Colin Doyle
University of Texas at Austin
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Journal of remote sensing | 2017
Jessica Fayne; John D. Bolten; Colin Doyle; Sven Fuhrmann; Matthew T. Rice; Paul R. Houser; Venkat Lakshmi
ABSTRACT In flat homogenous terrain such as in Cambodia and Vietnam, the monsoon season brings significant and consistent flooding between May and November. To monitor flooding in the Lower Mekong region, the near real-time NASA Flood Extent Product (NASA-FEP) was developed using seasonal normalized difference vegetation index (NDVI) differences from the 250 m resolution Moderate Resolution Imaging Spectroradiometer (MODIS) sensor compared to daily observations. The use of a percentage change interval classification relating to various stages of flooding reduces might be confusing to viewers or potential users, and therefore reducing the product usage. To increase the product usability through simplification, the classification intervals were compared with other commonly used change detection schemes to identify the change classification scheme that best delineates flooded areas. The percentage change method used in the NASA-FEP proved to be helpful in delineating flood boundaries compared to other change detection methods. The results of the accuracy assessments indicate that the −75% NDVI change interval can be reclassified to a descriptive ‘flood’ classification. A binary system was used to simplify the interpretation of the NASA-FEP by removing extraneous information from lower interval change classes.
Archive | 2017
Aakash Ahamed; John D. Bolten; Colin Doyle; Jessica Fayne
Flood detection through satellite remote sensing is a well-established practice (Brakenridge and Anderson 2006; Nigro et al. 2014) and has the potential to significantly enhance flood early warning and response systems (Brakenridge and Anderson 2003). Flood extent can be determined from optical sensors like Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS; Brakenridge and Anderson 2006), radar sensors like Sentinel, and land surface hydrologic routing models. Optical imagery can be obtained frequently at high to very high resolution. Radar sensors are sensitive to water and can penetrate through cloud cover at high resolution. Land surface models are used for hydrologic routing simulations of microwave radar precipitation data to determine flood depth and inundation extent (Brakenridge and Anderson 2006).
Quaternary International | 2018
Timothy Beach; Austin Ulmer; Duncan Cook; Michael L. Brennan; Sheryl Luzzadder-Beach; Colin Doyle; Sara Eshleman; Samantha Krause; Marisol Cortes-Rincon; Richard E. Terry
Geomorphology | 2017
Timothy Beach; Sheryl Luzzadder-Beach; Duncan Cook; Samantha Krause; Colin Doyle; Sara Eshleman; Greta Wells; Nicholas P. Dunning; Michael L. Brennan; Nicholas Brokaw; Marisol Cortes-Rincon; Gail Hammond; Richard E. Terry; Debora Trein; Sheila Ward
Quaternary International | 2018
Samantha Krause; Timothy Beach; Sheryl Luzzadder-Beach; Thomas H. Guderjan; Fred Valdez; Sara Eshleman; Colin Doyle; Steven Bozarth
Geomorphology | 2018
Samantha Krause; Timothy Beach; Sheryl Luzzadder-Beach; Duncan Cook; Gerald Islebe; Manuel R. Palacios-Fest; Sara Eshleman; Colin Doyle; Thomas H. Guderjan
The 81st Annual Meeting of the Society for American Archaeology | 2017
Timothy Beach; Sheryl Luzzadder-Beach; Colin Doyle; Nicholas P. Dunning; Nick Brokaw
The 81st Annual Meeting of the Society for American Archaeology | 2017
Samantha Krause; Timothy Beach; Sheryl Luzzadder-Beach; Thomas H. Guderjan; Colin Doyle
GSA Annual Meeting in Seattle, Washington, USA - 2017 | 2017
Samantha Krause; Timothy Beach; Sheryl Luzzadder-Beach; Colin Doyle; Thomas H. Guderjan; Lara Sanchez Morales
Archive | 2016
Aakash Ahamed; John D. Bolten; Colin Doyle; Jessica Fayne