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		<secondarykey>INPE-14635-PRE/9637</secondarykey>
		<issn>0098-3004</issn>
		<label>self-archiving-INPE-MCTIC-GOV-BR</label>
		<citationkey>ValerianoKuStAmMeLi:2006:MoSmWa</citationkey>
		<title>Modeling small watersheds in Brazilian Amazônia with SRTM-90m data</title>
		<project>Modelagem de dados topográficos SRTM (CNPq); TOPODATA (OBT)</project>
		<year>2006</year>
		<secondarydate>20061001</secondarydate>
		<month>Outubro</month>
		<secondarytype>PRE PI</secondarytype>
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		<author>Valeriano, Márcio de Morisson,</author>
		<author>Kuplich, Tatiana Mora,</author>
		<author>Storino, Moisés,</author>
		<author>Amaral, Benedito Domingues do,</author>
		<author>Mendes Júnior, Jaime Nogueira,</author>
		<author>Lima, Dayson Jardim,</author>
		<resumeid></resumeid>
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		<group>DSR-INPE-MCT-BR</group>
		<group>DSR-INPE-MCT-BR</group>
		<affiliation>INPE</affiliation>
		<affiliation>INPE</affiliation>
		<affiliation>IAC</affiliation>
		<affiliation>UNESP</affiliation>
		<affiliation>UNICAMP</affiliation>
		<affiliation>INPE</affiliation>
		<e-mailaddress>valerian@dsr.inpe.br</e-mailaddress>
		<journal>Computers and Geosciences</journal>
		<volume>32</volume>
		<number>8</number>
		<pages>1169-1181</pages>
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		<contenttype>External Contribution</contenttype>
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		<keywords>Geoprocessing, SRTM, Watershed, Amazonia.</keywords>
		<abstract>This work presents a methodology for the refinement of SRTM (Shuttle Radar Topographic Mission)-90m data available for South America to enable detailed watershed studies in Amazonia. The original data were pre-processed to properly map detailed low-order drainage features and allowed digital estimates of morphometric variables. Spatial resolution refinement (3o to 1o, or ~90m to ~30m) through data kriging was found to be an interesting solution to construct Digital Elevation Models (DEM) with more adequate presentation of land forms than the original data. The refinement of spatial resolution by kriging interpolation overcame the main constraints for drainage modeling with original SRTM-90m, such as spatial randomness, artifacts and unrealistic presentation due to pixel size. Kriging with Gaussian semivariogram model caused a smoothing of the resulting DEM, but the main features for drainage modeling were preserved. Canopy effects on the modeled surface represented the main remaining limitation for terrain analysis after pre-processing. Data regarding a small watershed in Amazonas (~38km2), Brazil, were evaluated through visualization techniques, morphometric analyses and plot diagrams of the results. The data showed limitations for use in the original form, but could be applied for watershed modeling at relatively detailed scales after the described pre-processing.</abstract>
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		<language>en</language>
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