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dc.contributor.authorPESARESI Martinoen_GB
dc.contributor.authorGERHARDINGER Andreaen_GB
dc.date.accessioned2012-06-29T00:00:52Z-
dc.date.available2012-06-28en_GB
dc.date.available2012-06-29T00:00:52Z-
dc.date.created2010-12-16en_GB
dc.date.issued2011en_GB
dc.date.submitted2010-04-07en_GB
dc.identifier.citationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING vol. 4 no. 1 p. 16-26en_GB
dc.identifier.issn1939-1404en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC57993-
dc.description.abstractAbstract┬┐The so-called PANTEX methodology for the automatic recognition of built-up areas is based on analysis of image textural measures extracted using anisotropic rotation-invariant gray-level co-occurrence matrix (GLCM) statistics [2]. These measures may overestimate the built-up areas in case of presence of scattered trees having the same spatial pattern of settlements. This overestimation is especially remarkable in case of bright soil background as in desert areas. In this paper we compare two options able to reduce this problem. One method is based on the subtraction of the vegetated areas from the built-up areas detected using the PANTEX index. The other method is based on the introduction of a morphological filtering step that pre-selects the image information to be ingested by the textural analysis phase. The test presented here uses multispectral Quick Bird satellite data input at the spatial resolution of 2.4 meters. In the selected test area, the application of the standard PANTEX procedure achieves the overall accuracy of 67.92%. The improvement of the procedure using the vegetation index achieves the accuracy of 70.37%, while the improvement based on morphological filtering achieves the accuracy of 88.69%, with an increase respect to the standard procedure of 2.44% and 20.76%, respectively.en_GB
dc.description.sponsorshipJRC.G.2-Global security and crisis managementen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.ispartofseriesJRC57993en_GB
dc.titleImproved textural built-up presence index for automatic recognition of human settlements in arid regions with scattered vegetationen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1109/JSTARS.2010.2049478en_GB
JRC Directorate:Space, Security and Migration

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