Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → Grèce → Multi-scale modelling of land cover/land use (LCLU) change with Geoinformatics and scenario-based simulations

University of the Aegena (2018)

Multi-scale modelling of land cover/land use (LCLU) change with Geoinformatics and scenario-based simulations

Gounaridis, Dimitrios

Titre : Multi-scale modelling of land cover/land use (LCLU) change with Geoinformatics and scenario-based simulations

Μοντελοποίηση σε πολλαπλές κλίμακες των αλλαγών κάλυψης/χρήσης γης με χρήση γεωπληροφορικής και προσομοίωση εναλλακτικών σεναρίων

Auteur : Gounaridis, Dimitrios

Etablissement de soutenance : University of the Aegena

Grade : Doctor of Philosophy (PhD) 2018

Résumé
The aim of the dissertation is to explore and understand the system of land use/land cover (LULC) changes in multiple scales by decoding the factors that affect it. An integrated methodological framework that i) takes into account the multiple scales involved in the LULC change system, ii) provides information on very high thematic analysis, iii) detects changes in LULC in a sufficient temporal resolution (iv) takes into account a wide range of factors affecting LULC ; and (v) provides results that are subject to sensitivity analysis, is described. The integrated approach involves semi-automated training for LULC classification and very high thematic resolution. The first step is to detect and quantify the historical LULC changes employing satellite data and geoinformatics. The changes are mapped and quantified using cross classification techniques. Next, the changes are combined with various spatial determinants derived for multiple sources and expressed in multiple scales, in order to generate transition probability surfaces. The alternative scenarios represent t different stages of economic growth. Scenarios are projected by implementing a spatially explicit Cellular Automata (CA) model. Finally, the resulting maps, are subject to a multiple resolution sensitivity analysis.

Présentation

Version intégrale (8 Mb)

Page publiée le 14 décembre 2022