Remote sensing excels as a means to measure, model, map, and monitor large-scale patterns of land cover change. With the steady deployment of satellite remote sensing platforms in recent decades, scientists now have access to a constellation of space-borne sensors. But with this increase in satellite imagery comes a specific challenge for the remote sensing community to efficiently process data streams from sensors with different spatial, spectral, temporal, and radiometric characteristics. This paper session elucidates automated approaches to the production of temporally consistent land cover time series that adapt to atmospheric, radiometric, and phenological inconsistencies among multi-temporal satellite images. Potential topics range from theory and algorithms to products and applications of automated time series mapping. If you wish to be included in this session register and submit your abstract through the AAG website by October 25, 2018, and send your personal identification number (PIN), paper title, abstract, and your abstract submission confirmation email to co-organizers: Christopher Hakkenberg (firstname.lastname@example.org) and Matthew Dannenberg (email@example.com) by November 1, 2018.
|Presenter||Jeffrey Cardille*, McGill University, Morgan A Crowley, McGill University, Xavier Giroux-Bougard, McGill University, Jacky Lee, McGill University, Multi-sensor data synthesis for land-use/land-cover time series with the Bayesian Updating of Land Cover (BULC) algorithm||20||9:55 AM|
|Presenter||Christopher Hakkenberg*, Rice University, Matthew Dannenberg, University of Iowa, Conghe Song, UNC-Chapel Hill, Automated prediction of subannual continuous fields impervious fractional cover dynamics||20||10:15 AM|
|Presenter||Xiaoyu Liang*, The Ohio State University, Desheng Liu, The Ohio State University, Detecting abrupt and long-term changes with Landsat Time Series||20||10:35 AM|
|Presenter||Mitchell T. Bonney*, University of Toronto - Mississauga, Yuhong He, University of Toronto - Mississauga, Understanding long-term changes in urban-rural forest communities using Landsat trajectories and hemispherical photography||20||10:55 AM|
|Presenter||Xiaopeng Song*, University of Maryland College Park, Matthew Hansen, University of Maryland, Stephen Stehman, SUNY College of Environmental Science and Forestry, Peter Potapov, University of Maryland, Alexandra Tyukavina, University of Maryland, Eric Vermote, NASA Goddard Space Flight Center, John Townshend, University of Maryland, Mapping global land cover change from 1982 to 2016||20||11:15 AM|
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