04916nam 22013093a 450 991036756700332120250203235431.09783039212101303921210910.3390/books978-3-03921-210-1(CKB)4100000010106076(oapen)https://directory.doabooks.org/handle/20.500.12854/58170(ScCtBLL)7f8ae726-bc45-487f-9468-33d5fdef042a(OCoLC)1163835832(oapen)doab58170(EXLCZ)99410000001010607620250203i20192019 uu engurmn|---annantxtrdacontentcrdamediacrrdacarrierRemote Sensing of Above Ground BiomassLalit Kumar, Onisimo MutangaMDPI - Multidisciplinary Digital Publishing Institute2019Basel, Switzerland :MDPI,2019.1 electronic resource (264 p.)9783039212095 3039212095 Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local-regional-global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring.History of engineering and technologybicsscNDLMAmulti-angle remote sensingTerraSAR-Xabove ground biomassstem volumeregression analysisground-based remote sensingsensor fusionpasture biomassgrazing managementlivestockmixed forestSPLSRestimation accuracyBidirectional Reflectance Distribution Factorforage cropsLand Surface Phenologyclimate changevegetation indexdry biomassmappingrangeland productivityvegetation indiceserror analysisbroadleavesremote sensingapplicability evaluationultrasonic sensorchlorophyll indexalpine meadow grasslandforest biomassanthropogenic disturbancefractional vegetation coveralpine grassland conservationcarbon mitigationconifershort grassgrazing exclusionMODIS time seriesrandom forestaboveground biomassNDVIAquaCrop modelinversion modelwetlandsfield spectrometryspectral indexyieldfoliage projective coverlidarcorrelation coefficientSahelbiomassdry matter indexNigerLandsatgrass biomassparticle swarm optimizationwinter wheatcarbon inventoryriceforest structure informationMODISlight detection and ranging (LiDAR)ALOS2ecological policiesabove-ground biomassWambiana grazing trialfood securityforest above ground biomass (AGB)Atriplex nummulariaregional sustainabilityCIRed-edgeHistory of engineering and technologyKumar Lalit1369316Mutanga OnisimoScCtBLLScCtBLLBOOK9910367567003321Remote Sensing of Above Ground Biomass4317661UNINA