Search results for " Forest Inventory"

showing 2 items of 2 documents

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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Simplified methods for spatial sampling: application to first-phase data of Italian National Forest Inventory (INFC) in Sicily

2006

Abstract: Methodological approaches able to integrate data from sample plots with cartographic processes are widely applied. Based on mathematic-statistical techniques, the spatial analysis allows the exploration and spatialization of geographic data. Starting from the punctual information on land use types obtained from the dataset of the first phase of the ongoing new Italian NFI (INFC), a spatialization of land cover classes was carried out using the Inverse Distance Weighting (IDW) method. In order to validate the obtained results, an overlay with other vectorial land use data was carried out. In particular, the overlay compared data at different scales, evaluating differences in terms …

Forest inventoryLand useComputer scienceGeographic Information Systems - GISSample (statistics)ForestryLand coverClassification Corine Land Cover Geographic Information Systems - GIS Inverse Distance Weighting - IDW Land cover class Forest InventoryCorine Land CoverLand cover classClassificationSpatializationForest InventoryInverse Distance Weighting - IDWInverse distance weightinglcsh:SD1-669.5lcsh:ForestryCartographyForest@
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