The main objective of Junttila’s thesis was to investigate the capabilities of multispectral terrestrial lidar in the detection and assessment of tree decline caused by different stressors. This was done by investigating the estimation of a remotely detectable indicator of tree decline, leaf water content (LWC).
The World’s forests are facing novel stress due to climate change. Pest insects and pathogens are shifting towards new latitudes and heat stress is resulting in increased tree mortality and more frequent forest fires globally. Uncertainty in estimating the magnitude of climate change induced forest and tree decline requires new methods for unbiased estimation of tree decline.
The dissertation contributes both to the development of an objective and automatable method for detecting and measuring tree decline in the field, and to the understanding of the relationship between LWC and tree decline with implications to remote sensing.
The potential of terrestrial laser scanning (TLS) in forest applications, both in industry and in national forest inventories (NFIs), has gained increasing awareness in the last two decades. Boosting this development, there has been tremendous research efforts and progress on the topic.
In 2014, a TLS benchmarking project was launched by the European Spatial Data Research Organization (EuroSDR) and hosted by the Finnish Geospatial Research Institute (FGI). 18 groups from Asia, Europe and North America have successfully processed the data and submitted their results for evaluation. Latest results of the work were published in ISPRS Journal of Photogrammetry and Remote Sensing along with open data on the sample plots.
Achievements and remaining barriers to TLS-based forest investigations
Terrestrial laser scanning is an effective technique for measuring forest plots. A terrestrial laser scanner automatically documents its surrounding environment in three-dimensional (3D) space with millions to billions of 3D points. The technology is anticipated to be practically used in forest in-situ observations, e.g. national forest inventories.
According to the benchmarking results, TLS is great at extracting forest attributes of trees that are recorded in the point cloud data. These attributes, i.e. diameter at breast height and stem curve estimates, can be measured at 1-2 cm accuracy level which is close to what is required in practical applications, e.g. national forest inventories. Remaining barriers are mainly from the occlusion effects that prevail and hard to eliminate in forests; therefore, attributes of trees such as tree heights are difficult to estimate.
Open data on sample plot pointclouds
The single- and multi-TLS data, as well as the reference data, of six sample plots of this benchmarking project can be downloaded from here.
The data is opened to anyone who is interested in TLS based forest investigation for non-commercial use. Since the reference information is also opened, users can evaluate their own feature extraction approaches and results by themselves, and compare their own results with the other results reported in the project publication. When making a publication based on the open data set, please reference the date source of the ISPRS journal paper International benchmarking of terrestrial laser scanning approaches for forest inventories (Liang et al 2018).
Getting ready for operational use
The results of this international benchmarking suggest that TLS as well as sophisticated automated algorithms are ready to be used in practice under easy forest conditions, e.g., forests with good visibility or single trees. The operational use of TLS in forest mensuration is a complex process. The current bottleneck is the lack of practical software and it requires time to develop such software. The emerging mobile and personal laser scanning (MLS/PLS) have the potential to solve the occlusion problems of TLS, but have yet to achieve similar accuracy . It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in the benchmarking results can also serve as a reference for other terrestrial point clouds sources.
More information: Research manager Xinlian Liang, firstname.lastname(a)nls.fi
Collaboration between researchers from the Department of Forest Sciences (University of Helsinki) and end users from industry, consulting, and governmental organizations, for example, has been one of the main aims when developing forest applications within the Centre of Excellence in Laser Scanning (CoE-LaSR). Department of Forest Sciences organized a seminar for stakeholders to present the latest research and results using laser scanning for precision forestry. The seminar also reached students and other faculty members from the Department of Forest Sciences apart from the researchers of the CoE-LaSR.
During the afternoon seminar, recent research related to especially TLS and its application in forest mapping and monitoring were presented. The topics included, among others, identifying dead wood, measuring and modelling tree structure and growth as well as health status and wood quality. Furthermore, presentations included experiences from tree species detection and use of augmented reality for harvester drivers.
Intriguing discussion between participants and presenters emerged especially towards the end of the seminar which continued with a panel discussion. The panelists represented Natural Resources Institute, the City of Helsinki, Metsähallitus, Tapio, Metsäteho, Stora Enso and Finnish Forestry Center, all utilizing either laser scanning or products based on laser scanning such as forest resource information. The panelists described how they see laser scanning in the field of forestry and forest sciences, and also pointed out where research efforts are still needed. These included improving accuracy of estimates for species-specific forest inventory attributes and tree-size distributions as well as logging recovery. In addition, measuring quality attributes such as branchiness from standing trees was seen as important research topic by forest industry.
Our novel Hyperspectral Terrestrial Laser Scanning (TLS) dataset has been published as open data.
The laser scanning point cloud dataset consists of 30 individual scans collected as a time series covering a 26 hour time frame. Each point in the laser scanning point cloud contains colour information from several different wavelengths. Ordinary laser scanning data has colour information from one wavelength.
Compared to traditional laser scanning data, hyperspectral data has advantages in for example target recognition and change detection, where it is possible to track changes of color of tree leaves, as in the data published. Also 3D RGB presentations can be produced from data without using separate camera. All laser scanners enable collecting data without external light source, also in the dark.
The data has been utilised in recent research on movement of a birch during a 26 hour period, where it was found out that trees ”sleep” during night. Click the picture below to see an animation on the movement of a tree:
More information: Dr. Eetu Puttonen, eetu.puttonen(a)nls.fi
Personal laser scanners (PLS) lead the way towards compact, agile and flexible solutions for mapping complex environments and challenging locations, such as rugged terrain and complicated urban structures. Our Akhka R2 backpack laser scanning system allows the operator to move in and around the scene while capturing the environment with millimetre precision. Read more about the latest development in the GIM International article Laser Scanner in a Backpack – The Evolution towards All-terrain Personal Laser Scanners.
Picture above: Preparing to collect terrestrial laser scanning data from old Norway spruce forest.
High detail remote sensing technologies, especially laser scanning, and their ability to measure 3D structure of the forest have revolutionized forest mapping and monitoring applications.
“For example in Finland, forest management practices have been based on intensive small-scale forestry because the forests are mainly privately-owned and the size of an average forest holding is relatively small. This creates demanding surroundings for the used remote sensing systems.” New CoE-doctor Ville Kankare says.
The main objective of Kankare’s Ph.D. thesis at the Department of forest sciences, University of Helsinki, was to develop high density laser scanning methodologies for individual tree-level forest mapping. The thesis was accepted in June 2015.
The results of this thesis indicate that high density laser scanning is a vital option for measuring the required individual tree-level attributes, such as tree biomass, timber assortments, quality and stem curve. This type of information will play an important role in the next generation’s forest resource mapping systems especially where the added value for the information is the highest.
The main goal in forest resource mapping is to produce accurate information about forest structure and resources for forest owners, managers and forest industry. The precise knowledge of the biomass (bioenergy potential), logging recoveries and the quality of the available timber plays an essential role for example
when forest owner request tenders for the planned forest management procedures or
when forest industry is optimizing the flow of raw material from forest to the final product.
“The economic value and profitability of forest holding rely on detailed and up-to-date information of forest structure and attributes.“ Kankare concludes.
Picture: Representation of the Scots pine forest measured with terrestrial laser scanning.
More information: Ph.D. Ville Kankare, ville.kankare( at )helsinki.fi
The public examination of the doctoral dissertation of Lingli Zhu will be held on 18 June 2015 at 12.00 at the Aalto University School of Engineering, Lecture hall M1, Otakaari 1, Espoo. The title of the dissertation is A Pipeline for 3D Scene Reconstruction from Point Clouds (Rakennetun ympäristön kolmiulotteinen mallintaminen pistepilvistä). Read more
A novel low-cost multi-sensor mobile laser scanning system has been developed at FGI CoE-LaSR by Anttoni Jaakkola. This work is the focus of his Dr. Sc. thesis, presented in the public examination on 5th June 2015 (Press release in Finnish).
“The results show that mobile laser scanning is a feasible method for various applications of mapping the environment and that even a low-cost system can perform sufficiently in these measurements” Anttoni Jaakkola concludes.
The developed system has been demonstrated on car and UAV (umanned aerial vehicle) platforms. It allows recognizing and classifying different features in the scanned environment, i.e. those of trees, roads and snow depth more accurately compared to the formerly used systems.
With future advances of laser scanning and positioning technologies, it can be expected that price of these systems will further decrease. Widespread adoption of laser scanners, especially in the automotive industry and the new global navigation satellite systems, will significantly reduce the cost of mobile laser scanning components. Nowadays expensive mobile laser scanning systems are almost exclusively owned by mapping companies as benefits of using them requires high rates of utilization and applications with high added-value.
“With future cost reduction, mobile laser scanning will expand to new fields, as also other companies can afford to acquire such systems and utilize them in various applications.” Jaakkola foresees.
Mobile laser scanning is a measurement technology that combines accurate positioning and attitude information from navigation satellites and inertial sensors with distance measurements from a laser scanner into a point cloud that represents the geometry of the environment surrounding the measurement platform. This geometrical information can be utilized in a variety of applications ranging from 3D city modelling and infrastructure maintenance to forestry and environmental monitoring.
Picture: Anttoni Jaakkola (left) demonstrating the UAV mobile laser scanning system
More information: Senior Research Scientist Anttoni Jaakkola, anttoni.jaakkola(at)nls.fi, tel 358 50 3498 108
FGI’s work on benchmarking of terrestrial laser scanning (TLS) methods for forestry applications progresses as planned, and new test datasets have been released in February 2015. More than 10 international groups have already downloaded the test data and more are encouraged to join. The test data can be obtained from the ftp site of the FGI, after sending a request to firstname.lastname@example.org or email@example.com.
The EuroSDR project on international benchmarking of terrestrial laser scanning methods for forestry applications is coordinated by the Centre of Excellence FGI group. The project was launched in 2014 in order to gain understanding on an optimum data processing technique for future automated forest plot inventories. The objective of the project is to evaluate the quality, accuracy and feasibility of automatic, semi-automatic or manual tree extraction methods based on high-density TLS data. The data is collected in a test forest, a southern Boreal Forest in Evo, Finland.
The benchmarking project is targeting on the existing and modified algorithms, and manual measurements from the point cloud data. Meanwhile, the project is also open for all techniques that are in the research phase. National mapping agencies, companies, universities and research organizations are all welcomed to participate in the project and to provide the extracted plotwise parameters. In addition to the final report (in the middle of 2016), joint peer-reviewed journal articles on the statistical comparison results will be prepared. All participants will be invited as co-authors/co-writers in all papers.
The distributed data includes one single-scan and one multi-scan dataset for each of the 24 plots. Read more about the data in the project webpage . The TLS data are exclusively used for this project before the publication of the final project report. After that, the point cloud data will be free of use for non-commercial purposes.
Picture: Multi-scan Terrestrial laser scanning data of a test plot 3D (Picture: Jiri Pyörälä)
Xinlian Liang xinlian.liang(a)nls.fi, Harri Kaartinen harri.kaartinen(a)nls.fi