Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/14350
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dc.contributor.authorKyriakidis, Phaedon-
dc.contributor.authorDungan, Jennifer L.-
dc.date.accessioned2019-07-05T11:04:12Z-
dc.date.available2019-07-05T11:04:12Z-
dc.date.issued2001-01-01-
dc.identifier.citationEnvironmental and Ecological Statistics, Volume 8, Issue 4, 2001, Pages 311-330en_US
dc.identifier.issn2-s2.0-0035677673-
dc.identifier.issnhttps://api.elsevier.com/content/abstract/scopus_id/0035677673-
dc.identifier.issn13528505-
dc.identifier.issn2-s2.0-0035677673-
dc.identifier.issnhttps://api.elsevier.com/content/abstract/scopus_id/0035677673-
dc.identifier.issn2-s2.0-0035677673-
dc.identifier.issnhttps://api.elsevier.com/content/abstract/scopus_id/0035677673-
dc.identifier.issn2-s2.0-0035677673-
dc.identifier.issnhttps://api.elsevier.com/content/abstract/scopus_id/0035677673-
dc.identifier.urihttps://ktisis.cut.ac.cy/handle/10488/14350-
dc.description.abstractSpatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).en_US
dc.language.isoenen_US
dc.relation.ispartofEnvironmental and Ecological Statisticsen_US
dc.subjectBiogeochemical cyclesen_US
dc.subjectClassification uncertaintyen_US
dc.subjectGeographic information systemsen_US
dc.subjectIndicator krigingen_US
dc.subjectLand cover map qualityen_US
dc.subjectNet primary productionen_US
dc.subjectRemote sensingen_US
dc.subjectStochastic simulationen_US
dc.titleA geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictionsen_US
dc.typeArticleen_US
dc.collaborationStanford Universityen_US
dc.collaborationCalifornia State Universityen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsSubscription Journalen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1023/A:1012778302005en_US
dc.identifier.scopus2-s2.0-0035677673en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/0035677673en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.issue4en
dc.relation.volume8en
cut.common.academicyear2000-2001en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.languageiso639-1other-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4222-8567-
crisitem.author.parentorgFaculty of Engineering and Technology-
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