摘要
We developed a global,30-m resolution dataset of percent tree cover by rescaling the 250-m MOderate-resolution Imaging Spectroradiometer(MODIS)Vegetation Continuous Fields(VCF)Tree Cover layer using circa-2000 and 2005 Landsat images,incorporating the MODIS Cropland Layer to improve accuracy in agricultural areas.Resulting Landsat-based estimates maintained consistency with the MODIS VCF in both epochs(RMSE=8.6%in 2000 and 11.9%in 2005),but showed improved accuracy in agricultural areas and increased discrimination of small forest patches.Against lidar measurements,the Landsat-based estimates exhibited accuracy slightly less than that of the MODIS VCF(RMSE=16.8%for MODIS-based vs.17.4%for Landsat-based estimates),but RMSE of Landsat estimates was 3.3 percentage points lower than that of the MODIS data in an agricultural region.The Landsat data retained the saturation artifact of the MODIS VCF at greater than or equal to 80%tree cover but showed greater potential for removal of errors through calibration to lidar,with post-calibration RMSE of 9.4%compared to 13.5%in MODIS estimates.Provided for free download at the Global Land Cover Facility(GLCF)website(www.landcover.org),the 30-m resolution GLCF tree cover dataset is the highest-resolution multi=temporal depiction of Earth’s tree cover available to the Earth science community.
基金
Work was performed in service of the Global Forest Cover Change Project(www.forestcover.org),a partnership of the University of Maryland Global Land Cover Facility(www.landcover.org)
NASA Goddard Space Flight Center,with funding from the NASA MEaSUREs program.Work was performed at the Global Land Cover Facility
The authors would like to thank especially the providers of datasets used in this project:Global Land Survey data were provided by Rachel Headley at the USGS Eros Data Center
MODIS Collection-5 VCF data were provided by Charlene DiMiceli in the University of Maryland Department of Geographical Sciences
Lidar data were provided by OpenTopography(www.opentopography.org)
by Bruce Cook at the NASA Goddard Space Flight Center and Paul Bolstad in the University of Minnesota Department of Forest Resouces with funding from NASA and the University of Minnesota Initiative for Renewable Energy and the Environment(IREE)
by James Kellner at the University of Maryland,and by R.Dubayah at the University of Maryland from work funded by the NASA Terrestrial Ecology Program.Lidar processing was done using the US Forest Service FUSION software,Version 3.21.Statistical analyses were conducted in R(R Core Team 2012)using the‘raster’package(Hijmans and Etten 2012)
Jeff Masek and Eric Vermote at the NASA Goddard Space Flight Center and Matthew Hansen and Amanda Whitehurst and Hao Tang at the University of Maryland Department of Geographical Sciences provided feedback and insights on algorithms and datasets.T.B.Murphy provided assistance with algorithm development.
