Authors: Michelle Bouchard*, South Dakota State University
Topics: Land Use and Land Cover Change
Keywords: Land Cover Change, LCMAP, Landsat, time series, CCDC, conterminous United States, mapping, land cover
Session Type: Virtual Guided Poster
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 53
Presentation File: No File Uploaded
Recent technological advances in computing and the increased availability of consistently calibrated remote sensing data have led to notable improvements in land change science. The U.S. Geological Survey’s (USGS) Land Change Monitoring, Assessment, and Projection (LCMAP) initiative implements a new approach to mapping and monitoring national land cover by applying time series modeling to Landsat Analysis Ready Data. LCMAP can provide solutions to scientists and land resource manager who need consistent data and land cover products spanning large geographic extents, over extended time periods, and at a higher frequency than in the past. The LCMAP implementation of the Continuous Change Detection and Classification (CCDC) algorithm uses all clear Landsat observations to develop harmonic time series models. Observations that diverge from these harmonic model predictions are identified as a change. This time series approach enables the monitoring of annual land cover class conversions and detection of disturbances, including more subtle conditional landscape changes, while also mitigating typical challenges associated with land cover mapping efforts such as cloud cover or phenological cycles. Attributes of these time series models are used to produce a suite of ten annual land cover and land surface change products for a 35-year record (1985 through 2019) across the conterminous United States. This poster will describe the LCMAP Collection 1 science products, show examples of their use, and how to access the data.