2003 Progress Report: GIS and Terrestrial Remote SensingEPA Grant Number: R829458C007
Subproject: 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: Yang, Xiaojun
Institution: Florida State University , University of Southern Mississippi
Current Institution: University of Southern Mississippi
EPA Project Officer: Hiscock, Michael
Project Period: December 1, 2001 through November 30, 2005
Project Period Covered by this Report: December 1, 2002 through November 30, 2003
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Water , Ecosystems , Ecological Indicators/Assessment/Restoration
The focus of Year 1 of the project was on the construction of a comprehensive locationally based database. The objective for Year 2 of the project has shifted from database building into spatial data synthesis, analysis, and modeling for developing landscape-level indicators that can be used to quantify the anthropogenic impacts upon the estuarine ecosystems.
Progress has been achieved in three major areas. First, all of the spatial datasets initially created during the first year were refined and metadata were added to each dataset. Second, we used remote sensing and GIS-based spatial analysis and modeling technologies to analyze the relationship between landscape characteristics, socioeconomic attributes, and estuarine water quality with the Pensacola estuarine drainage area as a case. Last, we have participated in an intercenter collaborative research project aimed at understanding the relationship between geomorphology, landscape scale, and estuarine water quality at North Inlet estuary. Our research results were present at professional conferences and a number of manuscripts were submitted for publication in professional journals. The principal investigator also is editing a special journal focus issue on estuarine ecosystem analysis, which is scheduled to be published by early 2005.
The primary study site was the Pensacola estuarine drainage area as defined by the National Oceanic and Atmospheric Administration's Coastal Assessment Framework. The total estuarine drainage area for the Pensacola Bay is 9,119.63 km2, including 8,643.00 km2 of land area and 476.63 km2 of water area. This included counties within two states: Alabama and Florida.
Spatial Database Construction
During the first year, our overwhelming research efforts were on the construction of a locationally based database. A detailed list of the data layers within this database can be found in our first annual progress report. During the second year, we refined these datasets and added metadata to each data layer. This has been very tedious work and demanded a lot of research time. Last October, we submitted an updated list of the data layers to Peter Noble, the Consortium for Estuarine Ecoindicator Research for the Gulf Of Mexico (CEER-GOM) data manager.
Predicting Estuarine Water Quality With Landscape and Socioeconomic Metrics
We formally investigated the relationship between landscape characteristics, socioeconomic attributes, and estuarine water quality using the Pensacola Estuarine Drainage Area as a case study. We considered a range of landscape indicators as related to changing landscape structure and pattern extracted from a time series of remotely sensed imagery. We remodeled some selected socioeconomic attributes according to their natural distributions by using an areal interpolation approach. We created surfaces from point-based water quality data sampled by the U.S. Environmental Protection Agency's Gulf Ecology Division. We developed a GIS-based method to select hydrologically critical points within the stream network and create buffer rings around these points. Within these buffer rings, we computed a number of landscape and socioeconomic metrics and related them with water quality measures by using a stepwise multiple regression. We found that landscape and socioeconomic metrics can explain most of the water quality variability within the Pensacola Estuarine Drainage Area.
The North Inlet Joint Project
This intercenter collaborative project involves researchers (James Morris, Luoheng Han, and myself) from two Estuarine and Great Lakes (EaGLe) centers. The aim of this project is to investigate the relationship between geomorphology, landscape scale, and estuarine water quality at North Inlet estuary. This is actually scaling-related research. The research consists of the following components:
• Remotely sensed imagery is used to map tidal channels, classify marshes, and estimate water quality.
• Light Detection and Ranging (LIDAR) data are used to construct a high-resolution digital elevation model, which was used to conduct hydrological network modeling for the purpose of determining stream order and other relevant hydrographical features.
• GIS-based spatial analysis is used to determine the relationship between stream order, water quality, anthropogenic influences, and natural influences (the ratio of wetland area/open water) using different spatial observation units.
This project has been partly completed with ongoing effort focused on the last component.
Special Conference Paper Sessions
At the 2003 annual meeting of the Association of American Geographers (AAG), Luoheng Han and I organized a special conference paper session dedicated to the remote sensing and GIS research within the EaGLe programs. James Morris chaired this session, and researchers from three EaGLe centers presented their research findings within this session. We also organized a similar paper session at the 2004 annual meeting of the AAG. These sessions were sponsored by three specialty groups of AAG: Remote Sensing, GIS, and Coastal and Marine Environment.
Collaborations Within and Across Centers
• We provided GIS technical support to the CEER-GOM microbial biofilm component for handling water quality data with GIS.
• We worked together with Jim Morris from the Atlantic Coast Environmental Indicators Consortium in the investigation of the relationship between geomorphology, landscape scale, and estuarine water quality at North Inlet estuary. We have achieved some initial results.
• The principal investigator visited Susan Ustin's Remote Sensing Laboratory (Pacific Estuarine Ecosystem Indicator Research Consortium) during December 2003 when he attended the third EaGLe annual meeting in California.
We will continue to: (1) use remotely sensed imagery to map tidal channels, classify marshes, and estimate water quality; (2) use Light Detection and Ranging (LIDAR) data to construct a high-resolution digital elevation model, which was used to conduct hydrological network modeling for the purpose of determining stream order and other relevant hydrographical features; and (3) conduct GIS-based spatial analysis to determine the relationship between stream order, water quality, anthropogenic influences, and natural influences (the ratio of wetland area/open water) using different spatial observation units. In addition, the principal investigator has been working with the Editor-in-Chief of the International Journal of Remote Sensing (IJRS) in developing a special focus issue "Remote Sensing and GIS for Estuarine Ecosystem Analysis." As the guest editor for this issue, his is giving priority to submissions from the EaGLe centers. Submissions have been received from all five EaGLe centers. This issue is scheduled to be published by early 2005.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
|Other subproject views:||All 17 publications||8 publications in selected types||All 8 journal articles|
|Other center views:||All 171 publications||54 publications in selected types||All 48 journal articles|
||Yang X, Lo CP. Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. International Journal of Remote Sensing 2002;23(9):1775-1798||
||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.||
||Yang X, Liu Z. Use of remote sensing and landscape metrics to analyze estuarine landscape changing dynamics. International Journal of Remote Sensing .||
Supplemental Keywords:population, community, ecosystem, watersheds, estuary, estuaries, Gulf of Mexico, nutrients, hypoxia, innovative technology, biomarkers, water quality, remote sensing, geographic information system, GIS, integrated assessment, risk assessment, fisheries, conservation, restoration, monitoring/modeling, Apalachicola Bay, Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico, CEER-GOM, Environmental Monitoring and Assessment Program, Galveston Bay, Mobile Bay, Florida, FL, Alabama, AL, benthic indicators, ecoindicator, ecological exposure, ecosystem monitoring, environmental indicators, environmental stress, estuarine ecoindicator, estuarine integrity., RFA, Scientific Discipline, Geographic Area, Water, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, estuarine research, Aquatic Ecosystems & Estuarine Research, Ecosystem/Assessment/Indicators, Aquatic Ecosystem, Aquatic Ecosystems, Environmental Monitoring, Ecological Monitoring, Ecology and Ecosystems, Gulf of Mexico, Ecological Indicators, monitoring, ecoindicator, ecological exposure, remote sensing, estuaries, estuarine integrity, Mobile Bay, Galveston Bay, CEER-GOM, estuarine ecoindicator, environmental indicators, environmental stress, estuarine waters, restoration, water quality, GIS
Progress and Final Reports: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