Predicting forest successional stages using multitemporal Landsat imagery with forest inventory and analysis data

International Journal of Remote Sensing

Volumn 29, Issue 13, 2008, Pages 3855-3872

  Liu, W ^a   Song, C ^b   Schroeder, T A ^c   Cohen, W B ^d  

^a UNIVERSITY OF TOLEDO   (United States)

^b University of North Carolina at Chapel Hill   (United States)

^c OREGON STATE UNIVERSITY   (United States)

^d PACIFIC NORTHWEST RESEARCH STATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; ECOSYSTEMS; FORECASTING; IMAGE ANALYSIS; IMAGE ENHANCEMENT;

DECISION TREES (DTS); FOREST INVENTORY AND ANALYSIS; FOREST SUCCESSIONAL STAGES; LANDSAT THEMATIC MAPPER; NEURAL NETWORKS (NNS); REASONABLE ACCURACY; REMOTELY SENSED IMAGERY; TERRESTRIAL ECOSYSTEMS;

FORESTRY;

ARTIFICIAL NEURAL NETWORK; FOREST INVENTORY; LANDSAT THEMATIC MAPPER; NUMERICAL MODEL; REGRESSION ANALYSIS; SATELLITE IMAGERY; SUCCESSION;

ARTIFICIAL INTELLIGENCE; DATA STORAGE; DECISION MAKING; DECISION THEORY; ECOSYSTEMS; FOOD; FORECASTS; FORESTRY; GEOCHEMISTRY; NEURAL NETWORKS; PROCESSING; REGRESSION ANALYSIS;

EID: 46349085950     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160701840166     Document Type: Article

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