Abstract:Terrestrial Laser Scanning (TLS) can be used to monitor plant dynamics with a frequency of several times per hour and with sub-centimeter accuracy, regardless of external lighting conditions. TLS point cloud time series measured at short intervals produce large quantities of data requiring fast processing techniques. These must be robust to the noise inherent in point clouds. This study presents a general framework for monitoring circadian rhythm in plant movements from TLS time series. Framework performance w… Show more
“…The sun rose 05:14 A.M on April 30 with the highest point at 1:20 P.M and set at 9:26 P.M. After sunset the clusters start to move back toward the initial position. This results show that the TLS measurement station provide point cloud time series with enough accuracy and resolution to monitor short-term dynamics, as previously presented by Puttonen et al (2019) .…”
Section: Examples Of Tls Measurement Data Applicationsupporting
confidence: 82%
“…The main setback in detecting circadian movements with TLS is the requirement of stable environmental conditions, such as no wind and no precipitation, which present a significant technical challenge for long-term monitoring campaigns outdoors. So far, studies outside laboratory conditions are rare ( Zlinszky et al, 2017 ; Puttonen et al, 2019 ). Here, we demonstrate with the second example that short-term structural phenomena are monitored with the measurement station as a future alternative for studying daily dynamics in trees.…”
Section: Examples Of Tls Measurement Data Applicationmentioning
confidence: 99%
“…The feasibility of terrestrial LiDAR data to detect and monitor long-term vegetation dynamics in forest and crop areas have been discussed in previous works, including plant growth ( Yu et al, 2004 , 2006 ; Olivier et al, 2017 ; Guo et al, 2019 ), DBH increase ( Liang et al, 2012 ), AGB change ( Kaasalainen et al, 2014 ; Srinivasan et al, 2014 ) and spring sprouting and flowering ( Olsoy et al, 2014 ; Calders et al, 2015 ). Recently, new studies have also used TLS data for monitoring short-term phenomena, such as circadian rhythms and foliar nyctinasty in different plants and tree species ( Puttonen et al, 2015 , 2016 , 2019 ; Zlinszky et al, 2017 ; Herrero-Huerta et al, 2018 ; Bakay and Moravčík, 2020 ). These studies highlight the high potential of setting up a permanent TLS measurement station as a new non-destructive tool for boreal forest dynamics monitoring.…”
Section: Introductionmentioning
confidence: 99%
“…The measurements were taken in an indoor environment over 2 days. Puttonen et al (2019) reported a new method to monitor circadian rhythms from point cloud time series. They studied overnight movements in two Norway maples from sunset to sunrise with 20-min scan repetitions that resulted in 130 scans in total.…”
Section: Introductionmentioning
confidence: 99%
“…Over the last 5 years, new studies have detected and quantified circadian movements in the tree branches and foliage of fullgrown trees using TLS data acquired with short timescale measurements that have had an hourly or even more frequent scanning repetition rate (Puttonen et al, 2015(Puttonen et al, , 2016(Puttonen et al, , 2019Zlinszky et al, 2017;Herrero-Huerta et al, 2018;Bakay and Moravčík, 2020). Puttonen et al (2016) used TLS time series acquired in two geographically different locations (Finland and Austria) to detect short-term vegetation dynamics.…”
The terrestrial laser scanner (TLS) has become standard technology for vegetation dynamics monitoring. TLS time series have significant underlying application in investigating structural development and dynamics on a daily and seasonal scale. However, the high potential of TLS for the monitoring of long-term temporal phenomena in fully grown trees with high spatial and temporal resolution has not yet been fully explored. Automated TLS platforms for long-term data collection and monitoring of forest dynamics are rare; and long-term TLS time series data is not yet readily available to potential end-user, such as forestry researchers and plant biologists. This work presents an automated and permanent TLS measurement station that collects high frequency and high spatial resolution TLS time series, aiming to monitor short- and long-term phenological changes at a boreal forestry field station (0.006° angular resolution, one scan per hour). The measurement station is the first of its kind considering the scope, accuracy, and length of the time series it produces. The TLS measurement station provides a unique dataset to monitor the 3D physical structure of a boreal forest, enabling new insights into forest dynamics. For instance, the information collected by the TLS station can be used to accurately detect structural changes in tree crowns surrounding the station. These changes and their timing can be linked with the phenological state of plants, such as the start of leaf-out during spring growing season. As the first results of this novel station, we present time series data products collected with the station and what detailed information it provides about the phenological changes in the test site during the leaf sprout in spring.
“…The sun rose 05:14 A.M on April 30 with the highest point at 1:20 P.M and set at 9:26 P.M. After sunset the clusters start to move back toward the initial position. This results show that the TLS measurement station provide point cloud time series with enough accuracy and resolution to monitor short-term dynamics, as previously presented by Puttonen et al (2019) .…”
Section: Examples Of Tls Measurement Data Applicationsupporting
confidence: 82%
“…The main setback in detecting circadian movements with TLS is the requirement of stable environmental conditions, such as no wind and no precipitation, which present a significant technical challenge for long-term monitoring campaigns outdoors. So far, studies outside laboratory conditions are rare ( Zlinszky et al, 2017 ; Puttonen et al, 2019 ). Here, we demonstrate with the second example that short-term structural phenomena are monitored with the measurement station as a future alternative for studying daily dynamics in trees.…”
Section: Examples Of Tls Measurement Data Applicationmentioning
confidence: 99%
“…The feasibility of terrestrial LiDAR data to detect and monitor long-term vegetation dynamics in forest and crop areas have been discussed in previous works, including plant growth ( Yu et al, 2004 , 2006 ; Olivier et al, 2017 ; Guo et al, 2019 ), DBH increase ( Liang et al, 2012 ), AGB change ( Kaasalainen et al, 2014 ; Srinivasan et al, 2014 ) and spring sprouting and flowering ( Olsoy et al, 2014 ; Calders et al, 2015 ). Recently, new studies have also used TLS data for monitoring short-term phenomena, such as circadian rhythms and foliar nyctinasty in different plants and tree species ( Puttonen et al, 2015 , 2016 , 2019 ; Zlinszky et al, 2017 ; Herrero-Huerta et al, 2018 ; Bakay and Moravčík, 2020 ). These studies highlight the high potential of setting up a permanent TLS measurement station as a new non-destructive tool for boreal forest dynamics monitoring.…”
Section: Introductionmentioning
confidence: 99%
“…The measurements were taken in an indoor environment over 2 days. Puttonen et al (2019) reported a new method to monitor circadian rhythms from point cloud time series. They studied overnight movements in two Norway maples from sunset to sunrise with 20-min scan repetitions that resulted in 130 scans in total.…”
Section: Introductionmentioning
confidence: 99%
“…Over the last 5 years, new studies have detected and quantified circadian movements in the tree branches and foliage of fullgrown trees using TLS data acquired with short timescale measurements that have had an hourly or even more frequent scanning repetition rate (Puttonen et al, 2015(Puttonen et al, , 2016(Puttonen et al, , 2019Zlinszky et al, 2017;Herrero-Huerta et al, 2018;Bakay and Moravčík, 2020). Puttonen et al (2016) used TLS time series acquired in two geographically different locations (Finland and Austria) to detect short-term vegetation dynamics.…”
The terrestrial laser scanner (TLS) has become standard technology for vegetation dynamics monitoring. TLS time series have significant underlying application in investigating structural development and dynamics on a daily and seasonal scale. However, the high potential of TLS for the monitoring of long-term temporal phenomena in fully grown trees with high spatial and temporal resolution has not yet been fully explored. Automated TLS platforms for long-term data collection and monitoring of forest dynamics are rare; and long-term TLS time series data is not yet readily available to potential end-user, such as forestry researchers and plant biologists. This work presents an automated and permanent TLS measurement station that collects high frequency and high spatial resolution TLS time series, aiming to monitor short- and long-term phenological changes at a boreal forestry field station (0.006° angular resolution, one scan per hour). The measurement station is the first of its kind considering the scope, accuracy, and length of the time series it produces. The TLS measurement station provides a unique dataset to monitor the 3D physical structure of a boreal forest, enabling new insights into forest dynamics. For instance, the information collected by the TLS station can be used to accurately detect structural changes in tree crowns surrounding the station. These changes and their timing can be linked with the phenological state of plants, such as the start of leaf-out during spring growing season. As the first results of this novel station, we present time series data products collected with the station and what detailed information it provides about the phenological changes in the test site during the leaf sprout in spring.
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