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A new approach to quantify grazing pressure under mediterranean pastoral systems using GIS and remote sensing

2020Journal article Restricted access
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dc.contributor.authorCastro, Marina
dc.contributor.authorAmeray, Abderrahmane
dc.contributor.authorCastro, João Paulo
dc.date.accessioned2020-04-20T13:17:42Z
dc.date.available2020-04-20T13:17:42Z
dc.date.issued2020
dc.description.abstractPastoral systems based on grazing itineraries are very common along the Mediterranean region and provide an opportunity to manage the fuel load and reduce fire risk in the ecosystem. Daily and seasonal movements of flocks bring on different grazing pressure (GP) (sheep ha−1) over the landscape. This study presents an approach to model sheep GP under a Mediterranean pastoral system in the Northeast of Portugal. The GP in a given location depends on the distance from the stable to the parish border, the distance to the stable, the heads of livestock and their preference for land use and cover (LUC). The geoprocessing we applied in this study integrated several spatial databases: the latest official Portuguese vector mapping of land use and cover (COS2015) and administrative boundaries (CAOP2018), the livestock stables location, and Sentinel-2 Multispectral Images. During the geoprocessing, the stocking density (SD) (sheep ha−1) were calculated and spatially interpolated. Homogeneous LUC units (permanent crops; annual crops; forest; shrubland; grassland; water bodies) were obtained by Random Forest supervised classification algorithm (kappa = 89.3%; global accuracy = 91.2%). Boolean overlapping of the LUC classes obtained by the supervised classifier with the mask created from COS2015 provides the potentially grazed LUC classes. Integrating LUC preferences with SD allows calculating and mapping the GP. The most common GP class is 0–0.25 sheep ha−1. Seeing the GP per LUC class, a value of 1.84 sheep ha−1 was found in permanent crops, 1.73 in annual crops, and 1.25 in grassland, 0.88 in grazed forests and 0.84 in shrublands. The GP modelling and mapping could assist in the implementation of herding programmes aimed at reducing fire hazards at a parish or at a regional scale.pt_PT
dc.description.sponsorshipWe acknowledge partial funding for this research from the European Regional Development Fund (ERDF) through the INTERREG SUDOE Programme (SOE2/P5/E0804: Open2Preserve). We thank two anonymous expert referees and the editor for their extremely valuable comments and suggestions on the manuscript.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCastro, Marina; Ameray, Abderrahmane; Castro, João Paulo (2020). A new approach to quantify grazing pressure under mediterranean pastoral systems using GIS and remote sensing. International Journal of Remote Sensing. ISSN 0143-1161. 41:14, p. 5371-5387pt_PT
dc.identifier.doi10.1080/01431161.2020.1731930pt_PT
dc.identifier.issn0143-1161
dc.identifier.urihttp://hdl.handle.net/10198/21724
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor and Francis Onlinept_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.titleA new approach to quantify grazing pressure under mediterranean pastoral systems using GIS and remote sensingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage5387pt_PT
oaire.citation.issue14pt_PT
oaire.citation.startPage5371pt_PT
oaire.citation.titleInternational Journal of Remote Sensingpt_PT
oaire.citation.volume41pt_PT
person.familyNameCastro
person.familyNameCastro
person.givenNameMarina
person.givenNameJoão Paulo
person.identifier2303569
person.identifier.ciencia-id6417-7D8D-FD7E
person.identifier.ciencia-id8D19-DBCC-8EF5
person.identifier.orcid0000-0002-6368-8098
person.identifier.orcid0000-0003-0647-8892
person.identifier.ridB-5197-2016
person.identifier.ridA-8581-2014
person.identifier.scopus-author-id56612728000
person.identifier.scopus-author-id21233448700
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationa7a3b08e-9d22-4faf-9224-36924d8ce7c8
relation.isAuthorOfPublication17820e65-bb0d-434b-bfef-4bb539f614a5
relation.isAuthorOfPublication.latestForDiscoverya7a3b08e-9d22-4faf-9224-36924d8ce7c8

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