Quantitative inversion of sparse vegetation coverage in desertification area

Autor: Xuedong Li, Xuya Zhang, HongYan Zhang, Guang bin Yang
Rok vydání: 2015
Předmět:
Zdroj: Proceedings of the 2015 International conference on Applied Science and Engineering Innovation.
ISSN: 2352-5401
DOI: 10.2991/asei-15.2015.339
Popis: Based on unmixing model and using the Thematic Mapper (TM) image as well as obtaining end-members by ground spectral measurements, quantitative retrieval of information on sparse vegetation coverage in oasis-desert transitional area in Minqin, Gansu was done. The results showed that a wide band of TM images can be used in extracting sparse vegetation coverage of arid regions. Three components were needed to build unmixing model and there includes light, vegetation not light and vegetation bare soil. And the unmixing model has a high correlation with measured vegetation coverage. Methods used to choose the end-members had certain influence on estimating the vegetation coverage. Monte Carlo method recorded 0.64 as coefficient of determination (R2) 3.8 as root mean square error (RMSE) and therefore was more accurate than the root mean square error minimization method.
Databáze: OpenAIRE