Land Cover and Crop Type Mapping at National Scale from Multitemporal High Resolution Satellite Data

Καρακίζη, Χριστίνα; Karakizi, Christina

dc.contributor.author	Καρακίζη, Χριστίνα	el
dc.contributor.author	Karakizi, Christina	en
dc.date.accessioned	2022-09-29T09:21:21Z
dc.date.available	2022-09-29T09:21:21Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/55812
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.23510
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/gr/	*
dc.subject	Image Classification	en
dc.subject	Machine Learning	en
dc.subject	Sentinel-2	en
dc.subject	Time Series	en
dc.subject	Big Data	en
dc.subject	Ταξινόμηση Εικόνας	el
dc.subject	Μηχανική Μάθηση	el
dc.subject	Χρονοσειρές Εικόνων	el
dc.subject	Μεγάλα Δεδομένα	el
dc.subject	Παρακολούθηση της Γης	el
dc.subject	Earth Observation	en
dc.title	Land Cover and Crop Type Mapping at National Scale from Multitemporal High Resolution Satellite Data	en
dc.title	Χαρτογράφηση Κάλυψης Γης και Καλλιεργειών σε Εθνική Κλίμακα με Χρήση Διαχρονικών Δορυφορικών Δεδομένων Υψηλής Χωρικής Ανάλυσης	el
dc.contributor.department	Εργαστήριο Τηλεπισκόπησης	el
heal.type	doctoralThesis
heal.classification	Remote Sensing	en
heal.classification	Τηλεπισκόπηση	el
heal.language	el
heal.language	en
heal.access	campus
heal.recordProvider	ntua	el
heal.publicationDate	2022-04-04
heal.abstract	Accurate and regularly updated land cover and crop type maps are considered essential for several scientific communities as well as for public and regional authorities. Currently, satellite Earth Observation data are considered the main input for the production of such maps thanks to the high spatial and temporal coverage, systematic monitoring and access to inaccessible areas, they can offer. The last decade, open data policies have given free access to an unprecedented volume of high spatial, temporal and spectral resolution satellite data, bringing a revolution in research and operational applications. Nonetheless the seamless exploitation of such Big Data for the production of accurate and reliable maps requires the developmental of efficient, robust and cost-effective pre-processing, classification and mapping frameworks. Towards this end, in this dissertation the subject of land cover and crop type mapping using multitemporal multispectral satellite data of high spatial resolution is thoroughly studied, assessed and discussed. The dissertation’s main contribution is the development, implementation and validation of a mapping framework exploiting Sentinel-2 data for the production of annual land cover and crop type maps at national scale for Greece. For data pre-processing, we have designed, developed and validated an efficient pipeline for the creation of radiometrically, geometrically and temporally consistent analysis-ready time series, while we have also further investigated the contribution of different applied methods and techniques. Various aspects of the mapping framework, i.e., machine learning algorithms, classification features, spatial stratification and validation approaches, have been experimentally assessed towards finalizing the proposed scheme. For map production we implemented a framework employing the Random Forest classifier, selected spectral and auxiliary features and a highly reliable training dataset, created under the scopes of this dissertation for 42, customized to the Greek Landscape, categories. Internal validation of the national classification experiments has documented a very high overall accuracy rate of over 91%. The generalization capacity of the classifier in predicting areas where it has not been trained on was validated with a high overall accuracy rate over 83%, as well. Finally, the produced country-scale land cover and crop type map at 10m with 42 classes, was externally validated by an independent rigorous accuracy assessment procedure that reported overall map accuracy at 82%. To the best of our knowledge there is no other available land cover map for Greece at 10m spatial resolution with such a thematic analysis and that high accuracy and reliability levels. Suggested ideas for the enhancement and further development of the proposed framework raised significant expectations for its expansion and use towards operational land cover and crop type map production at the country scale at regular time intervals, for supporting national and European actions, initiatives and mapping programs, such as the CORINE Land Cover inventory and the EU Common Agricultural Policy partnership.	en
heal.sponsor	Part of this dissertation research was funded by the ’ELKE’ Doctoral fellowship of the National Technical University of Athens and the ‘Research Projects for Excellence IKY/SIEMENS’.	en
heal.advisorName	Karantzalos, Konstantinos
heal.advisorName	Καράντζαλος, Κωνσταντίνος
heal.committeeMemberName	Karantzalos, Konstantinos
heal.committeeMemberName	Karathanassi, Vasilia
heal.committeeMemberName	Argialas, Dimitris
heal.committeeMemberName	Symeonakis, Elias
heal.committeeMemberName	Varras, Grigoris
heal.committeeMemberName	Mallinis, Georgios
heal.committeeMemberName	Manakos, Ioannis
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Αγρονόμων και Τοπογράφων Μηχανικών	el
heal.academicPublisherID	ntua
heal.numberOfPages	204
heal.fullTextAvailability	false