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Synergistic use of Lidar and color aerial photography for mapping urban parcel imperviousness / M.E. Hodgson in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 9 (September 2003) . - pp 973 - 980 Titre : Synergistic use of Lidar and color aerial photography for mapping urban parcel imperviousness Type de document : Article/Communication Auteurs : M.E. Hodgson, Auteur ; J.R. Jensen, Auteur ; J.A. Tullis, Auteur ; K.D. Riordan, Auteur ; C.M. Archer, Auteur Année de publication : 2003 Article en page(s) : pp 973 - 980 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] classification par maximum de vraisemblance [Termes IGN] données lidar [Termes IGN] orthoimage [Termes IGN] parcelle cadastrale [Termes IGN] photographie en couleur [Termes IGN] ruissellement [Termes IGN] surface imperméable [Termes IGN] système expert Résumé : (Auteur) The imperviousness of land parcels was mapped and evaluated using high spatial resolution digitized color orthophotography and surface-cover height extracted from multiple-return lidar data. Maximum-likelihood classification, spectral clustering, and expert system approaches were used to extract the impervious information from the datasets. Classified pixels (segments) were aggregated to parcels. The classification model based on the use of both the orthophotography and lidar-derived surface-cover height yielded impervious surface results for all parcels that were within 15 percent of reference data. The standard error for the rule-based per-pixel model was 7.15 percent with a maximum observed error of 18.94 percent. The maximum-likelihood per-pixel classification yielded a lower standard error of 6.62 percent with a maximum of 14.16 percent. The regression slope (i.e., 0. 955) for the maximum-likelihood per-pixel model indicated a near perfect relationship between observed and predicted imperviousness. The additional effort of using a per-segment approach with a rule-based classification resulted in slightly better standard error (5.85 percent) and a near-perfect regression slope (1.016). Numéro de notice : A2003-227 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.69.9.973 En ligne : https://doi.org/10.14358/PERS.69.9.973 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22522 [article]