BookDOI
National Forest Inventories : pathways for common reporting
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The article was published on 2010-01-01. It has received 596 citations till now.read more
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Journal ArticleDOI
Precision Forestry Using Remote Sensing Techniques: Opportunities and Limitations of Remote Sensing Application in Forestry
Journal ArticleDOI
Extrapolation of in situ data from 1-km squares to adjacent squares using remote sensed imagery and airborne lidar data for the assessment of habitat diversity and extent
Mait Lang,Mait Lang,Ants Vain,Robert G. H. Bunce,Rob H. G. Jongman,Janar Raet,K. Sepp,Valdo Kuusemets,T. Kikas,N. Liba +9 more
TL;DR: The application of remote sensing is described to the extension of field data recorded in 1-km squares to adjacent squares, in order to increase sample number without further field visits, to improve classification accuracy of habitats.
Journal ArticleDOI
Tree Species Site Suitability as a Combination of Occurrence Probability and Growth and Derivation of Priority Regions for Climate Change Adaptation
Ulrike Märkel,Klara Dolos +1 more
TL;DR: This work provided a more comprehensive view on tree species site suitability in biogeographical modeling, and identified priority regions for climate change adaptation under consideration of current stands.
Integrated modelling approach to assess woody biomass supply, demand and environmental impacts of forest management in the EU
Sarah Mubareka,Giorgio Vacchiano,Roberto Pilli,M. Hilferink,Giulia Fiorese,Ragnar Jonsson,Pablo Ruiz Castello,Wouter Nijs,Valerio Avitabile,Jasper van Vliet,Andrea Camia +10 more
Abstract: Forests are at the intersection of European policies on climate, energy and environmental protection and will contribute significantly to the shift of the European economy towards a greater and more sustainable use of renewable resources. Knowledge of the current and future provision and use of woody biomass is necessary to support multiple policies, provide insight into how forest ecosystems and their services will respond to increasing material and energy demand, climate change, and land use competition. The main data source for forest biomass data in the European Union are National Forest Inventories (NFIs). These are carried out based on country-specific requirements and definitions, therefore varying from country to country. The first challenge is therefore the integration of these data into a single modelling platform for simultaneous and seamless processing. Here we describe the efforts of a multi-disciplinary team that has developed modular pan-European modelling set-up to assess the demand and potential supply of woody biomass to the bioeconomy and the impacts of associated harvests using data sourced from heterogeneous NFIs. The modelling framework covers national-level wood-based commodity production and trade, spatially-explicit forest growth and carbon budget, analysis of the role of energy technologies and energy consumption and land-use systems. The hub of this modelling set-up is implemented in a readable and editable modelling script to facilitate dialogue between the modellers. These scripts are where the models meet and exchange data processes for different models, and are capable of resolving issues of thematic and spatial resolution and imputing missing data to enhance the exchange between the models. The philosophy behind this particular setup is one of furthering policy coherence: to inform different and sometimes conflicting policies using the same base data, modelling framework and expertise in a modular way as well as to provide appropriate and consistent outputs, ranging from environmental indicators to indicators about the wood-based industry.
Dissertation
Characterizing tree species in the Northwest Territories using spectral mixture analysis and multi-temporal satellite imagery
TL;DR: In this article, spectral mixture analysis (SMA) was used to identify the dominant tree species near Fort Providence NWT using Landsat-5 Thematic Mapper imagery, achieving an accuracy of 79 % for four species validated against 48 ground plots using multiple-date imagery acquired at different stages of the growing season.
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