Effect of image spatial and spectral characteristics on mapping semi-arid rangeland vegetation using multiple endmember spectral mixture analysis (MESMA)

TitleEffect of image spatial and spectral characteristics on mapping semi-arid rangeland vegetation using multiple endmember spectral mixture analysis (MESMA)
Publication TypeJournal Article
Year of Publication2013
AuthorsThorp KR, French A.N., Rango A.
JournalRemote Sensing of Environment
Start Page120
Date Published01/2013
Accession NumberJRN49864
ARIS Log Number286320
KeywordsAVIRIS, cresotebush, grass, Hyperspectral, HyspIRI, Imaging speactroscopy, mesquite, NDVI, Nonphotosynthetic, spatial scale, Spectra, VAI

Encroachment of invasive shrubs into grassland areas on rangelands in the southwestern United States threatens the viability of livestock production and can severely alter hydrology and biodiversity.  Novel remote sensing technologies may provide useful information for monitoring and remediating this threat.  The objectives were to investigate multiple endmember spectral mixture analysis (MESMA) as an approach to map rangeland vegetation using hyperspectral remote sensing imagery and to test the sensitivity of MESMA to alternative image spatial resolutions and spectral waveband combinations. Data from two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) overflights at the Jornada Experimental Range in southwestern New Mexico were used in the analysis. Endmember spectra were selected from a library of ground-based spectral observations collected with a field spectroradiometer. A 4-endmember MESMA was conducted for both AVIRIS images at their native spatial resolutions using 113 10-nm wavebands from 422 to 2339 nm. Additional MESMAs were conducted at 10 multiples of the images' native spatial resolution and for 6 alternative combinations of spectral waveband subregions.  Maps of endmember fractional cover for green shrub vegetation, nonphotosynthetic grass vegetation, and bare soil were comparable to an earlier vegetation classification map of Jornada. MESMA fractional cover estimates for the green vegetation endmember were positively correlated with the normalized difference vegetation index (NDVI) with correlation coefficients (r) greater than 0.58.  Correlation coefficients between the sum of the green and nonphotosynthetic vegetation endmembers and the cellulose absorption index (CAI) were greater than 0.59. Correlation coefficients between MESMA fractional green vegetation cover and NDVI for independent multispectral images were greater than 0.57.  Despite obvious losses in spatial detail at coarser image spatial resolutions, MESMA results for images with spatial resolution degraded by a factor of 10 (~150 m) were quite similar to aggregated results for MESMA at the native spatial resolution (~15 m).  Additionally, MESMA results were shown to be substantially more sensitive to the spectral wavebands used in the analysis as compared to the spatial resolution of the images.  Considered together, the MESMA results at Jornada indicate that fine spectral resolution with hyperspectral remote sensing is substantially more important than incremental changes in image spatial scale from 15 m to 150 m.