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2005 Progress Report: GIS and Terrestrial Remote Sensing
EPA Grant Number: R829458C007Subproject: this is subproject number 007 , established and managed by the Center Director under grant R829458
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: EAGLES - Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico
Center Director: Brouwer, Marius
Title: GIS and Terrestrial Remote Sensing
Investigators: Han, Xiaojun
Institution: University of Southern Mississippi
EPA Project Officer: Levinson, Barbara
Project Period: December 1, 2001 through November 30, 2005
Project Period Covered by this Report: December 1, 2004 through November 30, 2005
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000)
Research Category: Ecological Indicators/Assessment/Restoration
Description:
Progress Summary:During this reporting period, we conducted research on non-point source pollution modeling. This includes a pilot study in a small watershed and an extended study considering the entire Pensacola estuarine watershed. The aim was to simulate the generation and transport of pollutants in overland flow to waterways (and finally the receiving basin) by using the Agricultural Non-point Source Pollution Model (AGNPS). The pilot study was undertaken for a complete sub-basin (610 km2 in size) within the Pensacola estuarine watershed. This model has three major output products: runoff, erosion, and total nitrogen . We validated the model with real measurements dated on September 25, 2002. We also tested the model performance at four different levels of spatial resolution, namely, 45 m, 60 m, 75 m, 90 m, and 105 m. This part of work has been very computationally intensive (30 m does not work; program crashed). We also considered different rainfall conditions—return periods (5, 10, 50 years). The pilot work was quite successful. Starting from late 2005, we have been extending the geographic dimension of non-point source pollution modeling into the entire Pensacola estuarine drainage area while considering several different watershed management scenarios. We also investigate the scale impacts upon non-point pollution modeling through the simulations undertaken at different levels of spatial resolution. This involves the use of a land cover transition model being loosely coupled with the AGNPS . We reported our preliminary work on non-point source pollution at the 102nd Annual Meeting of the Association of American Geographers on March 11, 2006, Chicago.
The special International Journal of Remote Sensing (IJRS) edition (see below) highlights the remote sensing and GIS research primarily conducted by investigators from the U.S. Environmental Protection Agency (EPA) Estuarine and Great Lakes (EaGLe) Research Program. Investigators from four major EaGLe centers and EPA headquarter have contributed to this issue. All papers collected in this issue were peer-reviewed using the established procedures and criteria by IJRS. IJRS is a leading international journal in remote sensing.
Journal Articles on this Report: 5 Displayed | Download in RIS Format
| Other subproject views: | All 17 publications | 8 publications in selected types | All 8 journal articles |
| Other center views: | All 161 publications | 48 publications in selected types | All 44 journal articles |
| Type | Citation | ||
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Yang X, Liu Z. Quantifying landscape pattern and its change in an estuarine watershed using satellite imagery and landscape metrics. International Journal of Remote Sensing 2005;26(23):5297-5323. |
R829458C007 (2004) R829458C007 (2005) |
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Yang XJ. Remote sensing and GIS applications for estuarine ecosystem analysis:an overview. International Journal of Remote Sensing 2005;26(23):5347-5356. |
R829458C007 (2004) R829458C007 (2005) |
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Yang X. Estimating landscape imperviousness with remotely sensed imagery. IEEE Geoscience and Remote Sensing Letters 2006;3(1):6-9. |
R829458C007 (2004) R829458C007 (2005) |
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Yang X, Liu Z. Use of satellite-derived landscape imperviousness index to characterize urban spatial growth. Computers, Environment and Urban Systems 2005; 29(5):524-540. |
R829458C007 (2003) R829458C007 (2004) R829458C007 (2005) |
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Yang X, Liu Z. Using satellite imagery and GIS for land-use and land-cover change mapping in an estuarine watershed. International Journal of Remote Sensing 2005;26(23):5275-5296. |
R829458C007 (2005) |
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Ecosystem Protection/Environmental Exposure & Risk, Water, Geographic Area, Scientific Discipline, RFA, ECOSYSTEMS, Ecosystem/Assessment/Indicators, Gulf of Mexico, estuarine research, Aquatic Ecosystems & Estuarine Research, Ecological Monitoring, Aquatic Ecosystem, Ecological Indicators, Aquatic Ecosystems, Ecology and Ecosystems, Environmental Monitoring, water quality, remote sensing, environmental indicators, ecoindicator, monitoring, Environmental Monitoring and Assessment Program, GIS, estuarine integrity, estuarine ecoindicator, ecological exposure, environmental stress, CEER-GOM, Galveston Bay, estuaries, restoration, Mobile Bay
Relevant Websites:
http://www.usm.edu/gcrl/ceer_gom/
Progress and Final Reports:
2002 Progress Report
2003 Progress Report
2004 Progress Report
Original Abstract
Main Center Abstract and Reports:
R829458 EAGLES - Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico
Subprojects under this Center:
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R829458C001 Remote Sensing of Water Quality
R829458C002 Microbial Biofilms as Indicators of Estuarine Ecosystem Condition
R829458C003 Individual Level Indicators: Molecular Indicators of Dissolved Oxygen Stress in Crustaceans
R829458C004 Data Management and Analysis
R829458C005 Individual Level Indicators: Reproductive Function in Estuarine Fishes
R829458C006 Collaborative Efforts Between CEER-GOM and U.S. Environmental Protection Agency (EPA)-Gulf Ecology Division (GED)
R829458C007 GIS and Terrestrial Remote Sensing
R829458C008 Macrobenthic Process Indicators of Estuarine Condition for the Northern Gulf of Mexico
R829458C009 Modeling and Integration