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Cadastral mapping of forestlands in Greece : current and future challenges / M. Vogiatzis in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 1 (January 2008)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 1 (January 2008) . - pp 39 - 46 Titre : Cadastral mapping of forestlands in Greece : current and future challenges Type de document : Article/Communication Auteurs : M. Vogiatzis, Auteur Année de publication : 2008 Article en page(s) : pp 39 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger [Termes IGN] cadastre étranger [Termes IGN] cadastre numérique [Termes IGN] carte de la végétation [Termes IGN] composant SIG [Termes IGN] forêt méditerranéenne [Termes IGN] Grèce [Termes IGN] occupation du sol [Termes IGN] orthophotoplan numérique [Termes IGN] système d'information foncière Résumé : (Auteur) The Hellenic Cadastre Program (HCP) of Greece aims at developing a modern cadastral system for the first time in the Hellenic history. This paper is focused on the issues related to cadastral forestlands digital mapping, an indispensable part of HCP. Mapping the forestlands is a challenge of multiple disciplines. It includes photogrammetry, photointerpretation, Geographic Information Systems (GIS), and a clear understanding of the current institutional and legislative setting. The process requires both historical and current information pertaining to land-cover in order to identify forestland changes over time. Historical and current digital orthoimagery is generated through photogrammetric operations. Forestlands are delineated in a spatiotemporal environment; state property rights in forestlands are allocated and land ownership is established within the framework of HCP. This paper demonstrates that the integration of airborne remote sensing and collateral data with a GIS is an effective approach for cadastral forest mapping. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. Copyright ASPRS Numéro de notice : A2008-013 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.14358/PERS.74.1.39 En ligne : https://doi.org/10.14358/PERS.74.1.39 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29008 [article]

Global elevation ancillary data for land-use classification using granular neural networks / D. Stathakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 1 (January 2008)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 1 (January 2008) . - pp 55 - 63 Titre : Global elevation ancillary data for land-use classification using granular neural networks Type de document : Article/Communication Auteurs : D. Stathakis, Auteur ; I. Kanellopoulos, Auteur Année de publication : 2008 Article en page(s) : pp 55 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] altitude [Termes IGN] classification floue [Termes IGN] classification par réseau neuronal [Termes IGN] données auxiliaires [Termes IGN] fusion d'images [Termes IGN] granularité d'image [Termes IGN] logique floue [Termes IGN] utilisation du sol Résumé : (Auteur) The development of digital global databases containing data such as elevation and soil can greatly simplify and aid in the classification of remotely sensed data to create land-use classes. An efficient method that can simultaneously handle diverse input dimensions can be formed by merging fuzzy logic and neural networks. The so-called granular or fuzzy neural networks are able not only to achieve high classification levels, but at the same time produce compressed and transparent neural network skeletons. Compression results in reduced training times, while transparency is an aid for interpreting the structure of the neural network by translating it into meaningful rules and vice versa. The purpose of this paper is to provide some initial guidelines for the construction of granular neural networks in the remote sensing context, while using global elevation ancillary data within the classification process. Copyright ASPRS Numéro de notice : A2008-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.1.55 En ligne : https://doi.org/10.14358/PERS.74.1.55 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29009 [article]