Journal of Geo-information Science >
Research on Pixel Unmixing of Typical Surface Features in Oasis Based on the MESMA Model
Received date: 2012-06-26
Revised date: 2012-12-25
Online published: 2013-06-17
Soil salinization is an important worldwide environmental problem, especially in arid and semi-arid regions. Quantitative remote sensing provides accurate and up-to-date information of spatio-temporal dynamics of salinity. Studies at both home and overseas showed that it is hard to acquire reliable information of salinity by using a single wavelength in visible, near infrared (NIR), thermal or microwave domain, especially in a sophisticat-ed surface conditions such as agricultural fields, while the reported methods inherited many limitations in practical applications including time-lag effect, being too complex to calculate, being excessively dependent on meteorological observations and field measurements etc. Therefore, developing of simple, effective and operational methods for the satellite estimation of surface salinity, especially vegetation cover is of great interest for both researchers in remote sensing community and policy makers for the sustainable development of eco-environments. Mixed pixels as an important aspects in remote sensing information uncertainty, it always been one of the core areas of quantitative remote sensing science research. With the congenital features, i.e., a homogeneous underlying surface and simple meteorological conditions and so on, arid area has become an ideal place for quantitative remote sensing products testing. In this article we took the Kuqa River, in north of Tarim Basin oasis as the study field. At first we selected spectral mixture analysis models, according to different feature types we extracted the endmembers in different ways. Depending on EAR (Endmember Average RMSE) and MASA (Minimum Average Spectral Angle) we chose the optimal endmembers. At last we carried out pixel unmixing by using the MESMA (Multiple End-member Spectral Mixture Analysis) model, then we finished the accuracy evaluation and comparative analysis. The results showed that MESMA model can effectively improve the information accuracy of a pixel. Therefore, it provided a scientific basis for the high-precision information extraction for typical oasis surface features.
DING Jian-Li, TAO Yuan . Research on Pixel Unmixing of Typical Surface Features in Oasis Based on the MESMA Model[J]. Journal of Geo-information Science, 2013 , 15(3) : 452 -460 . DOI: 10.3724/SP.J.1047.2013.00452
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