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Auteur Marijke Elisabeth Bekkema |
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Mapping grassland management intensity using Sentinel-2 satellite data / Marijke Elisabeth Bekkema in GI Forum, vol 2018 n° 1 ([01/01/2018])
[article]
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]