GIS Integration of Aster Stereo Imagery for the Support of Watershed ManagementView Crossref metadata(active tab) <div id="edit-xml" class="form-item form-type-item"> <?xml version="1.0"?> <doi_batch version="4.4.1" xmlns="http://www.crossref.org/schema/4.4.1" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/schema/4.4.1 http://www.crossref.org/schemas/crossref4.4.1.xsd"><head><doi_batch_id>000692</doi_batch_id><timestamp>1713942867</timestamp><depositor><depositor_name>University of the Aegean</depositor_name><email_address>uoa@university.com</email_address></depositor><registrant>Global NEST Journal</registrant></head><body><journal><journal_metadata><full_title>Global NEST Journal</full_title><full_title>Global NEST: the international Journal</full_title><issn media_type="print">1790-7632</issn><issn media_type="electronic">2241-777X</issn></journal_metadata><journal_issue><titles><title>Issue 2</title></titles><publication_date><month>07</month><year>2024</year></publication_date><journal_volume><volume>5</volume></journal_volume><issue>2</issue></journal_issue><journal_article><titles><title>GIS Integration of Aster Stereo Imagery for the Support of Watershed Management</title></titles><abstract xmlns="http://www.ncbi.nlm.nih.gov/JATS1"><p>In this study, ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) stereo imagery was analysed in combination with Global Positioning System (GPS) data and field observations, using Geographical Information Systems (GIS) techniques to examine the potential of satellite remote sensing to support watershed management. Terrain elevation data were derived for the region of Heraklion, Crete. The accuracy of the ASTER derived DEM (Digital Elevation Model), was better than 20 meters (planimetric) and better than 15 meters (elevation). Supervised classification techniques were applied for land cover production using ASTER multi-spectral imagery and filed observations at predefined application sites. The determination of training areas required in the supervised classification scheme was based on these observations. Finally, GIS methods were applied to estimate watershed characterization parameters for the study area offering the advantages of spatial data handling capabilities and automatic extraction of thematic information. The drainage pattern, which was derived, provided a generally representative depiction of the watershed. The output pixel spacing of 15 m of the produced DEM as well as the high spatial resolution of ASTER imagery found to be quite satisfactory for the watershed characterization of the study area, indicating the high potential of ASTER imagery to support watershed management.</p></abstract><publication_date><month>04</month><day>29</day><year>2013</year></publication_date><pages><first_page>47</first_page><last_page>56</last_page></pages><publisher_item><identifier id_type="pii">266</identifier></publisher_item><doi_data><doi>10.30955/gnj.000266</doi><timestamp>1713942867</timestamp><resource>https://journal.gnest.org/publication/266</resource></doi_data></journal_article></journal></body></doi_batch> </div>
