Discriminating indicator grass species for rangeland degradation assessment using hyperspectral data resampled to AISA Eagle resolution

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 70, Issue , 2012, Pages 56-65

  Mansour, Khalid ^a   Mutanga, Onisimo ^a   Everson, Terry ^a   Adam, Elhadi ^a  

^a UNIVERSITY OF KWAZULU NATAL   (South Africa)

Author keywords

Field spectrometer measurements; Indicator species; Random forest; Rangeland degradation; Variable selection

Indexed keywords

AIR-BORNE SENSORS; CANOPY REFLECTANCE SPECTRA; DEGRADATION ASSESSMENT; ELECTROMAGNETIC SPECTRA; ERAGROSTIS CURVULA; GRASS SPECIES; GRAZING MANAGEMENT; HYPERSPECTRAL DATA; INDICATOR SPECIES; MAPPING INDICATORS; NEAR INFRARED REGION; OPTIMAL NUMBER; OPTIMAL WAVELENGTH; RANDOM FOREST ALGORITHM; RANDOM FORESTS; RANGELAND MANAGEMENT; SPECTRAL MEASUREMENT; VARIABLE SELECTION;

ALGORITHMS; DECISION TREES; DEGRADATION; FORESTRY; OPTIMIZATION;

PHOTODEGRADATION;

ALGORITHM; BIOINDICATOR; FOREST CANOPY; GRASS; GRAZING MANAGEMENT; HABITAT FRAGMENTATION; RANGELAND; SPECTRAL REFLECTANCE; SUSTAINABLE DEVELOPMENT; WAVELENGTH;

ALGORITHMS; DEGRADATION; FORESTRY; OPTIMIZATION; SPECIES IDENTIFICATION;

ARISTIDA; ERAGROSTIS CURVULA; HYPARRHENIA HIRTA; SPOROBOLUS INDICUS CAPENSIS;

EID: 84860222532     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2012.03.006     Document Type: Article

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