In this paper a study on the use of multi-temporal LiDAR data to monitor forest changes is presented. LiDAR data acquired at two different times (2007 and 2011) were chosen in order to analyze in details the changes associated to different forest conditions in the temporal domain such as tree growth, tree cuts, and changes in forest volume. The preliminary experimental results show that LiDAR data allow an effective and accurate monitoring of the forest changes.

Dalponte, M.; Liu, S.; Gianelle, D. (2018). Detection of forest changes with multi-temporal LiDAR data. In: 2018IGARSS: International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22-27 July 2018. handle: http://hdl.handle.net/10449/50412

Detection of forest changes with multi-temporal LiDAR data

Dalponte M.
Primo
;
Gianelle D.
Ultimo
2018-01-01

Abstract

In this paper a study on the use of multi-temporal LiDAR data to monitor forest changes is presented. LiDAR data acquired at two different times (2007 and 2011) were chosen in order to analyze in details the changes associated to different forest conditions in the temporal domain such as tree growth, tree cuts, and changes in forest volume. The preliminary experimental results show that LiDAR data allow an effective and accurate monitoring of the forest changes.
LiDAR
Multitemporal LiDAR
Forestry
Change detection
Forest height
Forest volume
2018
Dalponte, M.; Liu, S.; Gianelle, D. (2018). Detection of forest changes with multi-temporal LiDAR data. In: 2018IGARSS: International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22-27 July 2018. handle: http://hdl.handle.net/10449/50412
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/50412
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