Species distribution modelling for the people: Unclassified landsat TM imagery predicts bird occurrence at fine resolutions

Diversity and Distributions

Volumn 19, Issue 7, 2013, Pages 855-866

  Shirley, S M ^a   Yang, Z ^a   Hutchinson, R A ^b   Alexander, J D ^c   Mcgarigal, K ^d   Betts, M G ^a  

^a OREGON STATE UNIVERSITY   (United States)

^b Oregon State University   (United States)

^c Klamath Bird Observatory   (United States)

^d UNIVERSITY OF MASSACHUSETTS   (United States)

Author keywords

Boosted regression trees; Land cover; Model validation; Species distribution modelling; Unclassified remote sensing imagery; Western Oregon

Indexed keywords

AVIFAUNA; BIOMASS; IMAGE RESOLUTION; LAND COVER; LANDSAT THEMATIC MAPPER; MODEL VALIDATION; NDVI; NUMERICAL MODEL; PHOTOSYNTHESIS; POPULATION DISTRIBUTION; POPULATION MODELING; PREDICTION; REFLECTANCE; REGRESSION ANALYSIS; RESERVE DESIGN; SATELLITE IMAGERY; SPECIES OCCURRENCE; VEGETATION STRUCTURE;

CASCADE RANGE; COAST RANGES; KLAMATH MOUNTAINS; OREGON; UNITED STATES;

AVES;

EID: 84879183572     PISSN: 13669516     EISSN: 14724642     Source Type: Journal    
DOI: 10.1111/ddi.12093     Document Type: Article

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