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Proceedings Paper

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space
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Paper Abstract

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Paper Details

Date Published: 9 December 2015
PDF: 4 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980825 (9 December 2015); doi: 10.1117/12.2220607
Show Author Affiliations
Dianjun Zhang, Tianjin Univ. (China)
Guoqing Zhou, Guilin Univ. of Technology (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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