GI Forum / Car, Adrijana . vol 2018 n° 1Paru le : 01/01/2018 |
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Ajouter le résultat dans votre panierSentinel-2 data analysis and comparison with UAV multispectral images for precision viticulture / Frederica Nonni in GI Forum, vol 2018 n° 1 ([01/01/2018])
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Titre : Sentinel-2 data analysis and comparison with UAV multispectral images for precision viticulture Type de document : Article/Communication Auteurs : Frederica Nonni, Auteur ; Diego Malacarne, Auteur ; Salvatore Eugenio Pappalardo, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 105 -116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture de précision
[Termes IGN] analyse comparative
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] image Sentinel-MSI
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] viticultureRésumé : (auteur) Precision viticulture (PV) requires the use of technologies that can detect the spatial and temporal variability of vineyards and, at the same time, allow useful information to be obtained at sustainable costs. In order to develop a cheap and easy - to - handle operational monitoring scheme for PV, the aim of this work was to evaluate the possibility of using Sentinel-2 multispectral images for long- term vineyard monitoring through the Normalized Difference Vegetation Index (NDVI) . Vigo u r maps of two vineyards located in north eastern Italy were computed from satellite imagery and compared with those derived from UAV multispectral images ; their correspondence was evaluated from qualitative and statistical point s of view. To achieve this, the UAV images were roughly resampled to 10 m pixel size in order to match the spatial resolution of the satellite imagery. Preliminary results show the potential use of open source Sentinel-2 platforms for monitoring vineyards, highlighting links with the information given in the agronomic bulletins and identifying critical areas for crop production. Despite the large differences in spatial resolution, the results of the comparison between the UAV and Sentinel-2 data were promising. However, for long-term vineyard monitoring at territory scale, further studies using multispectral sensor calibration and ground truth data are required. Numéro de notice : A2018-300 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1553/giscience2018_01_s105 En ligne : http://dx.doi.org/10.1553/giscience2018_01_s105 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90398
in GI Forum > vol 2018 n° 1 [01/01/2018] . - pp 105 -116[article]Mapping grassland management intensity using Sentinel-2 satellite data / Marijke Elisabeth Bekkema in GI Forum, vol 2018 n° 1 ([01/01/2018])
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Titre : Mapping grassland management intensity using Sentinel-2 satellite data Type de document : Article/Communication Auteurs : Marijke Elisabeth Bekkema, Auteur ; Marieke Eleveld, Auteur Année de publication : 2018 Article en page(s) : pp 194 - 213 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Aves
[Termes IGN] biodiversité
[Termes IGN] habitat animal
[Termes IGN] image Sentinel-MSI
[Termes IGN] prairieRésumé : (auteur) For the conservation of biodiversity in general and the monitoring of meadow birds in particular, actual grassland - use intensity maps are highly desirable. A method to map and assess grassland management intensity was developed using C5.0 decision tree classification on Sentinel-2 satellite data. Monoculture and extensively managed grasslands on both peat and clay soils could be accurately detected at parcel level in Friesland, the Netherlands. Field - survey - based validation returned an overall classification accuracy of 84.3% (KHAT 0.65). The Sentinel-2 Red-Edge Position vegetation index was found to be a good indicator of fertilization. Availability of springtime imagery, preferably acquired in April before the first mowing date, is essential for accurate classification. The spectral responses of grassland types on peat and clay soils differ significantly. Hence, successful classification requires training data for both soil types. The resulting grassland management map was used to assess the distribution of meadow bird nests. Redshank (79%) and godwit (77%) in particular choose to breed on extensive parcels. With the increasing availability of satellite imagery, remote sensing techniques can be used to monitor agri-environmental measures (at parcel and landscape scale) that impact the conservation of grassland biodiversity. Numéro de notice : A2018-301 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1553/giscience2018_01_s194 En ligne : http://dx.doi.org/10.1553/giscience2018_01_s194 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90399
in GI Forum > vol 2018 n° 1 [01/01/2018] . - pp 194 - 213[article]Automated delineation of wildfire areas using Sentinel-2 satellite imagery / Mira Weirather in GI Forum, vol 2018 n° 1 ([01/01/2018])
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Titre : Automated delineation of wildfire areas using Sentinel-2 satellite imagery Type de document : Article/Communication Auteurs : Mira Weirather, Auteur ; Gunter Zeug, Auteur ; Thomas Schneider, Auteur Année de publication : 2018 Article en page(s) : pp 251 - 262 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Copernicus (programme européen)
[Termes IGN] extraction automatique
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] informatique en nuageRésumé : (auteur) Climate change will bring many changes to the world. For example, the frequency and severity of natural hazards and related disasters are expected to increase globally. Wildfires already affect thousands of people every year and cause billions of Euros’ worth of damage. It is therefore paramount to develop measures that help deal with the consequences of wildfires. Forests being the largest terrestrial ecosystem in the European Union and providing many ecosystem services, their loss due to wildfires is of serious concern. In this study, an algorithm to extract the burned area of wildfire events is presented. It was developed on the basis of three fire events in 2017. The procedure is fully automated, from downloading suitable data to determining the burned area by applying the differenced Normalized Burn Ratio (dNBR) on open Sentinel-2 satellite imagery from the European Copernicus programme. First results show good performance and encourage its further development and application. It is planned that the output of our mapping will feed into and be used in calibrating wildfire simulations during longer fire events. Numéro de notice : A2018-302 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1553/giscience2018_01_s251 En ligne : https://doi.org/10.1553/giscience2018_01_s251 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90400
in GI Forum > vol 2018 n° 1 [01/01/2018] . - pp 251 - 262[article]