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

Dianjun Zhang; Guoqing Zhou

doi:10.1117/12.2220607

9 December 2015 Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

Dianjun Zhang, Guoqing Zhou

Author Affiliations +

Proceedings Volume 9808, International Conference on Intelligent Earth Observing and Applications 2015; 980825 (2015) https://doi.org/10.1117/12.2220607
Event: International Conference on Intelligent Earth Observing and Applications, 2015, Guilin, China

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.

Citation Download Citation

Dianjun Zhang and Guoqing Zhou "Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space", Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980825 (9 December 2015); https://doi.org/10.1117/12.2220607

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