Monitoring global land cover with Landsat data

Matthew Hansen, University of Maryland College Park, mhansen@umd.edu (Presenter)

The ‘Blue Marble’ photograph of Earth, taken by the Apollo 17 crew in 1972, depicted the illuminated Earth in the black void of space, inspiring many to recognize our shared global environment. In the same year, the first earth observation satellite, Landsat 1, was launched. A series of Landsat missions have followed. However, a number of factors - from computing limitations to insufficient acquisitions - precluded global land cover characterization. In the 1990’s, the quantification of global land cover from space was prototyped; initial products were experimental and focused on land cover as a static set of themes, initially depicted at one degree spatial resolution using meteorological AVHRR imagery. With the launch of MODIS, spectral bands specifically designed for land monitoring led to operational categorical cover classifications and percent cover characterizations. Similar capabilities were developed using Vegetation and MERIS data for global land classification. Follow-on missions such as the VIIRS and PROBA-V sensors will continue the global scale coarse resolution mapping and monitoring of the land surface. However, despite an over 40 year history, it was only recently that conditions were met to map global land change using Landsat data. Cloud computing, advanced algorithms and progressive data policies together have made possible the efficient processing and characterization of the Landsat data record. Landsat data, with a spatial resolution of 30m, represent a significant advance in quantifying land change, as 30m is a scale finer than most human-induced land change. Global 30m land cover extent and change characterizations capture land surface dynamics at landscape granularity, enabling consistent global-scale overviews with local-scale relevancy. Similar to antecedent coarse resolution efforts, the first Landsat-based products were classifications and percent cover maps. Concerning change detection, forests have been the primary thematic target, due to the impacts of disturbance to key ecological services, but also due to the relative ease in which they are mapped using satellite data. Next steps using Landsat data include moving into additional themes at the global scale, with examples for water, agriculture, and urbanization illustrated. Future capabilities will employ Landsat with Sentinel data and possibly very high spatial resolution commercial imagery such as RapidEye and PlanetLabs. Other spaceborne radar and lidar data sources offer novel and improved land characterization at the global scale.

Presentation Type:  Plenary Talk

Session:  Theme 1: Tracking habitat change through new integrative approaches and products

Presentation Time:  Mon 10:48 AM  (18 minutes)