Browsing by Subject "Laser scanning"

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  • Korpela, Ilkka (2017)
    Forest inventories comprise observations, models and sampling. Airborne LiDAR has established its role in providing observations of canopy geometry and topography. These data are input for estimation of important forest properties to support forestry-related decision-making. A major deficiency in forest remote sensing is tree species identification. This study examines the option of using multi-footprint airborne LiDAR data. Features of such sensor design exist in recently introduced multispectral laser scanners. The first objective was to acquire radiometrically normalized, multi-footprint (11, 22, 44 and 59 cm) waveform (WF) data that characterize 1064nm backscatter reflectance on the interval scale. The second objective was to analyze and validate the data quality in order to draw the correct conclusions about the effect of footprint size on WFs from natural and man-made targets. The experiment was carried out in Finland. Footprint variation was generated by acquiring data at different flying heights and by adjusting the transmitted power. The LiDAR campaign was successful and the data were of sufficient quality, except for a 1 dB trend due to the atmosphere. Significant findings were made conceming the magnitude of atmospheric losses, the linearity of the amplitude scale and the bandwidth characteristics of the receiver, the stability of the transmitter, the precision of the amplitude data and the transmission losses in canopies and power lines, as well as the response of WF attributes to footprint size in forest canopies. Multi-footprint data are a promising approach although the tree species-specific signatures were weak. (C) 2016 Elsevier Inc. All rights reserved.
  • Yu, Xiaowei; Litkey, Paula; Hyyppa, Juha; Holopainen, Markus; Vastaranta, Mikko (2014)
  • Liu, Jingbin; Liang, Xinlian; Hyyppä, Juha; Yu, Xiaowei; Lehtomäki, Matti; Pyörälä, Jiri; Zhu, Lingli; Wang, Yunsheng; Chen, Ruizhi (2017)
    Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency. (C) 2016 The Authors. Published by Elsevier B.V.
  • Tanhuanpää, Topi-Mikko Tapio (Finnish Society of Forest Science, 2016)
    Dissertationes Forestales
    Urban forests provide various ecosystem services. However, they also require fairly intensive management, which can be supported with up-to-date tree-level data. Until recently, the data have been collected using traditional field measurements. Laser scanning (LS) techniques provide efficient means for acquiring detailed three-dimensional (3D) data from the vegetation. The objective of this dissertation was to develop methods for mapping and monitoring urban forests at tree level. In substudy I, a method (MS-STI) utilizing multiple data sources was developed for extracting tree-level attributes. The method combined airborne laser scanning (ALS), field measurements, and tree locations. The field sample was generalized using the non-parametric nearest neighbor (NN) approach. The relative root mean square error (RMSE) of diameter at breast height (DBH) varied between 18.8–33.8%. The performance of MS-STI was assessed in substudy II by applying it to an existing tree register. 88.8% of the trees were successfully detected, and the relative RMSE of DBH for the most common diameter classes varied between 21.7–24.3%. In substudy III, downed trees were mapped from a recreational forest area by detecting changes in the canopy. 97.7% of the downed trees were detected and the commission error was 10%. Species group, DBH, and volume were estimated for all downed trees using ALS metrics and existing allometric models. For the DBH, the relative RMSE was 20.8% and 34.1% for conifers and deciduous trees respectively. Finally, in substudy IV, a method utilizing terrestrial laser scanning (TLS) and tree basic density was developed for estimating tree-level stem biomass for urban trees. The relative RMSE of the stem biomass estimates varied between 8.4–10.5%. The dissertation demonstrates the applicability of LS data in assessing tree-level attributes for urban forests. The methods developed show potential in providing the planning and management of urban forests with cost-efficient and up-to-date tree-level data.
  • Junttila, Oula Samuli; Vastaranta, Mikko Antero; Hämäläinen, Jarno; Latva-käyrä, Petri; Holopainen, Markus Edvard; Hernandez-Clemente, Rocio; Hyyppä, Hannu; Navarro-Cerrillo, Rafael (2017)
    The effect of forest structure and health on the relative surface temperature captured by airborne thermal imagery was investigated in Norway Spruce-dominated stands in Southern Finland. Airborne thermal imagery, airborne scanning light detection and ranging (LiDAR) data and 92 field-measured sample plots were acquired at the area of interest. The surface temperature correlated most negatively with the logarithm of stem volume, Lorey’s height and the logarithm of basal area at a resolution of 254 m2 (9-m radius). LiDAR-derived metrics: the standard deviations of the canopy heights, canopy height (upper percentiles and maximum height) and canopy cover percentage were most strongly negatively correlated with the surface temperature. Although forest structure has an effect on the detected surface temperature, higher temperatures were detected in severely defoliated canopies and the difference was statistically significant. We also found that the surface temperature differences between the segmented canopy and the entire plot were greater in the defoliated plots, indicating that thermal images may also provide some additional information for classifying forests health status. Based on our results, the effects of forest structure on the surface temperature captured by airborne thermal imagery should be taken into account when developing forest health mapping applications using thermal imagery.
  • Pellikka, P.K.E.; Heikinheimo, V.; Hietanen, J.; Schäfer, E.; Siljander, M.; Heiskanen, J. (2018)
    Land cover change takes place in sub-Saharan Africa as forests and shrublands are converted to agricultural lands in order to meet the needs of growing population. Changes in land cover also impact carbon sequestration in vegetation cover with an influence on climate on continental scale. The impact of land cover change on tree aboveground carbon stocks was studied in Taita Hills, Kenya. The land cover change between 1987 and 2011 for four points of time was assessed using SPOT satellite imagery, while the carbon density in various land cover types was assessed with field measurements, allometric biomass functions and airborne laser scanning data. Finally, the mean carbon densities of land cover types were combined with land cover maps resulting in carbon stock values for given land cover types for each point of time studied. Expansion of croplands has been taking place since 1987 and before on the cost of thickets and shrublands, especially on the foothills and lowlands. Due to the land cover changes, the carbon stock of trees was decreasing until 2003, after which there has been an increase. The findings of the research is supported by forest transition model, which emphasizes increase of awareness of forests' role in providing ecosystem services, such as habitats for pollinators, water harvesting and storage at the same time when economic reasons in making land-use choices between cropland and woodland, and governmental legislation supports trees on farms.
  • Junttila, Oula Samuli; Vastaranta, Mikko Antero; Linnakoski, Riikka Marjaana; Sugano, Junko; Kaartinen, Harri; Kukko, Antero; Holopainen, Markus Edvard; Hyyppä, Hannu; Hyyppä, Juha (2017)
    International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
    Climate change is increasing the amount and intensity of disturbance events, i.e. drought, pest insect outbreaks and fungal pathogens, in forests worldwide. Leaf water content (LWC) is an early indicator of tree stress that can be measured remotely using multispectral terrestrial laser scanning (MS-TLS). LWC affects leaf reflectance in the shortwave infrared spectrum which can be used to predict LWC from spatially explicit MS-TLS intensity data. Here, we investigated the relationship between LWC and MS-TLS intensity features at 690 nm, 905 nm and 1550 nm wavelengths with Norway spruce seedlings in greenhouse conditions. We found that a simple ratio of 905 nm and 1550 nm wavelengths was able to explain 84% of the variation (R2) in LWC with a respective prediction accuracy of 0.0041 g/cm2. Our results showed that MS-TLS can be used to estimate LWC with a reasonable accuracy in environmentally stable conditions.
  • Wang, Yunsheng; Kukko, Antero; Hyyppä, Eric; Hakala, Teemu; Pyörälä, Jiri; Lehtomäki, Matti; El Issaoui, Aimad; Yu, Xiaowei; Kaartinen, Harri; Liang, Xinlian; Hyyppä, Juha (2021)
    BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5ha forest was covered in ca. 10min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2-4cm RMSE of the diameter at the breast height estimates, and a 4-7cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.
  • Wang, Yunsheng; Kukko, Antero; Hyyppä, Eric; Hakala, Teemu; Pyörälä, Jiri; Lehtomäki, Matti; El Issaoui, Aimad; Yu, Xiaowei; Kaartinen, Harri; Liang, Xinlian; Hyyppä, Juha (Springer Singapore, 2021)
    Abstract Background Current automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost. Results In the experiment, an approximately 0.5 ha forest was covered in ca. 10 min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2–4 cm RMSE of the diameter at the breast height estimates, and a 4–7 cm RMSE of the stem curve estimates. Conclusions Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.
  • Simula, Juhana (Helsingin yliopisto, 2020)
    Single Photon LiDAR (Light Detection and Ranging) is a novel and promising technology that can make laser scanning faster and cheaper. Compared to typical linear mode LiDARs (LML), SPL (Single Photon LiDAR) can be operated from higher altitude which means wider bandwidth on ground and a larger scanning area at once. Due to capability of SPL systems to create denser point clouds than current typical LML systems, the flight altitude can be higher in SPL which means quick remote sensing data collations abilities over large areas. Additionally, SPL can penetrate thin clouds and fog which gives airborne ALS better time frame as flight can be operated earlier in the morning than with LML. To the best of authors knowledge, this is pioneering research in Finland to analyse the applicability of SPL in Finnish forests and compare it with LML dataset. This thesis focuses on applying and comparing two LiDAR systems (SPL and LML) for extracting individual tree level (ITD) forest inventorying attributes and generating canopy height models in mature forests. Results were validated over 49 field measured plots, located in southern boreal forest. Additionally, the suitability of two crown segmentation methods (local maxima and watershed) were tested in both datasets. Watershed segmentation method yielded more accurate results for tree density and height estimation in both LML and SPL datasets. Tree density was underestimated by 4.7% (rRMSE: 32.3%) for all species. Comparing tree density estimation in different species, it was most accurate in deciduous plots (rRMSE: 17.0%, rBias: -9.5). Tree height estimation with SPL was highly correlated (R 2=0.93) with field-measured height and reliability accurate with underestimation of 3.4% (rRMSE of 7.0%). Comparing the tree height estimation in different species, it was most accurate between pine plots (rRMSE: 1.1%, rBias: 4.9%). In this research, SPL represented reliable and usable point cloud data for forest remote sensing and quality similar to LML. As expected, SPL had more deviation and higher bias compared to LML in tree density but yielded more accurate results for height estimations. Further studies with more accurate geolocated plots and individual tree maps are required. The hypothesis, the applicability of SPL data for forest inventorying and extracting tree density and tree height in mature forests, is valid.