Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/51140

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dc.contributor.authorGonçalves, Joãopor
dc.contributor.authorHenriques, Renato F.por
dc.contributor.authorAlves, Paulopor
dc.contributor.authorSousa-Silva, Ritapor
dc.contributor.authorMonteiro, António T.por
dc.contributor.authorLomba, Ângelapor
dc.contributor.authorMarcos, Brunopor
dc.contributor.authorHonrado, Joãopor
dc.date.accessioned2018-02-27T16:30:57Z-
dc.date.issued2016-
dc.date.submitted2014-10-06-
dc.identifier.citationGonçalves, J., R. Henriques, Paulo Alves, R. Sousa-Silva, A. T. Monteiro, Angela Lomba, B. Marcos, and João Honrado. 2016. “Evaluating an Unmanned Aerial Vehicle-Based Approach for Assessing Habitat Extent and Condition in Fine-Scale Early Successional Mountain Mosaics.” Applied Vegetation Science 19(1):132–46.por
dc.identifier.issn1402-2001por
dc.identifier.urihttps://hdl.handle.net/1822/51140-
dc.description.abstractQuestion: Can very high-resolution colour orthophotography and digital surface models (DSMs) from an unmanned aerial vehicle (UAV) be effectively used for assessment of habitat extent and condition in fine-scale disturbancedependent mosaics? Location: Serra de Arga mountain range, a Natura 2000 protected site in the NW region of Portugal where drastic changes in pastoral activities have occurred over recent decades. Methods: An UAV platform was used to collect very high-resolution (6 cm) images and to produce a DSM (10 cm). From these data, several features were extracted related to colour, band ratios, as well as texture features calculated from colour imagery and surface elevation. Based on a systematic sampling design, field data were collected for both training and validation of a supervised classifier. Extracted features and ground truth training data were combined to calibrate a pixel-based Random forest classifier, with the purpose of devising a habitat map for the entire study area. Map validation was performed to assess classification accuracy, and feature importance metrics were calculated. Results: Validation results revealed good mean overall accuracy (0.89), with some performance decrease in situations of high interspersion of habitat types. The priority habitat type 6230* (Nardus grasslands), defining the vegetation matrix of the test site, obtained 0.96 and 0.91, considering, respectively, producer and user accuracy. In turn, priority habitat type 4020* (Atlantic wet heathlands) recorded 0.68 and 0.77. The obtained habitat map allowed measurement of the extent, description of the spatial arrangement and provided an indication of the conservation condition of target habitat types. Test results regarding the discrimination ability of different features highlighted the importance of surface elevation textures derived from the DSM, followed by band ratios textures and other more complex texture features calculated from colour imagery. Conclusions: Overall, the developed methodology showed promising results for assessing the extent and condition of habitats of high conservation priority in fine-scale, dynamic vegetation mosaics. Future advances in the use of UAV platforms may play an important role in monitoring protected sites and fulfil legal reporting obligations of EU member states, while reducing the costs associated with intensive in-field assessments.por
dc.description.sponsorshipThis study was developed as part of the LIFE+ project ‘Higro’ (Demonstrative Actions for the Conservation of Priority Habitats in Northern Mountain Areas in Portugal; LIFE09NAT/PT/000043). Jo~ao Gonc alves was supported by the Portuguese Foundation for Science and Technology (FCT; PhD grant nr. SFRH/BD/90112/2012). Rita SousaSilva is supported by a PhD grant from KU Leuven in the framework of the FORBIO Climate project, financed by BRAIN.be, Belgian Research Action through INterdisciplinary research. Ant onio T. Monteiro is supported through the Project ‘Biodiversity, Ecology and Global Change’, co-financed by North Portugal Regional Operational Programme 2007/2013 (ON.2 – O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF). A. Lomba is supported by the PFST through Post-Doctoral Fellowship SFRH/BPD/80747/2011. Bruno Marcos received support from FEDER/COMPETE and FCT through project grant ‘IND_CHANGE’ (PTDC/AAG-MAA/ 4539/2012– FCOMP-01-0124-FEDER-027863).por
dc.language.isoengpor
dc.publisherWileypor
dc.relationinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F90112%2F2012/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBPD%2F80747%2F2011/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/131431/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/COMPETE/131431/PTpor
dc.rightsclosedAccesspor
dc.subjectHabitat typespor
dc.subjectImage classificationpor
dc.subjectMonitoring; Mountain systempor
dc.subjectNatura 2000por
dc.subjectRandom forestpor
dc.subjectRemote sensingpor
dc.subjectUnmanned aerial vehiclepor
dc.subjectVery high spatial resolutionpor
dc.subjectMonitoringpor
dc.subjectMountain systempor
dc.titleEvaluating an unmanned aerial vehicle-based approach for assessing habitat extent and condition in fine-scale early successional mountain mosaicspor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttp://onlinelibrary.wiley.com/doi/10.1111/avsc.12204/abstractpor
oaire.citationStartPage132por
oaire.citationEndPage146por
oaire.citationIssue1por
oaire.citationVolume19por
dc.identifier.eissn1654-109Xpor
dc.identifier.doi10.1111/avsc.12204por
dc.subject.fosCiências Naturais::Ciências Biológicaspor
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technologypor
sdum.journalApplied Vegetation Sciencepor
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