Geospatial Technology/Traditional Ecological Knowledge-Derived Information Tools for the Enhancement of Coastal Restoration Decision Support Processes
This research investigated the feasibility and benefits of integrating geospatial technology with traditional ecological knowledge (TEK) of an indigenous Louisiana coastal population in order to assess the impacts of current and historical ecosystem change to community viability. The primary goal wa...
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| Format: | Others |
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ScholarWorks@UNO
2010
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| Online Access: | http://scholarworks.uno.edu/td/1228 http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=2211&context=td |
| Summary: | This research investigated the feasibility and benefits of integrating geospatial technology with traditional ecological knowledge (TEK) of an indigenous Louisiana coastal population in order to assess the impacts of current and historical ecosystem change to community viability. The primary goal was to provide resource managers with a comprehensive method of assessing localized ecological change in the Gulf Coast region that can benefit community sustainability. Using Remote Sensing (RS), Geographic Information Systems (GIS), and other geospatial technologies integrated with a coastal community's TEK to achieve this goal, the objectives were (1) to determine a method for producing vulnerability/sustainability mapping products for an ecosystem-dependent livelihood base of a coastal population that results from physical information derived from RS imagery and supported, refined, and prioritized with TEK, and (2) to demonstrate how such an approach can engage affected community residents who are interested in understanding better marsh health and ways that marsh health can be recognized, and the causes of declining marsh determined and addressed. TEK relevant to the project objectives collected included: changes in the flora and fauna over time; changes in environmental conditions observed over time such as land loss; a history of man-made structures and impacts to the area; as well as priority areas of particular community significance or concern. Scientific field data collection measured marsh vegetation health characteristics. These data were analyzed for correlation with satellite image data acquired concurrently with field data collection. Resulting regression equations were applied to the image data to produce estimated marsh health maps. Historical image datasets of the study area were acquired to understand evolution of land change to current conditions and project future vulnerability. Image processing procedures were developed and applied to produce maps that detail land change in the study area at time intervals from 1968 to 2009. This information was combined with the TEK and scientific datasets in a GIS to produce mapping products that provide new information to the coastal restoration decision making process. This information includes: 1) what marsh areas are most vulnerable; and 2) what areas are most significant to the sustainability of the community. |
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