Mapping forest canopy height across large areas by upscaling ALS estimates with freely available satellite data

Remote Sensing

Volumn 7, Issue 9, 2015, Pages 12563-12587

  Wilkes, Phil ^a,b,c   Jones, Simon D ^a,c   Suarez, Lola ^a,c   Mellor, Andrew ^a,d,e   Woodgate, William ^a,c   Soto Berelov, Mariela ^a,c   Haywood, Andrew ^c,f   Skidmore, Andrew K ^b  

^a RMIT UNIVERSITY   (Australia)

^b UNIVERSITY OF TWENTE   (Netherlands)

^c Andrew Haywood is with the Cooperative Research Centre for Spatial Information   (Australia)

^d DEPARTMENT OF ENVIRONMENT   (Australia)

^e UNIVERSITY OF QUEENSLAND   (Australia)

^f FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS   (Italy)

Author keywords

ALS; Canopy height; Landsat; Large area assessment; Open source; Random forest

Indexed keywords

ALUMINUM; DECISION TREES; ERRORS; FORESTRY; IMAGE RECONSTRUCTION; MEAN SQUARE ERROR; RADIOMETERS; SCALABILITY;

CANOPY HEIGHTS; LANDSAT; LARGE AREA ASSESSMENT; OPEN SOURCES; RANDOM FORESTS;

VEGETATION;

EID: 84942515767     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs70912563     Document Type: Article

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