JpGU-AGU Joint Meeting 2017

Presentation information

[EJ] Oral

A (Atmospheric and Hydrospheric Sciences) » A-HW Hydrology & Water Environment

[A-HW34] [EJ] Hydrological Cycle and Water Environment

Mon. May 22, 2017 1:45 PM - 3:15 PM 201A (International Conference Hall 2F)

convener:Takeshi Hayashi(Faculty of Education and Human Studies, Akita University), Maksym Gusyev(International Centre for Water Hazard Risk Management, Public Works Research Institute), Seiya Nagao(Institute of Nature and Environmental Technology, Kanazawa University), Isao Machida(Geological Survey of Japan), Shin'ichi Iida(Department of Disaster Prevention, Meteorology and Hydrology, Forestry and Forest Products Research Institute), Chairperson:Takeshi Hayashi(Faculty of Education and Human Studies, Akita University), Chairperson:Shin'ichi Iida(Forestry and Forest Products Research Institute), Chairperson:Isao Machida(Geological Survey of Japan, AIST), Chairperson:Seiya Nagao(Institute of Nature and Environmental Technology, Kanazawa University), Chairperson:Maksym Gusyev(International Centre for Water Hazard Risk Management, Public Works Research Institute)

2:15 PM - 2:30 PM

[AHW34-14] Monitoring wetland inundation dynamics from space using a fully automated multi-sensor mapping approach

*Ben DeVries1, Wenli Huang1, Chengquan Huang1, Megan Lang2, John W. Jones3, Irena Creed4, Mark Carroll5,6 (1.University of Maryland, College Park, MD, USA, 2.US Fish and Wildlife Service, National Wetlands Inventory, Falls Church, VA, USA, 3.US Geological Survey, Eastern Geographic Science Center, Reston, VA, USA, 4.Department of Biology, University of Western Ontario, London, ON, Canada, 5.Biospheric Sciences Lab, NASA Goddard Space Flight Center, Greenbelt, MD, USA, 6.Science Systems and Applications, Inc., Lanham, MD, USA)

Keywords:Landsat, Sentinel, inundation, surface water, wetlands

Surface water inundation drives myriad important wetland functions, including water storage, carbon sequestration, nutrient removal, and biodiversity. Reliable information on wetland inundation dynamics is often lacking, leading to large uncertainties when studying these functions. A number of regional to global-scale surface water products have been released in recent years using a variety of satellite data sources. However, their utility is limited due to their relatively coarse spatial and temporal resolution. The fusion of optical and synthetic aperture radar (SAR) data streams has been put forward as a way to enhance temporal resolution and leverage the inherent benefits of these two disparate data types. Harmonized methods are needed to achieve enhanced temporal resolution through the generation of consistent wetland inundation estimates. Here, we present novel algorithms for the automated mapping of inundation, making use of optical (Landsat and Sentinel-2) and SAR (Sentinel-1) data streams. Using a combination of static thresholds, spatial aggregation, inundation probability from time series imagery and random forest classifiers, these algorithms are shown to be efficient in deriving inundated surfaces from optical and SAR imagery without the use of externally derived training data. While both algorithms are highly scalable in both space and time, several key limitations will need to be addressed before generating regional dynamic inundation products, including: insufficient frequency of satellite overpasses; commission errors from dark surfaces in optical imagery; and challenges in quantifying sub-pixel inundated extent from SAR imagery, which is necessary to ensure consistency between data streams. Addressing these issues will allow for the generation of near-daily estimates of wetland inundation at the continental to global scale, representing a significant step forward in understanding wetland ecosystems in support of relevant policies and management strategies.

The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the U.S. Government.