This session is open to all presentations featuring novel remote sensing techniques or applications. All remote sensing technologies are welcome, including (but not limited to) multispectral, hyperspectral, thermal infrared, high resolution, drone/unmanned aerial systems, lidar, and synthetic aperture radar remote sensing.
The diversity and availability of remote sensing technologies used to measure and monitor the Earth continues to grow. A decades-long record of multispectral remote sensing allows quantification of change and mapping at regional-to-global scales, drones provide easily accessible imagery at very high spatial resolution, and rapidly evolving technologies like hyperspectral, lidar, and radar remote sensing have enabled retrieval of a new array of biogeophysical variables. This session features novel remote sensing, with respect to either the techniques being applied to remotely sensed data or to the remote sensing application.
|Presenter||Yunzhe Zhu*, Clark University, Lyndon Estes, Clark University, Using Deep Learning-based Super-Resolution to Improve Maps of Smallholder Crop Field Boundaries||15||3:05 PM|
|Presenter||Grayson Morgan*, , Determining a Confidence Interval for Repeat sUAS Imagery to Assess Vegetation Cover Change||15||3:20 PM|
|Presenter||Bo Yang*, Univerisity of Central Florida, Hawthorne Timothy, University of Central Florida, Accessing the spatial variation of seagrass beds along the west coast of North America using high-resolution UAV data||15||3:35 PM|
|Presenter||A H M Mainul Islam*, Graduate Student, Department of Geography, Kent State University, Timothy Assal, Assistant Professor, Department of Geography, Kent State University, Tracking Cyclonic Impact and Recovery Rate of Mangrove Forest using Remote Sensing: A Case Study of the Sundarbans, Bangladesh||15||3:50 PM|
|Presenter||He Yin*, Department of Geography, Kent State University, USA, Patrick Griffiths, European Space Agency (ESA), Directorate of EO Programmes, Science Applications & Climate Department, Italy, Patrick Hostert, Geography Department, Humboldt-Universität zu Berlin, Germany, Volker C. Radeloff, SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, USA, Mapping grassland use with Landsat and Sentinel-2 time series||15||4:05 PM|
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