Evaluation of a linear mixing model to retrieve soil and vegetation temperatures of land targets

Jinxin Yang, Li Jia*, Yaokui Cui, Jie Zhou, Massimo Menenti

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

A simple linear mixing model of heterogeneous soil-vegetation system and retrieval of component temperatures from directional remote sensing measurements by inverting this model is evaluated in this paper using observations by a thermal camera. The thermal camera was used to obtain multi-angular TIR (Thermal Infra-Red) images over vegetable and orchard canopies. A whole thermal camera image was treated as a pixel of a satellite image to evaluate the model with the two-component system, i.e. soil and vegetation. The evaluation included two parts: evaluation of the linear mixing model and evaluation of the inversion of the model to retrieve component temperatures. For evaluation of the linear mixing model, the RMSE is 0.2 K between the observed and modelled brightness temperatures, which indicates that the linear mixing model works well under most conditions. For evaluation of the model inversion, the RMSE between the model retrieved and the observed vegetation temperatures is 1.6K, correspondingly, the RMSE between the observed and retrieved soil temperatures is 2.0K. According to the evaluation of the sensitivity of retrieved component temperatures on fractional cover, the linear mixing model gives more accurate retrieval accuracies for both soil and vegetation temperatures under intermediate fractional cover conditions.

Original languageEnglish
Title of host publicationIOP Conference Series: Earth and Environmental Science
PublisherIOP Publishing
Volume17
Edition1
DOIs
Publication statusPublished - 2014
Event35th International Symposium on Remote Sensing of Environment, ISRSE 2013 - Beijing, China
Duration: 22 Apr 201326 Apr 2013

Publication series

NameIOP Conference Series: Earth and Environmental Science
PublisherIOP Publishing
ISSN (Print)1755-1307

Conference

Conference35th International Symposium on Remote Sensing of Environment, ISRSE 2013
CountryChina
CityBeijing
Period22/04/1326/04/13

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