRONMENT, 1991, 35 (2-3) :161-173
[10]  
Baret F., 1989, P IGARSS 89, V3, P1355