From MFKP_wiki

Jump to: navigation, search

Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error

Joseph O. Sexton, Xiao-Peng Song, Min Feng, Praveen Noojipady, Anupam Anand, Chengquan Huang, Do-Hyung Kim, Kathrine M. Collins, Saurabh Channan, Charlene DiMiceli, John R. Townshend

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 (, 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.

International Journal of Digital Earth, Vol. 6, No. 5. (21 September 2013), pp. 427-448, 
Key: INRMM:12286079



Article-Level Metrics (Altmetrics)
Digital Object Identifier

Available versions (may include free-access full text)

DOI, Taylor and Francis Online, Pubget, PubMed (Search)

Versions of the publication are also available in Google Scholar.
Google Scholar code: GScluster:690855862807956542

Works citing this publication (including grey literature)

An updated list of who cited this publication is available in Google Scholar.
Google Scholar code: GScites:690855862807956542

Further search for available versions

Search in ResearchGate (or try with a fuzzier search in ResearchGate)
Search in Mendeley (or try with a fuzzier search in Mendeley)

Publication metadata

Bibtex, RIS, RSS/XML feed, Json, Dublin Core
Metadata search: CrossRef DOI, DataCite DOI

Digital preservation of this INRMM-MiD record

Internet Archive

Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
Search only within the INRMM-MiD publication records:
Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.