04721nam 2201369z- 450 991055733810332120231214133206.0(CKB)5400000000042497(oapen)https://directory.doabooks.org/handle/20.500.12854/76724(EXLCZ)99540000000004249720202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvances in Remote Sensing for Global Forest MonitoringBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (352 p.)3-0365-1252-7 3-0365-1253-5 The 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.Research & information: generalbicsscEnvironmental economicsbicsscforest structure changeEBLUPsmall area estimationmultitemporal LiDAR and stand-level estimatesforest coverSentinel-1Sentinel-2data fusionmachine-learningGermanySouth Africatemperate forestsavannaclassificationSentinel 2land use land coverimproved k-NNlogistic regressionrandom forestsupport vector machinestatistical estimatorIPCC good practice guidelinesactivity dataemissions factorremovals factorPicea crassifolia Komcompatible equationnonlinear seemingly unrelated regressionerror-in-variable modelingleave-one-out cross-validationdigital surface modeldigital terrain modelcanopy height modelconstrained neighbor interpolationordinary neighbor interpolationpoint cloud densitystereo imageryremotely sensed LAIfield measured LAIvalidationmagnitudeuncertaintytemporal dynamicsstate space modelsforest disturbance mappingnear real-time monitoringCUSUMNRT monitoringdeforestationdegradationtropical foresttropical peatforest typedeep learningFCN8sCRFasRNNGF2dual-FCN8srandom forestserror propagationbootstrappingLandsatLiDARLa Riojaforest area changedata assessmentuncertainty evaluationinconsistencyforest monitoringdroughttime series satellite dataBowen ratiocarbon fluxboreal forestwindstorm damagesynthetic aperture radarC-bandgenetic algorithmmultinomial logistic regressionResearch & information: generalEnvironmental economicsTomppo Erkkiedt1322272Praks JaanedtWang GuangxingedtWaser Lars TedtTomppo ErkkiothPraks JaanothWang GuangxingothWaser Lars TothBOOK9910557338103321Advances in Remote Sensing for Global Forest Monitoring3034740UNINA