The performance of random forests in an operational setting for large area sclerophyll forest classification

Remote Sensing

Volumn 5, Issue 6, 2013, Pages 2838-2856

  Mellor, Andrew ^a,b,c   Haywood, Andrew ^b,c   Stone, Christine ^d   Jones, Simon ^a  

^a RMIT UNIVERSITY   (Australia)

^b Victorian Department of Sustainability and Environment   (Australia)

^c UNIVERSITY OF QUEENSLAND   (Australia)

^d NSW DEPARTMENT OF PRIMARY INDUSTRIES   (Australia)

Author keywords

Forest extent; Landsat TM; Large area monitoring; MODIS; Operational; Random forests

Indexed keywords

AREA MONITORING; FOREST EXTENT; LANDSAT TM; MODIS; OPERATIONAL; RANDOM FORESTS;

AERIAL PHOTOGRAPHY; LAND USE; LEARNING ALGORITHMS; NATURAL RESOURCES MANAGEMENT; SATELLITE IMAGERY;

DECISION TREES;

EID: 84880413388     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs5062838     Document Type: Article

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