Mapping Vegetation, Soils, and Geology in Semiarid Shrublands Using Spectral Matching and Mixture Modeling of SWIR AVIRIS Imagery
✍ Scribed by Nick A. Drake; Steve Mackin; Jeff J. Settle
- Book ID
- 104165531
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 484 KB
- Volume
- 68
- Category
- Article
- ISSN
- 0034-4257
No coin nor oath required. For personal study only.
✦ Synopsis
Spectral matching and linear mixture modeling tech-geological mapping because it allowed identification and niques have been applied to synthetic imagery and mapping of the relatively pure regions of all the surficial AVIRIS SWIR imagery of a semiarid rangeland in order materials that exert an influence on the spectral response. to determine their effectiveness as mapping tools, the
The maps of the different clay minerals were of considersynergism between the two methods, and their advanable value for mineral exploration purposes. Conversely, tages, and limitations for rangeland resource exploitation spectral matching was less useful than mixture modeling and management. Spectral matching of pure library specfor rangeland vegetation studies because a classification of tra was found to be an effective method of locating and all pixels is needed and abundance estimates are required identifying endmembers for mixture modeling although for many applications. Mixture modeling allowed identifisome problems were found with the false identification cation of both nonphotosynthetic and green vegetation of gypsum. Mixture modeling could accurately estimate cover and thus total cover. Though the green vegetation proportions for a large number of materials in synthetic mixture map appears to be very precise, the nonphotoimagery; however, it produced high variance estimates synthetic vegetation estimates were poor. ©Elsevier Sciand high error estimates when presented with all nine ence Inc., 1999 AVIRIS endmembers because of high noise levels in the imagery. The problem of which endmembers to select was addressed by implementing a mixture model that allowed