2004 Progress Report: Remote Sensing of Water QualityEPA Grant Number: R829458C001
Subproject: this is subproject number 001 , 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: Remote Sensing of Water Quality
Investigators: Han, Luoheng
Institution: The University of Alabama
Current Institution: The University of Alabama , University of Southern Mississippi
EPA Project Officer: Packard, Benjamin H
Project Period: December 1, 2001 through November 30, 2005 (Extended to May 20, 2007)
Project Period Covered by this Report: December 1, 2003 through November 30, 2004
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Water , Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration
The objectives of the remote sensing component of the Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico (CEER-GOM) are: (1) continuing the hyperspectral characterization of the Gulf of Mexico; (2) comparing regression (band ratioing) and artificial neural networks (ANN) models in estimating and mapping chlorophyll concentration using Landsat Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+) Data; and (3) mapping the sea surface temperature using Landsat TM/ETM+ data.
Field Data Collection
On July 6, 2004, hyperspectral data were collected from 15 sampling sites in the Pensacola Bay. On July 27, 2004, hyperspectral data were collected from 14 sampling sites in the Mobile Bay. On October 30, 2004, no data in the Mobile Bay were collected because of mechanical problems with the boat.
Hyperspectral Characterization. Spectral reflectances collected over Pensacola Bay and Mobile Bay in July 2004 clearly indicate the differences in water quality between the two systems (Figure 1). Relatively less peak-and-trough curves for Pensacola Bay reveals that the chlorophyll concentration is low in almost all U.S. Environmental Protection Agency Gulf Ecology Division sampling sites. In comparison, the spectral curves of Mobile Bay indicate much higher chlorophyll concentration and dissolved organic matter.
Regression Versus ANN Models. Regression analysis is the long-established method for creating models of water quality. Statistical results may not be as strong as those of the ANN, but this method is still a valid procedure to employ for predicting chlorophyll a concentrations in estuarine environments. Additionally, during periods of low chlorophyll a concentration, ANN provides a useful alternative to predict phytoplankton distribution.
Figure 1. Hypersperctral Data Collected July 2004 in Pensacola Bay and Mobile Bay
Sea Surface Temperature (SST) Mapping Using TM Band 6. An operational model was created for retrieving SST with delineation of water body. A well-developed algorithm was applied to calculated SST using Landsat TM band 6 (thermal band).
Figure 2. Results of SST Mapping Using Landsat Tm Band 6
Journal Articles on this Report : 2 Displayed | Download in RIS Format
|Other subproject views:||All 8 publications||2 publications in selected types||All 2 journal articles|
|Other center views:||All 171 publications||54 publications in selected types||All 48 journal articles|
|| Han LH, Jordan KJ. Estimating and mapping chlorophyll-a concentration in Pensacola Bay, Florida using Landsat ETM+ data. International Journal of Remote Sensing 2005;26(23):5245-5254.
|| Han LH. Estimating chlorophyll-a concentration using first-derivative spectra in coastal water. International Journal of Remote Sensing 2005;26(23):5235-5244
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, benthic indicators, ecological exposure, ecosystem monitoring, environmental indicators, environmental stress, estuarine ecoindicator, estuarine integrity,, RFA, Scientific Discipline, ECOSYSTEMS, Geographic Area, Water, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, Ecology, estuarine research, Ecosystem/Assessment/Indicators, Ecosystem Protection, 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, Apalachicola Bay, estuarine ecoindicator, environmental indicators, environmental stress, estuarine waters, restoration, water quality
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