Normalized difference;
Color space;
N-dimensional;
Material identification;
Soil index;
Vegetation index;
Soil-vegetation index;
Emergent vegetation;
Partial canopy cover;
Mineral mapping;
LEAF-AREA INDEX;
VEGETATION INDEX;
PARTICLE-SIZE;
REFLECTANCE;
SOIL;
COVER;
MODEL;
D O I:
10.1016/j.rse.2021.112622
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Identification of materials based on spectral reflectance is confounded by variations in reflectance magnitude that are independent of the spectral shape. Local variations such as viewing/illumination angles, multiscale soil surface roughness that causes shadows and redistributes light, and soil moisture content, all drive changes in magnitude that are distinct from the spectral variations, and complicate identification and modeling of targets based on spectral features. Normalization metrics that remove magnitude variations can greatly clarify the nature of spectral differences, simplifying interpretation of reflectance features in spectral imagery. Normalized difference measures are particularly useful because of the simplicity of the computation, the convenient scaling, and the ease with which the normalized difference procedure can be extended to multiple dimensions. The twodimensional normalized difference space described here allows for improved discrimination among bare soils and emergent vegetation when there are multiple soil types in the scene. A 2-D model of soil-specific change in vegetation density is presented. An application of the vector index to mineral identification and mapping is also presented, with an emphasis on band selection.
机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Jia, Li
Zhou, Jie
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机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Delft Univ Technol, Dept Geosci & Remote Sensing, NL-2628 CN Delft, NetherlandsChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Zhou, Jie
Zheng, Chaolei
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机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
机构:
Univ New Hampshire, Inst Study Earth Oceans & Space, Complex Syst Res Ctr, Durham, NH 03824 USAUniv New Hampshire, Inst Study Earth Oceans & Space, Complex Syst Res Ctr, Durham, NH 03824 USA
Xiao, XM
Shen, ZX
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机构:Univ New Hampshire, Inst Study Earth Oceans & Space, Complex Syst Res Ctr, Durham, NH 03824 USA
Shen, ZX
Qin, XG
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机构:Univ New Hampshire, Inst Study Earth Oceans & Space, Complex Syst Res Ctr, Durham, NH 03824 USA