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dc.contributor.authorCristina Gonçalves, Ana
dc.contributor.authorM. O. Sousa, Adélia
dc.date.accessioned2021-02-10T12:58:18Z
dc.date.issued2018
dc.date.submitted2021-06-02T10:10:56Z
dc.identifierONIX_20210602_10.5772/intechopen.76817_380
dc.identifierhttps://library.oapen.org/handle/20.500.12657/49266
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/70298
dc.description.abstractAssessment and monitoring of forest structure is frequently done with absolute density measures with field forest inventory data and expansion methods. The development of basal area and the number of trees estimation functions with data derived from very high spatial resolution satellite images enable their short-term and cost-effective evaluation, allowing also the estimation for the area not requiring extrapolation methods. The functions of basal area and the number of trees per hectare are based on crown cover obtained with very high spatial resolution satellite images for two evergreen oaks and umbrella pine. The three tree species are especially important in the agroforestry systems of the Mediterranean region. The linear functions fitted for pure stands of the three species and mixed stands of cork and holm oak and of cork oak and umbrella pine showed a better performance for basal area than for the number of trees per hectare. The inclusion of dummy variables for species composition improved the accuracy of the functions.
dc.languageEnglish
dc.rightsopen access
dc.subject.otherquickBird image, multi-resolution segmentation, crown horizontal projection, absolute density measures, regression
dc.subject.otherthema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences
dc.titleChapter Absolute Density Measures Estimation Functions with Very High Resolution Satellite Images
dc.typechapter
oapen.identifier.doi10.5772/intechopen.76817
oapen.relation.isPublishedBy035ecc65-6737-43cf-a13a-6bdf67ce01f4
dc.relationisFundedByH2020-EE-2015-3-MarketUptake


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