Individual tree measurements by means of digital aerial photogrammetry

Korpela, I. 2004. Individual tree measurements by means of digital aerial photogrammetry. Silva Fennica Monographs 3. 93 p. This study explores the plausibility of the use of multi-scale, CIR aerial photographs to conduct forest inventory at the individual tree level. Multiple digitised aerial photographs are used for manual and semi-automatic 3D positioning of tree tops, for species classification, and for measurements on tree height and crown width. A new tree top positioning algorithm is presented and tested. It incorporates template matching in a 3D search space. Also, a new method is presented for tree species classification. In it, a partition of the image space according to the continuously varying image-object-sun geometry of aerial views is performed. Discernibility of trees in aerial images is studied. The measurement accuracy and overall measurability of crown width by using manual image measurements is investigated. A simulation study is used to examine the combined effects of discernibility and photogrammetric measurement errors on stand variables. The study material contained large-scale colour and CIR image material and 7708 trees from 24 fully mappe

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Acquisition and evaluation of radiometrically comparable multi-footprint airborne LiDAR data for forest remote sensing

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.Peer reviewe

Eddies in motion : visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos

High-resolution thermal infrared (TIR) imaging is opening up new vistas in biosphere-atmosphere heat exchange studies. The rapidly developing unmanned aerial systems (UASs) and specially designed cameras offer opportunities for TIR survey with increasingly high resolution, reduced geometric and radiometric noise, and prolonged flight times. A state-of-the-art science platform is assembled using a Matrice 210 V2 drone equipped with a Zenmuse XT2 thermal camera and deployed over a pristine boreal peatland with the aim of testing its performance in a heterogeneous sedgefen ecosystem. The study utilizes the capability of the UAS platform to hover for prolonged times (about 20 min) at a height of 500ma.g.l. while recording high frame rate (30 Hz) TIR videos of an area of ca. 430 x 340 m. A methodology is developed to derive thermal signatures of near-ground coherent turbulent structures impinging on the land surface, surface temperature spectra, and heat fluxes from the retrieved videos. The size, orientation, and movement of the coherent structures are computed from the surface temperature maps, and their dependency on atmospheric conditions is examined. A range of spectral and wavelet-based approaches are used to infer the properties of the dominant turbulent scene structures. A ground-based eddy-covariance system and an in situ meteorological setup are used for reference.Peer reviewe

Fine-resolution mapping of microforms of a boreal bog using aerial images and waveform-recording LiDAR

Boreal bogs are important stores and sinks of atmospheric carbon whose surfaces are characterised by vegetation microforms. Efficient methods for monitoring their vegetation are needed because changes in vegetation composition lead to alteration in their function such as carbon gas exchange with the atmosphere. We investigated how airborne image and waveform-recording LiDAR data can be used for 3D mapping of microforms in an open bog which is a mosaic of pools, hummocks with a few stunted pines, hollows, intermediate surfaces and mud-bottom hollows. The proposed method operates on the bog surface, which is reconstructed using LiDAR. The vegetation was classified at 20 cm resolution. We hypothesised that LiDAR data describe surface topography, moisture and the presence and depth of field-layer vegetation and surface roughness; while multiple images capture the colours and texture of the vegetation, which are influenced by directional reflectance effects. We conclude that geometric LiDAR features are efficient predictors of microforms. LiDAR intensity and echo width were specific to moisture and surface roughness, respectively. Directional reflectance constituted 4-34 % of the variance in images and its form was linked to the presence of the field layer. Microform-specific directional reflectance patterns were deemed to be of marginal value in enhancing the classification, and RGB image features were inferior to LiDAR variables. Sensor fusion is an attractive option for fine-scale mapping of these habitats. We discuss the task and propose options for improving the methodology.Peer reviewe

Airborne dual-wavelength waveform LiDAR improves species classification accuracy of boreal broadleaved and coniferous trees

Funding Information: This study was conducted on course FOR-254 ‘Advanced Forest Inventory and Management Project’ at the University of Helsinki. Plots IM and OG were measured by students and assistants on course FOR110B with the kind permission of Prof. Pauline Stenberg. Dr. Pekka Kaitaniemi provided phenological observations during LiDAR campaigns, and support by Dr. Antti Uotila was crucial in finding aspen, alder and larch samples in Hyytiälä. The LiDAR and field data in 2013 were collected and processed with funding from the Academy of Finland and Metsämiesten säätiö. Other work by made possible by the University of Helsinki. Publisher Copyright: © 2022, Finnish Society of Forest Science. All rights reserved.Tree species identification constitutes a bottleneck in remote sensing applications. Waveform LiDAR has been shown to offer potential over discrete-return observations, and we assessed if the combination of two-wavelength waveform data can lead to further improvements. A total of 2532 trees representing seven living and dead conifer and deciduous species classes found in Hyytiälä forests in southern Finland were included in the experiments. LiDAR data was acquired by two single-wavelength sensors. The 1064-nm and 1550-nm data were radiometrically corrected to enable range-normalization using the radar equation. Pulses were traced through the canopy, and by applying 3D crown models, the return waveforms were assigned to individual trees. Crown models and a terrain model enabled a further split of the waveforms to strata representing the crown, understory and ground segments. Different geometric and radiometric waveform attributes were extracted per return pulse and aggregated to tree-level mean and standard deviation features. We analyzed the effect of tree size on the features, the correlation between features and the between-species differences of the waveform features. Feature importance for species classification was derived using F-test and the Random Forest algorithm. Classification tests showed significant improvement in overall accuracy (74→83% with 7 classes, 88→91% with 4 classes) when the 1064-nm and 1550-nm features were merged. Most features were not invariant to tree size, and the dependencies differed between species and LiDAR wavelength. The differences were likely driven by factors such as bark reflectance, height growth induced structural changes near the treetop as well as foliage density in old trees.Peer reviewe

Relasphone - Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland ( boreal zone) were in good agreement with reference forest inventory plot data on pine ( R-2 = 0.75, RMSE = 5.33 m(2)/ha), spruce ( R-2 = 0.75, RMSE = 6.73 m(2)/ha) and birch ( R-2 = 0.71, RMSE = 4.98 m(2)/ha), with total relative RMSE ( %) = 29.66%. In Durango, Mexico ( temperate zone), Relasphone stem volume measurements were best for pine ( R-2 = 0.88, RMSE = 32.46 m(3)/ha) and total stem volume ( R-2 = 0.87, RMSE = 35.21 m(3)/ha). Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations.Peer reviewe

MiR-185-5p regulates the development of myocardial fibrosis

Background: Cardiac fibrosis stiffens the ventricular wall, predisposes to cardiac arrhythmias and contributes to the development of heart failure. In the present study, our aim was to identify novel miRNAs that regulate the development of cardiac fibrosis and could serve as potential therapeutic targets for myocardial fibrosis. Methods and results: Analysis for cardiac samples from sudden cardiac death victims with extensive myocardial fibrosis as the primary cause of death identified dysregulation of miR-185-5p. Analysis of resident cardiac cells from mice subjected to experimental cardiac fibrosis model showed induction of miR-185-5p expression specifically in cardiac fibroblasts. In vitro, augmenting miR-185-5p induced collagen production and profibrotic activation in cardiac fibroblasts, whereas inhibition of miR-185-5p attenuated collagen production. In vivo, targeting miR-185-5p in mice abolished pressure overload induced cardiac interstitial fibrosis. Mechanistically, miR-185-5p targets apelin receptor and inhibits the anti-fibrotic effects of apelin. Finally, analysis of left ventricular tissue from patients with severe cardiomyopathy showed an increase in miR-185-5p expression together with pro-fibrotic TGF-beta 1 and collagen I. Conclusions: Our data show that miR-185-5p targets apelin receptor and promotes myocardial fibrosis.Peer reviewe