Investigating Bi-Temporal Hyperspectral Lidar Measurements from Declined Trees - Experiences from Laboratory Test

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Junttila , S , Kaasalainen , S , Vastaranta , M , Hakala , T , Nevalainen , O & Holopainen , M 2015 , ' Investigating Bi-Temporal Hyperspectral Lidar Measurements from Declined Trees - Experiences from Laboratory Test ' , Remote Sensing , vol. 7 , no. 10 , pp. 13863-13877 . https://doi.org/10.3390/rs71013863

Title: Investigating Bi-Temporal Hyperspectral Lidar Measurements from Declined Trees - Experiences from Laboratory Test
Author: Junttila, Samuli; Kaasalainen, Sanna; Vastaranta, Mikko; Hakala, Teemu; Nevalainen, Olli; Holopainen, Markus
Contributor organization: Department of Forest Sciences
Laboratory of Forest Resources Management and Geo-information Science
Forest Health Group
Forest Ecology and Management
Date: 2015-10
Language: eng
Number of pages: 15
Belongs to series: Remote Sensing
ISSN: 2072-4292
DOI: https://doi.org/10.3390/rs71013863
URI: http://hdl.handle.net/10138/159320
Abstract: Global warming is posing a threat to the health and condition of forests as the amount and length of biotic and abiotic disturbances increase. Most methods for detecting disturbances and measuring forest health are based on multi- and hyperspectral imaging. We conducted a test with spruce and pine trees using a hyperspectral Lidar instrument in a laboratory to determine the capability of combined range and reflectance measurements to investigate forest health. A simple drought treatment was conducted by leaving the harvested trees outdoors without a water supply for 12 days. The results showed statistically significant variation in reflectance after the drought treatment for both species. However, the changes differed between the species, indicating that drought-induced alterations in spectral characteristics may be species-dependent. Based on our results, hyperspectral Lidar has the potential to detect drought in spruce and pine trees.
Subject: Lidar
hyperspectral sensors
forest health
drought
declined trees
laser scanning
forestry
TEMPERATURE CONDITION INDEXES
LEAF-AREA INDEX
CLIMATE-CHANGE
WATER-CONTENT
DROUGHT STRESS
SPECTRAL REFLECTANCE
CHLOROPHYLL CONTENT
NATIONAL-FOREST
LIQUID WATER
AVHRR DATA
4112 Forestry
1172 Environmental sciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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