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Obtaining statistical data

Projects / Programmes source: ARIS

Processing lidar data (Development and usage of algorithms for mapping and estimation of forest stand biomass and structure using lidar and digital multispectral imagery)

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Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   

Code Science Field
P176  Natural sciences and mathematics  Artificial intelligence 
Keywords
algorithms, machine learning, segmentation, remote sensing, 3D GIS, forest biomass, forest structure
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (10)
no. Code Name and surname Research area Role Period No. of publications
1.  15660  PhD Marko Debeljak  Biology  Researcher  2006 - 2007  313 
2.  16415  PhD Damjan Demšar  Computer science and informatics  Researcher  2004 - 2007  46 
3.  11130  PhD Sašo Džeroski  Computer science and informatics  Head  2004 - 2007  1,204 
4.  03382  PhD Milan Hočevar  Forestry, wood and paper technology  Researcher  2004 - 2007  184 
5.  16067  PhD Andrej Kobler  Forestry, wood and paper technology  Researcher  2004 - 2007  289 
6.  08949  PhD Nada Lavrač  Computer science and informatics  Researcher  2004 - 2007  867 
7.  23326  Peter Ljubič  Computer science and informatics  Researcher  2004 - 2006  28 
8.  27759  PhD Panče Panov  Computer science and informatics  Researcher  2006 - 2007  155 
9.  16302  PhD Ljupčo Todorovski  Computer science and informatics  Researcher  2004 - 2007  443 
10.  22279  PhD Bernard Ženko  Computer science and informatics  Researcher  2007  172 
Organisations (2)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,706 
2.  0404  Slovenian Forestry Institute  Ljubljana  5051673000  12,020 
Abstract
Sound decision-making in the forestry domain and in the environmental protection domain demands a more exhaustive and detailed insight into the extent, structure and trends of forest biomass, which is one of the most important ecosystem attributes. In the context of remote sensing of Earth surface lidar (LIght Detection And Ranging, a laser-based analogue to radar) counts among the most accurate and precise spatial vegetation cover data sources. Due to its technological properties (ability to sense the interior structure of forest stands, three-dimensional data, very high resolution down to 10 cm) lidar surpasses the most recent passive sensors (e.g. Ikonos, Quickbird satellites) in their ability to estimate quantity and structure of forest biomass. The complexity and the high price of 3D data processing are the main obstacles to a faster adoption of lidar in the environmental applications. Commercial lidar data providers offer only some basic (and expensive) data processing services. Algorithms and methods for lidar data processing covering specific information needs of carbon budgeting (in the context of the Kyoto protocol) and forestry in Slovenia will be developed and adapted in the framework of this project. A standardized and enhanced set of lidar-based environmental and forestry related data- and GIS (map) products will be defined and tested. Thus a faster adoption of lidar technology by environmental users will be facilitated, the information usage of lidar data will be maximized, and potential processing costs for the beneficiary (and other institutional users) will be considerably reduced, compared to commercially available data processing services.
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