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		<doi>10.1007/s40808-016-0129-3</doi>
		<issn>2363-6203</issn>
		<citationkey>ContiAraúCunh:2016:SpDaMo</citationkey>
		<title>Spatial database modeling for mangrove forests mapping; example of two estuarine systems in Brazil</title>
		<year>2016</year>
		<month>June</month>
		<typeofwork>journal article</typeofwork>
		<secondarytype>PRE PI</secondarytype>
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		<author>Conti, Luis Américo,</author>
		<author>Araújo, Carlos Alberto Sampaio de,</author>
		<author>Cunha-Lignon, Marília,</author>
		<group></group>
		<group>DSR-OBT-INPE-MCTI-GOV-BR</group>
		<affiliation>Universidade de São Paulo (USP)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Universidade Estadual Paulista (UNESP)</affiliation>
		<electronicmailaddress>lconti@usp.br</electronicmailaddress>
		<electronicmailaddress>carlos@dsr.inpe.br</electronicmailaddress>
		<journal>Modelling Earth Systems and Enrironment</journal>
		<volume>2</volume>
		<number>73</number>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
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		<keywords>Remote sensing  GIS  Time change detection  Subtropical wetland  Coastal zone management  Conservation  Geospatial database Intr.</keywords>
		<abstract>This work considers mangrove cover changes in two subtropical estuaries in the southeastern coast of Brazil: Canane´ia-Iguape Coastal System and Santos Estuarine System. A sequence of Landsat images from 1985 to 2014 from both areas was segmented, classified and analyzed in order to develop a systematic GIS approach for identifying and characterizing mangrove fragments in such estuaries and how they change over time. The main goal of our work is to propose a unified hierarchical spatial database model in a GIS framework developed to incorporate different types of spatial information such as spectral (e.g. vegetation indices), spatial (e.g. fragmentation indices) and temporal (e.g. change detection) at different scales. The examples analyzed showed that changes and fluctuations in mangrove habitats could be identified and characterized revealing potential tools for handling and analyzing data focused on environmental monitoring and the coastal resource protection and conservation.</abstract>
		<area>SRE</area>
		<language>en</language>
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