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Remote Sensing and Environmental Treaties: Building More Effective Linkages
Remote Sensing Technologies for Ecosystem Management Treaties

This project was funded by the United States Department of State, Bureau of Oceans and International Environmental and Scientific Affairs initiatives program (OESI) and involved a collaboration among the following institutions:

In addition, the U.S. Fish and Wildlife Service’s International Division provided technical assistance. The project duration was two years (October 2003-September 2005).

Problem Addressed
The project focused on the utilization of satellite remote sensing data to improve the effectiveness of ecosystem-oriented multilateral environmental agreements (MEAs). These agreements include, among others, the Ramsar Convention on Wetlands of International Importance, the Convention on Biological Diversity, the World Heritage Convention, and UNESCO Biosphere Reserves. These conventions and site designations serve to protect natural resources and biodiversity of international importance, yet they are often constrained by lack of data and information to support implementation. The project tested applications of remote sensing for wetland delineation and conservation priority setting on a complex of wetlands on the Brazilian and Uruguayan sides of Laguna Merin, the second largest freshwater lake in South America (after Lake Titicaca). The region's biodiversity is threatened by expanding rice culture, agrochemical pollution, and plantation forests. Figures 1 and 2 (below) show the location of Laguna Merin in South America and Landsat thumbnail images of the lake, respectively.

Results
The project had three components. The first component involved a literature review and an inventory examining treaty-specific provisions with regards to ecosystem management, and developing a list of remote sensing instruments and applications that are relevant to those provisions. This includes an examination of treaty monitoring and reporting requirements that could be supported by remote sensing. The report developed for this component also includes discussion on the utilization of remote sensing for transboundary conservation. This report is available for download from the top of the table at right.

The second component was to develop a pilot application of remote sensing applied to two 40 square kilometer regions directly across from eachother on Laguna Merin: the area surrounding Rio Tacuari on the Uruguayan side of the lake, and the area surrounding Arroio del Rei on the Brazilian side. The pilot study involved remote sensing and two rounds of field work in March and October 2004. The final technical report for this component of the project is available in the "Laguna Merin Case Study" section of the table at right.

The third component was a user workshop in which the results of components one and two were presented. This workshop was held at IBAMA headquarters in Brasilia, Brazil, on July 14, 2005, in conjunction with the 2005 Annual Meeting of the Society for Conservation Biology. The workshop involved policy makers from the governments of Brazil and Uruguay as well as remote sensing experts and conservationists. A summary report on the Laguna Merin field study was distributed at this workshop, and a special session of the Society for Conservation Biology meeting on July 16. This summary report is available for download at right.

Landsat scenes (for 1984, 1986, 1987, 2000 and 2002) along with all field data and an associated shape file, are also available for download from the table at right.

 

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  Landsat thumbnail images of Laguna Merin
Figure 2. Landsat Image Mosaic of Laguna Merín, Southeastern Brazil and Northeastern Uruguay (22 April 2001)
global land cover 2000 map of South America with location of Laguna Merin  
Figure 1. (A) The Global Land Cover 2000 land cover classification for South America; and (B) An analysis utilizing the software Diversidad found that Laguna Merín showed up on the continental scale as having high levels of landscape diversity, which translates to high potential biodiversity.

 

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