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dc.contributor.editorTomppo, Erkki
dc.contributor.editorPraks, Jaan
dc.contributor.editorWang, Guangxing
dc.contributor.editorWaser, Lars T.
dc.date.accessioned2022-01-11T13:40:11Z
dc.date.available2022-01-11T13:40:11Z
dc.date.issued2021
dc.identifierONIX_20220111_9783036512525_459
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/76724
dc.description.abstractThe topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economicsen_US
dc.subject.otherforest structure change
dc.subject.otherEBLUP
dc.subject.othersmall area estimation
dc.subject.othermultitemporal LiDAR and stand-level estimates
dc.subject.otherforest cover
dc.subject.otherSentinel-1
dc.subject.otherSentinel-2
dc.subject.otherdata fusion
dc.subject.othermachine-learning
dc.subject.otherGermany
dc.subject.otherSouth Africa
dc.subject.othertemperate forest
dc.subject.othersavanna
dc.subject.otherclassification
dc.subject.otherSentinel 2
dc.subject.otherland use land cover
dc.subject.otherimproved k-NN
dc.subject.otherlogistic regression
dc.subject.otherrandom forest
dc.subject.othersupport vector machine
dc.subject.otherstatistical estimator
dc.subject.otherIPCC good practice guidelines
dc.subject.otheractivity data
dc.subject.otheremissions factor
dc.subject.otherremovals factor
dc.subject.otherPicea crassifolia Kom
dc.subject.othercompatible equation
dc.subject.othernonlinear seemingly unrelated regression
dc.subject.othererror-in-variable modeling
dc.subject.otherleave-one-out cross-validation
dc.subject.otherdigital surface model
dc.subject.otherdigital terrain model
dc.subject.othercanopy height model
dc.subject.otherconstrained neighbor interpolation
dc.subject.otherordinary neighbor interpolation
dc.subject.otherpoint cloud density
dc.subject.otherstereo imagery
dc.subject.otherremotely sensed LAI
dc.subject.otherfield measured LAI
dc.subject.othervalidation
dc.subject.othermagnitude
dc.subject.otheruncertainty
dc.subject.othertemporal dynamics
dc.subject.otherstate space models
dc.subject.otherforest disturbance mapping
dc.subject.othernear real-time monitoring
dc.subject.otherCUSUM
dc.subject.otherNRT monitoring
dc.subject.otherdeforestation
dc.subject.otherdegradation
dc.subject.othertropical forest
dc.subject.othertropical peat
dc.subject.otherforest type
dc.subject.otherdeep learning
dc.subject.otherFCN8s
dc.subject.otherCRFasRNN
dc.subject.otherGF2
dc.subject.otherdual-FCN8s
dc.subject.otherrandom forests
dc.subject.othererror propagation
dc.subject.otherbootstrapping
dc.subject.otherLandsat
dc.subject.otherLiDAR
dc.subject.otherLa Rioja
dc.subject.otherforest area change
dc.subject.otherdata assessment
dc.subject.otheruncertainty evaluation
dc.subject.otherinconsistency
dc.subject.otherforest monitoring
dc.subject.otherdrought
dc.subject.othertime series satellite data
dc.subject.otherBowen ratio
dc.subject.othercarbon flux
dc.subject.otherboreal forest
dc.subject.otherwindstorm damage
dc.subject.othersynthetic aperture radar
dc.subject.otherC-band
dc.subject.othergenetic algorithm
dc.subject.othermultinomial logistic regression
dc.subject.othern/a
dc.titleAdvances in Remote Sensing for Global Forest Monitoring
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-1253-2
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036512525
oapen.relation.isbn9783036512532
oapen.pages352
oapen.place.publicationBasel, Switzerland


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