Global Long-Term Multi-Sensor Web-Enabled Landsat Data Record

Principal Investigator:

Matthew Hansen

CO Investigators:

Peter Potapov

Sponsor:

Time period:

2013

2018

Researchers:

Alexander Krylov

Marc Steininger

Project Description:

This project supports the use of WELD data, specifically in the generation and validation of global land cover datasets, including percent tree, percent barren, percent water, and percent other vegetation. This procedure requires the creation of WELD-derived multi-spectral and multi-temporal features and training data to calibrate the land cover mapping algorithms. We will have considerable training data (derived from 1-4m very high spatial resolution imagery) for producing WELD land cover products, but will add to our very high spatial resolution data base, in particular for validation purposes. This sub-award will be coordinated existing global land cover investigations, currently funded through Year 2 of the proposed WELD activity. Specifically, current work supported by USGS and the Moore Foundation will be used to prototype methods for global land cover characterization using Landsat data, to be ready for implementation when global WELD data sets come online.

Related Publications:

Egorov, A.V., Roy, D.P., Zhang, H.K., Hansen, M.C., Kommareddy, A. (2018) Demonstration of Percent Tree Cover Mapping Using Landsat Analysis Ready Data (ARD) and Sensitivity with Respect to Landsat ARD Processing Level. Remote Sensing, 10(2), 209.

Egorov, A. V., Hansen, M. C., Roy, D. P., Kommareddy, A., & Potapov, P. V. (2015). Image interpretation-guided supervised classification using nested segmentation. Remote Sensing of Environment, 165, 135-147.

Roy, D.P., Qin, Y., Kovalskyy, V., Vermote, E.F., Ju, J., Egorov, A., Hansen, M.C., Kommareddy, I., and Yan, L. (2014) Conterminous United States demonstration and characterization of MODIS-based Landsat ETM + atmospheric correction., Remote Sensing of Environment, 140, 433-449.

Hansen M.C., Egorov A., Potapov P. V., Stehman S. V., Tyukavina A., Turubanova S. A., Roy D. P., Goetz S. J., Loveland T. R., Ju J., Kommareddy A., Forsythe C., Bents T. (2014) Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD), Remote Sensing of Environment, 140, 466-484.

Hansen, M.C., Egorov, A., Roy, D.P., Potapov, P., Ju, J., Turubanova, S., Kommareddy, I., and Loveland, T.R. (2011) Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project, Remote Sensing Letters, 2, 279-288.

Roy, D.P., Junchang, J., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M., Loveland, T.R., Vermote, E., and Zhang, C. (2009) Web-enabled Landsat data (WELD): Landsat ETM+ composited mosaics of the conterminous United States, Remote Sensing of Environment, 114, 35-49.

GLAD