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Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities / Pavlos Tsagkis in Sustainable Cities and Society, vol 89 (February 2023)  

Public [article]  inSustainable Cities and Society > vol 89 (February 2023) . - n° 104337 Titre : Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities Type de document : Article/Communication Auteurs : Pavlos Tsagkis, Auteur ; Efthimios Bakogiannis, Auteur ; Alexandros Nikitas, Auteur Année de publication : 2023 Article en page(s) : n° 104337 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] Corine (base de données) [Termes IGN] croissance urbaine [Termes IGN] données localisées libres [Termes IGN] étalement urbain [Termes IGN] Grèce [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de surface [Termes IGN] modèle orienté agent [Termes IGN] OpenStreetMap [Termes IGN] planification urbaine [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Urban development if not planned and managed adequately can be unsustainable. Urban growth models have been a powerful toolkit to help tackling this challenge. In this paper, we use a machine learning approach, to apply an urban growth model to five of the largest cities in Greece. Specifically, we first develop a methodology to collect, organise, handle and transform historical open spatial data, concerning various impact factors, into machine learning data. Such factors involve social, economic, biophysical, neighbouring-related and political driving forces, which must be transformed into tabular data. We also provide an artificial neural network (ANN) model and the methodology to train and evaluate it using goodness-of-fit metrics, which in turn provide the best weights of impact factors. Finally, we execute a prediction for 2030, presenting the results and output maps for each of the five case study cities. As our study is based on pan-European datasets, our model can be used for any area within Europe, using the open-source utility developed to support it. In this sense, our work provides local policy-makers and urban planners with an instrument that could help them analyse various future development scenarios and take the right decisions going forward. Numéro de notice : A2023-116 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.104337 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104337 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102486 [article]

Comparison of deep neural networks in detecting field grapevine diseases using transfer learning / Antonios Morellos in Remote sensing, vol 14 n° 18 (September-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 18 (September-2 2022) . - n° 4648 Titre : Comparison of deep neural networks in detecting field grapevine diseases using transfer learning Type de document : Article/Communication Auteurs : Antonios Morellos, Auteur ; Xanthoula Eirini Pantazi, Auteur ; Charalampos Paraskevas, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4648 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de changement [Termes IGN] extraction de traits caractéristiques [Termes IGN] Grèce [Termes IGN] jeu de données [Termes IGN] maladie cryptogamique [Termes IGN] maladie phytosanitaire [Termes IGN] viticulture Résumé : (auteur) Plants diseases constitute a substantial threat for farmers given the high economic and environmental impact of their treatment. Detecting possible pathogen threats in plants based on non-destructive remote sensing and computer vision methods offers an alternative to existing laboratory methods and leads to improved crop management. Vine is an important crop that is mainly affected by fungal diseases. In this study, photos from healthy leaves and leaves infected by a fungal disease of vine are used to create disease identification classifiers. The transfer learning technique was employed in this study and was used to train three different deep convolutional neural network (DCNN) approaches that were compared according to their classification accuracy, namely AlexNet, VGG-19, and Inception v3. The above-mentioned models were trained on the open-source PlantVillage dataset using two training approaches: feature extraction, where the weights of the base deep neural network model were frozen and only the ones on the newly added layers were updated, and fine tuning, where the weights of the base model were also updated during training. Then, the created models were validated on the PlantVillage dataset and retrained using a custom field-grown vine photo dataset. The results showed that the fine-tuning approach showed better validation and testing accuracy, for all DCNNs, compared to the feature extraction approach. As far as the results of DCNNs are concerned, the Inception v3 algorithm outperformed VGG-19 and AlexNet in almost all the cases, demonstrating a validation performance of 100% for the fine-tuned strategy on the PlantVillage dataset and an accuracy of 83.3% for the respective strategy on a custom vine disease use case dataset, while AlexNet achieved 87.5% validation and 66.7% accuracy for the respective scenarios. Regarding VGG-19, the validation performance reached 100%, with an accuracy of 76.7%. Numéro de notice : A2022-768 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14184648 Date de publication en ligne : 17/09/2022 En ligne : https://doi.org/10.3390/rs14184648 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101794 [article]

Dendroclimatological analysis of fir (A. borisii-regis) in Greece in the frame of climate change investigation / Aristeidis Kastridis in Forests, vol 13 n° 6 (June 2022)  

Public [article]  inForests > vol 13 n° 6 (June 2022) . - n°979 Titre : Dendroclimatological analysis of fir (A. borisii-regis) in Greece in the frame of climate change investigation Type de document : Article/Communication Auteurs : Aristeidis Kastridis, Auteur ; Vasiliki Kamperidou, Auteur ; Dimitrios Stathis, Auteur Année de publication : 2022 Article en page(s) : n°979 Langues : Anglais (eng) Descripteur : [Termes IGN] Abies borisii-regis [Termes IGN] analyse diachronique [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] Grèce [Termes IGN] sécheresse [Termes IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Numéro de notice : A2022-490 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f13060879 Date de publication en ligne : 02/06/2022 En ligne : https://doi.org/10.3390/f13060879 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100965 [article]

Consideration on how to introduce gamification tools to enhance citizen engagement in crowdsourced cadastral surveys / K. Apostolopoulos in Survey review, vol 54 n° 383 (March 2022)  

Public [article]  inSurvey review > vol 54 n° 383 (March 2022) . - pp 142 - 152 Titre : Consideration on how to introduce gamification tools to enhance citizen engagement in crowdsourced cadastral surveys Type de document : Article/Communication Auteurs : K. Apostolopoulos, Auteur ; Chryssy Potsiou, Auteur Année de publication : 2022 Article en page(s) : pp 142 - 152 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger [Termes IGN] approche participative [Termes IGN] base de données foncières [Termes IGN] citoyen [Termes IGN] données cadastrales [Termes IGN] enquête [Termes IGN] Grèce [Termes IGN] participation du public [Termes IGN] réseau social [Termes IGN] téléphone intelligent Résumé : (auteur) The major objective of this research is to investigate the progress of citizen participation in cadastral surveying and to consider ways on how to introduce gamification tools for further improvement. A brief literature review is presented in the areas of the Sustainable Development Agenda 2030 related to land administration and citizen engagement, e-government and citizen participation and gamification tools for citizen engagement. This paper, also, includes an investigation of the progress in introducing volunteerism and citizen participation to the Hellenic Cadastre. A case study is held by a group of volunteers in order to assess the developed tools designed either by the private sector or by the cadastral agency. Numéro de notice : A2022-240 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT/SOCIETE NUMERIQUE Nature : Article DOI : 10.1080/00396265.2021.1888027 Date de publication en ligne : 23/02/2021 En ligne : https://doi.org/10.1080/00396265.2021.1888027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100164 [article]

A national fuel type mapping method improvement using sentinel-2 satellite data / Alexandra Stefanidou in Geocarto international, vol 37 n° 4 ([15/02/2022])  

Public [article]  inGeocarto international > vol 37 n° 4 [15/02/2022] . - pp 1022 - 1042 Titre : A national fuel type mapping method improvement using sentinel-2 satellite data Type de document : Article/Communication Auteurs : Alexandra Stefanidou, Auteur ; Ioannis Z. Gitas, Auteur ; Thomas Katagis, Auteur Année de publication : 2022 Article en page(s) : pp 1022 - 1042 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] analyse d'image orientée objet [Termes IGN] carte de la végétation [Termes IGN] carte thématique [Termes IGN] combustible [Termes IGN] distribution spatiale [Termes IGN] Grèce [Termes IGN] image Sentinel-MSI [Termes IGN] incendie de forêt [Termes IGN] prévention des risques Résumé : (auteur) Despite the fact that wildland fires have always been an integral part of many ecosystems, their increased frequency and intensity have reinforced the need of fire managers for updated and highly accurate information associated with the spatial distribution of forest fuels. In 2015, a fuel type mapping method was developed in the framework of the “National Observatory of Forest Fires (NOFFi)” project resulting in the generation of a national fuel type map. In this study, we aimed at examining the potential of the newly available Sentinel-2 satellite images for the improvement of the NOFFi’s mapping method in terms of accuracy and update effectiveness of the national fuel type map. Results demonstrate Sentinel-2 data will likely improve the resolution and reliability of national fuel type maps, increasing mapping efficiency for operational purposes. Numéro de notice : A2022-393 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1756460 Date de publication en ligne : 28/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1756460 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100687 [article]

Estimation of individual tree stem biomass in an uneven-aged structured coniferous forest using multispectral LiDAR data / Nikos Georgopoulos in Remote sensing, vol 13 n° 23 (December-1 2021)  

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Applying planetary mapping methods to submarine environments: onshore-offshore geomorphology of Christiana-Santorini-Kolumbo Volcanic Group, Greece / Alexandra E. Huff in Journal of maps, vol 17 n° 3 (July 2021)  

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Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece / Stavroula Dimitriadou in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)  

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Land use planning for natural hazards / George D. Bathrellos (2021)  

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Mapping urban spaces / Lamberto Amistadi (2021)  

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Deformation detection through the realization of reference frames / Nestoras Papadopoulos in Journal of applied geodesy, vol 14 n° 2 (April 2020)  

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Velocity field and crustal deformation of broader Athens plain (Greece) from a dense geodetic network / Michael Foumelis in Journal of applied geodesy, Vol 13 n° 4 (October 2019)  

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Mapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])  

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Assessing a new velocity field in Greece towards a new semi-kinematic datum / S. Bitharis in Survey review, vol 51 n° 368 (September 2019)  

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Using Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece / D.D. Alexakis in Geocarto international, vol 34 n° 7 ([01/06/2019])  

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