Multi-Source Imaging of Time-Serial Tree and Water Cover at Continental to Global Scales

Start Date:

07/01/2015

End Date:

07/06/2019

Grant Number:

ROSES-2014 NNH14ZDA001N-LCLUC

No Cost Extension:

Yes

Project Call:

Multi-Source Land Imaging (MuSLI)

Science Theme:

Multi-Source Land Imaging (MuSLI)

Detection and Monitoring of LCLUC

Observations and Data

Region:

Global

Solicitation:

NNH14ZDA001N-LCLUC

Team members:

Person Name	Person role on project	Affiliation
John Townshend	Principal Investigator	University of Maryland, College Park, College Park, United States
Joseph Sexton	Co-Investigator	University of Maryland, College Park, US
Min Feng	Co-Investigator	University of Maryland, College Park, US
Saurabh Channan	Co-Investigator	University of Maryland, College Park, US
Christiane Schmullius	Collaborator	University of Maryland, College Park, Jena, Germany
Mona Williams	Other	University of Maryland, College Park, US

Abstract:

We propose to develop a seamless and consistent, moderate - (i.e., sub - hectare) resolution database of percent - tree and water cover on a global, epoch al basis in 2000, 2005, and 2010 and continentally at annual frequency from 2010 to 2015. Globally, we will refine our existing Landsat - based maps of tree and water cover in 2000 and 2005, and we will extend these data with a global layer for 2010. Further , we will estimate tree and water cover annually from 2010 to 2015 across North and South America. All estimates will be accompanied by per - pixel estimates of uncertainty. To do so, we will generalize our proven multi - source fusion algorithms and apply the m to a combination of Landsat, ALOS - PALSAR, Sentinel - 2, and other data sources. This research will be partnered with the ESA - funded GLOBBIOMASS project (C. Schmullius, PI), which will map biomass regionally and globally in 2000, 2005, and 2010 epochs based on our maps of tree cover.

Project Products:

Global 30m Landsat Tree Canopy Version 4

Project Documents

Year	Authors	Type	Title
2015	Min Feng Joseph Sexton Saurabh Channan John Townshend	Publications	Feng, M., Sexton, J. O., Channan, S., & Townshend, J. R. (2016). A global, high-resolution (30-m) inland water body dataset for 2000: First results of a topographic–spectral classification algorithm. International Journal of Digital Earth, 9(2), 113-133.

Data Access

Title	Download Link
Global 30m Landsat Tree Canopy Version 4	https://e4ftl01.cr.usgs.gov/MEASURES/GFCC30TC.003/