Environmental Research Letters · 2008 · 420 citations · 41 references
Natural SciencesEarth SciencesGeographyClimatologyRemote SensingTerrestrial EcologyBiomass EstimationBiomass Resource AssessmentLand Surface MonitoringLidar Remote SensingSatellite Image InterpretationVegetation MonitoringAbove-ground Biomass EstimationAboveground Biomass MappingCross-validationField MeasurementsLaser AltimetryRemote Sensing Biomass EstimationSatellite-based Biomass EstimationSatellite-based Biomass Mapping
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000–2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha−1 for a range of biomass between 0 and 454 Mg ha−1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.
41
Leo Breiman · Machine Learning · 2001 · 126.2K citations · Full text
Classification and Regression Trees.
Alexander Gordon, Leo Breiman, Jerome H. Friedman et al. · Biometrics · 1984 · 23.9K citations
Classification and Regression Trees.
John Van Ryzin, Leo Breiman, Jerome H. Friedman et al. · Journal of the American Statistical Association · 1986 · 21K citations
Classification and regression trees
J. Praagman · European Journal of Operational Research · 1985 · 10.2K citations