Search results for "canopy height model"

showing 2 items of 2 documents

Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables

2015

In this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost and flexibility over traditional manned aircraft in forest remote sensing applications in small areas, but they lack range and endurance in larger areas. On the other hand, advances in the processing of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy data on the basis of images acquired using simple lightweight digital camera sensors. In this study, an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the images acquired …

CanopyAerial surveyUAVta1172ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONta1171ComputerApplications_COMPUTERSINOTHERSYSTEMSphotogrammetric surface modelBasal areaAerial photographyaerial imagerylcsh:Forestryforest inventorycanopy height modelRemote sensingta113Forest inventoryEcological ModelingForestryta4112unmanned aerial systemAerial imageryPhotogrammetrylcsh:SD1-669.5Environmental scienceWoody plantSilva fennica
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Airborne-laser-scanning-derived auxiliary information discriminating between broadleaf and conifer trees improves the accuracy of models for predicti…

2020

Managing forests for ecosystem services and biodiversity requires accurate and spatially explicit forest inventory data. A major objective of forest management inventories is to estimate the standing timber volume for certain forest areas. In order to improve the efficiency of an inventory, field based sample-plots can be statistically combined with remote sensing data. Such models usually incorporate auxiliary variables derived from canopy height models. The inclusion of forest type variables, which quantify broadleaf and conifer volume proportions, has been shown to further improve model performance. Currently, the most common way of quantifying broadleaf and conifer forest types is by ca…

0106 biological sciencesCanopysekametsätMean squared errorForest managementBiodiversityClimate changeairborne laser scanningManagement Monitoring Policy and Law010603 evolutionary biology01 natural sciencesforest type mapStatisticscanopy height modelimage-based point cloudsNature and Landscape ConservationForest inventorymetsäsuunnitteluForestryPercentage pointmetsänarviointipuutavaranmittausOrdinary least squaresordinary least squares regression modelsEnvironmental sciencemixed and heterogeneously structured forestkaukokartoitushigh-precision forest inventorymetsänhoitobest fit modelsmerchantable timber volumelaserkeilaus010606 plant biology & botanyForest Ecology and Management
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