{"refrec":{"BRefID":30815,"RR":"<b>Dahdouh-Guebas, F.</b> (2002). The use of remote sensing and GIS in the sustainable management of tropical coastal ecosystems. <i>Environ. Dev. Sustain. 4(2)</i>: 93-112. <a href=\"https://dx.doi.org/10.1023/A:1020887204285\" target=\"_blank\">https://dx.doi.org/10.1023/A:1020887204285</a>","BEntID":30815,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Environ. Dev. Sustain. 4(2)</i>: 93-112. <a href=\"https://dx.doi.org/10.1023/A:1020887204285\" target=\"_blank\">https://dx.doi.org/10.1023/A:1020887204285</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":1,"TerrestrialFlag":0,"Authorstring":"Dahdouh-Guebas, F.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Dahdouh-Guebas, F.","Englishabstract":"The sustainable use and management of important tropical coastal ecosystems (mangrove forests, seagrass beds and coral reefs) cannot be done without understanding the direct and indirect impacts of man. The ecosystem’s resilience and recovery capacity following such impacts must be determined. The efficacy of mitigation measures must also be considered. Remote sensing and geographic information systems (GIS) are excellent tools to use in such studies. This paper reviews the state of the art and application of these tools in tropical coastal zones, and illustrates their relevance in sustainable development. It highlights a selected number of remote sensing case-studies on land cover patterns, population structure and dynamics, and stand characteristics from South-East Asia, Africa and South-America, with a particular emphasis on mangroves. It further shows how remote sensing technology and other scientific tools can be integrated in long-term studies, both retrospective and predictive, in order to anticipate degradation and to take mitigating measures at an early stage. The paper also highlights the guidelines for sustainable management that can result from remote sensing and GIS studies, and identifies existent gaps and research priorities. There is a need for more comprehensive approaches that deal with new remote sensing technologies and analysis in a GIS-environment, and that integrate findings collected over longer periods with the aim of prediction. It is also imperative to collect and integrate data from different disciplines. 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