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dc.contributor.authorCristina Gonçalves, Ana
dc.contributor.authorSousa, Adélia
dc.contributor.authorMarques daSilva, José R.
dc.date.accessioned2021-06-02T10:09:37Z
dc.date.available2021-06-02T10:09:37Z
dc.date.issued2017
dc.identifierONIX_20210602_10.5772/65665_328
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/49214
dc.description.abstractAssessment and monitoring of forest biomass are frequently done with allometric functions per species for inventory plots. The estimation per area unit is carried out with an extrapolation method. In this chapter, a review of the recent methods to estimate forest above‐ground biomass (AGB) using remote sensing data is presented. A case study is given with an innovative methodology to estimate above‐ground biomass based on crown horizontal projection obtained with high spatial resolution satellite images for two evergreen oak species. The linear functions fitted for pure, mixed and both compositions showed a good performance. Also, the functions with dummy variables to distinguish species and compositions adjusted had the best performance. An error threshold of 5% corresponds to stand areas of 8.7 and 5.5 ha for the functions of all species and compositions without and with dummy variables. This method enables the overall area evaluation, and it is easily implemented in a geographic information system environment.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::T Technology, engineering, agriculture::TH Energy technology & engineering::THX Alternative & renewable energy sources & technology
dc.subject.otherQuickBird, multi‐resolution segmentation, crown horizontal projection, forest inventory, regressions
dc.titleChapter Above‐Ground Biomass Estimation with High Spatial Resolution Satellite Images
dc.typechapter
oapen.identifier.doi10.5772/65665
oapen.relation.isPublishedBy09f6769d-48ed-467d-b150-4cf2680656a1
oapen.relation.isFundedByH2020-EE-2015-3-MarketUptake
oapen.grant.number696140
oapen.grant.acronymTrustEE


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