Book cover Book cover Italian Conference on Geomatics and Geospatial Technologies ASITA 2022: Geomatics for Green and Digital Transition pp 263–274Cite as Low Density ALS Data to Support Forest Management Plans: The Alta Val Di Susa Forestry Consortium (NW Italy) Case Study Download book PDF Download book EPUB Low Density ALS Data to Support Forest Management Plans: The Alta Val Di Susa Forestry Consortium (NW Italy) Case Study E. Ilardi, V. Fissore, R. Berretti, A. Dotta, P. Boccardo & E. Borgogno-Mondino Conference paper First Online: 08 October 2022 96 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1651) Abstract LiDAR systems are evolving very rapidly. In recent years, in fact, the forest sector is largely taking advantage of such evolving progress. Aerial LiDAR (ALS) capability of collecting large amounts of data can directly influence the cost of ordinary in-field forest measurements. A great availability of freely accessible LiDAR data archives from public institutions, often obtained for different purposes than the forestry one, can, however, enormously contribute to forests management. The present study, based on pre-processed and freely available LiDAR-derived DTM and DSM from the Piemonte Region (NW Italy), is a further demonstration that forest planning can be valuable supported by this type of data, that proved to be able to support Forest Settlement Plans redaction. In this study, an estimate (and mapping) of the main forest structural parameters over a test area was achieved with an accuracy consistent with the one ordinarily required by planners when reviewing/setting up a new forest management plan. Moreover, this work proved that free official open data coupled with the current availability of free advanced software for data processing can make this technology easily transferrable to professionals and territory managers.
Low Density ALS Data to Support Forest Management Plans: The Alta Val Di Susa Forestry Consortium (NW Italy) Case Study
Berretti, R.;Borgogno-Mondino, E.
2022-01-01
Abstract
Book cover Book cover Italian Conference on Geomatics and Geospatial Technologies ASITA 2022: Geomatics for Green and Digital Transition pp 263–274Cite as Low Density ALS Data to Support Forest Management Plans: The Alta Val Di Susa Forestry Consortium (NW Italy) Case Study Download book PDF Download book EPUB Low Density ALS Data to Support Forest Management Plans: The Alta Val Di Susa Forestry Consortium (NW Italy) Case Study E. Ilardi, V. Fissore, R. Berretti, A. Dotta, P. Boccardo & E. Borgogno-Mondino Conference paper First Online: 08 October 2022 96 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1651) Abstract LiDAR systems are evolving very rapidly. In recent years, in fact, the forest sector is largely taking advantage of such evolving progress. Aerial LiDAR (ALS) capability of collecting large amounts of data can directly influence the cost of ordinary in-field forest measurements. A great availability of freely accessible LiDAR data archives from public institutions, often obtained for different purposes than the forestry one, can, however, enormously contribute to forests management. The present study, based on pre-processed and freely available LiDAR-derived DTM and DSM from the Piemonte Region (NW Italy), is a further demonstration that forest planning can be valuable supported by this type of data, that proved to be able to support Forest Settlement Plans redaction. In this study, an estimate (and mapping) of the main forest structural parameters over a test area was achieved with an accuracy consistent with the one ordinarily required by planners when reviewing/setting up a new forest management plan. Moreover, this work proved that free official open data coupled with the current availability of free advanced software for data processing can make this technology easily transferrable to professionals and territory managers.
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