TARGET CLASSIFICATION AND SOIL WATER CONTENT REGRESSION USING LAND SURFACE TEMPERATURE(LST)AND VEGETATION INDEX(VI)

[in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]

Journals >Journal of Infrared and Millimeter Waves >Volume 21 >Issue 4 >Page 269 > Article

Journal of Infrared and Millimeter Waves
Vol. 21, Issue 4, 269 (2002)

TARGET CLASSIFICATION AND SOIL WATER CONTENT REGRESSION USING LAND SURFACE TEMPERATURE(LST)AND VEGETATION INDEX(VI)

[in Chinese]¹, [in Chinese]¹, [in Chinese]¹, [in Chinese]¹, [in Chinese]², [in Chinese]², [in Chinese]³, and [in Chinese]³

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¹[in Chinese]

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³[in Chinese]

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DOI: Cite this Article

[in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese]. TARGET CLASSIFICATION AND SOIL WATER CONTENT REGRESSION USING LAND SURFACE TEMPERATURE(LST)AND VEGETATION INDEX(VI)[J]. Journal of Infrared and Millimeter Waves, 2002, 21(4): 269 Copy Citation Text

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References

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[4] Kealy P S. Hook S J. Separating temperature and emissivity in thermal infrared multispectral scanner data: implications for recovering land surface temperatures. IEEE Trans. Geosci. Remote Sens.,1993,31:1155-1164

[5] Gamon J A. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sens. Envion., 1992,41:35-44

[7] MMoran M S, Clarke T R, Inoue Y, et al. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sens. Envion., 1994,49:246-263

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