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Dive into the research topics where E. J. Deeb is active.

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Featured researches published by E. J. Deeb.


Journal of remote sensing | 2011

Monitoring snowpack evolution using interferometric synthetic aperture radar on the North Slope of Alaska, USA

E. J. Deeb; Richard R. Forster; Douglas L. Kane

This research investigates the use of Interferometric Synthetic Aperture Radar (InSAR) to generate a time-series of snow water equivalent (SWE) for dry snow within the Kuparuk watershed, North Slope, Alaska, during the winter of 1993/1994. Maps depicting relative change in phase and the theoretical relative change in SWE between satellite acquisitions are created for 3-day periods at the end of March 1994 using both ascending and descending ERS-1 overpasses. The theoretical coefficient relating relative change in phase and relative change in SWE for C-band is found to be at least twice as large as what is expected when using a simple single-layer snow model for this study area and time period. Without any direct measurements of SWE on the ground, station measurements of snow depth and hourly wind are linked to each 3-day relative change in phase map. Along with a qualitative assessment, quantitative measures of the rate and magnitude of phase change around these stations are directly compared to the hourly wind data for a given 3-day period. InSAR-derived maps acquired around a measured precipitation event show a considerable relationship to the predominant direction of strong winds over each 3-day period while maps acquired around no measureable precipitation depict much less correlation between phase change and predominant direction of strong winds. Despite limited ground measurements to infer snowpack conditions, these results show continued promise for the InSAR technique to measure changes in snowpack conditions (e.g. SWE) at much higher resolutions than manual sampling methods or passive microwave remote sensing. The extension of this technique to current L-band InSAR satellite platforms is also discussed.


IEEE Transactions on Geoscience and Remote Sensing | 2003

Measurement of glacier geophysical properties from InSAR wrapped phase

Richard R. Forster; Kenneth C. Jezek; Lora S. Koenig; E. J. Deeb

A method is presented for calculating longitudinal glacier strain rates directly from the wrapped phase of an interferometric synthetic aperture radar (InSAR) interferogram assuming the ice flow path is known. This technique enables strain rates to be calculated for scenes lacking any velocity control points or areas within a scene where the phase is not continuously unwrappable from a velocity control point. The contributions to the error in the estimate of the strain rate are evaluated, and recommendations for appropriate SAR and InSAR parameters are presented. An example using Radarsat-1 InSAR data of an East Antarctic ice stream demonstrates the technique for calculating longitudinal strain rate profiles and estimating tensile strength of ice (186-215 kPa) from locations of crevasse initiation. The strain rate error was found to be 17% corresponding to a tensile strength of ice error of 5.3%.


international geoscience and remote sensing symposium | 2017

Supporting NASA SnowEx remote sensing strategies and requirements for L-band interferometric snow depth and snow water equivalent estimation

E. J. Deeb; Hans-Peter Marshall; Richard R. Forster; Cathleen E. Jones; Christopher A. Hiemstra; Paul Siqueira

The objectives of this research are to (1) address remote sensing strategies and requirements for estimating snow depth and snow water equivalent (SWE) using existing L-Band interferometric data sets in coordination with field-based observations and modeling frameworks and, with this information, (2) inform the Next Generation Cold Land Processes Experiment (SnowEx) toward articulating the appropriate science and research questions for a single motivating science plan. As proposed, SnowEx is a multi-year airborne snow campaign with a primary goal of exploring multimodal sensor observations in coordination with field campaigns to inform the next generation snow remote sensing satellite platform. Based on limitations of satellite-based optical and LiDAR instruments operating in regions of the globe with consistent cloud-cover, the fact that many snow-dominated regions are at more northerly latitudes (limited solar illumination in the middle of winter), and these snow-dominated regions often experience periods of prolonged cloud cover (due to synoptic precipitation events), a microwave remote sensing platform may be the most viable path to space for a dedicated snow remote sensing mission. Specifically, L-Band radar interferometry has shown some unique promise with an archive of historical and contemporary satellite collections from JAXAs PALSAR-1 and PALSAR-2 instruments, respectively. Moreover, with the expected NISAR (NASA-ISRO Synthetic Aperture Radar) mission launch in 2020 and the unprecedented availability of dedicated global interferometric L-Band products every 12-days, as well as what is in essence a NISAR airborne simulator in JPLs UAVSAR platform, the L-Band interferometric approach to estimating snow depth and snow water equivalent (SWE) requires further investigation within the context of in-situ observations and modeling frameworks.


Archive | 2017

Changes in the albedo of the Pegasus and Phoenix Runways, 2000–2017

E. J. Deeb; Blaine F Morriss; Steven F. Daly; Robert Haehnel

Albedo is the ratio of total hemispherical reflected (upwelling) to incoming (downwelling) radiative flux (or irradiance) at a surface. For operations on the McMurdo Ice Shelf, Antarctica, albedo is a controlling factor. Impurities such as dust, soot, mineral, and other organic deposits on a snow or ice surface can dramatically lower albedo, increase solar energy absorption in the ice shelf, and significantly alter the energy balance, resulting in increased melting, snow density variations, and compromised structural integrity of the snow and ice matrix. The occurrence of such impurities at Pegasus Runway may have been a factor in its decline and replacement with the Phoenix Runway in the 2016–2017 field season. Therefore, the National Science Foundation (NSF) requested that the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) establish a longterm record of surface albedo at the Pegasus and Phoenix Runway sites. To accomplish this, data from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) satellite was used. MODIS satellite data has a daily temporal resolution and a significant period of record (2000–present). Additionally, its narrowband surface reflectance may be used as a proxy for albedo. This report documents the results of these analyses. ERDC/CRREL TR-17-10 iii


Hydrological Processes | 2012

Assessment of the snow conditions in the major watersheds of Afghanistan using multispectral and passive microwave remote sensing

Steven F. Daly; Carrie M. Vuyovich; E. J. Deeb; Stephen D. Newman; Timothy B. Baldwin; John J. Gagnon


Remote Sensing of Environment | 2016

Persistence-based temporal filtering for MODIS snow products

B.F. Morriss; E. Ochs; E. J. Deeb; Stephen D. Newman; Steven F. Daly; John J. Gagnon


Archive | 2010

Crevasse Detection and Avoidance for Safe Traversing on the Dynamic and Annually Changing Margin of the Greenland Ice Sheet

Jennifer Mercer; James H. Lever; Sharlene D. Newman; E. J. Deeb; Brian Tracy; Jason C Weale; Allan J. Delaney; Rowan Davies; K. S. Emery


Archive | 2018

Snow strategic science plan

Carrie M. Vuyovich; E. J. Deeb; Chris Polashenski; Zoe Courville; Christopher A. Hiemstra; Anna Wagner; John Eylander; Robert Davis


Remote Sensing of Environment | 2017

Effect of spatial variability of wet snow on modeled and observed microwave emissions

Carrie M. Vuyovich; Jennifer M. Jacobs; Christopher A. Hiemstra; E. J. Deeb


Remote Sensing of the Terrestrial Water Cycle | 2014

Passive Microwave Remote Sensing of Snowmelt and Melt‐Refreeze Using Diurnal Amplitude Variations

Kathryn Alese Semmens; J. M. Ramage; Jeremy D. Apgar; Katrina E. Bennett; Glen E. Liston; E. J. Deeb

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Carrie M. Vuyovich

Cold Regions Research and Engineering Laboratory

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Christopher A. Hiemstra

Cold Regions Research and Engineering Laboratory

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Stephen D. Newman

Cold Regions Research and Engineering Laboratory

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Steven F. Daly

Cold Regions Research and Engineering Laboratory

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D. C. Finnegan

Cold Regions Research and Engineering Laboratory

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John J. Gagnon

Cold Regions Research and Engineering Laboratory

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