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

Aaltomuoto – avain laserkeilainhavaintojen syvällisempään ymmärrykseen

Tieteen tori: Yksityiskohtainen metsävaratiet

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

Assessing spatial variability and estimating mean crown diameter in boreal forests using variograms and amplitude spectra of very-high-resolution remote sensing data

Funding Information: This work was supported by the Academy of Finland under Grant [317387]. We would like to acknowledge assistance from the University of Helsinki and Ilkka Korpela for providing us with the field measured tree data from Hyyti?l?. Publisher Copyright: © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.The retrieval of forest variables from optical remote sensing data using physically-based models is an ill-posed problem and does not make full use of the high spatial resolution imagery that is becoming available globally. A possible solution to this is to use prior information about the retrieved variables, which constrains the possible solutions and reduces uncertainty in forest variable estimation. Therefore, we tried to quantify physically-based parameters that could be retrieved using the second-order statistics of measured and simulated very-high-resolution (pixel size less than 1 m) images of Finnish boreal forests. These forests have a well-defined structure and are usually not closed, i.e. the reflected signal has a considerable contribution from a green forest floor. We retrieved the second-order statistics using variograms and Fourier amplitude spectra. We found, in line with previous studies, that the range of variograms correlates well (r = 0.83) with the mean crown diameter for spatially homogeneous forest patches, and it can be used to estimate crown diameters with reasonable accuracy (RMSE = 0.42 m). We present a novel approach, which uses the Fourier amplitude spectrum to study the spatial structure of a forest. The approach provided encouraging results with the measured data: despite the lower accuracy (RMSE = 0.67 m) compared with variograms, we found that it could also be used to estimate mean crown diameters for heterogeneous forest areas. The Fourier amplitude spectrum approach did not work with the simulated images. Our results highlight the possibility to obtain further information from very-high-resolution images of forests to solve the ill-posed problem of forest variable estimation from optical remote sensing data using physically-based models.Peer reviewe

Analyyttinen hierarkiaprosessi ja sen käyttö puolustusvoimien suunnittelussa

Johdannossa käsitellään päätöksentekoon liittyvän tutkimuksen motiiveja ja tavoitteita sekä kuvataan lyhyesti päätöksenteon tukijärjestelmien perusteita sekä selvitetään tutkimuksen taustoja ja tavoitteita. "Tämän tutkimuksen tavoitteena on esitellä laajalti käytetty analyyttinen päätöksenteon tukijärjestelmä Analytic Hierarchy Process, josta käytetään jatkossa nimitystä analyyttinen hierarkiaprosessi (AHP). Tutkimus jakaantuu kolmeen osaan. Ensimmäisessä osassa selvitetään AHP:n periaatteet yleisellä tasolla puuttumatta syvällisesti matemaattisiin ratkaisuihin. Lisäksi esitellään menetelmän käyttöä helpottavia tietokoneohjelmia ja niiden mahdollisuuksia. Toisessa osassa käsitellään esimerkinomaisesti, julkisiin tietolähteisiin perustuen AHP:n käyttöä neljällä sotilaallisella soveltamisalueella: strateginen suunnittelu, operatiivinen suunnittelu, joukkojen suorituskyvyn arviointi ja asejärjestelmän valinta. Esimerkit on valittu silmälläpitäen sitä, että niistä saisi mahdollisimman monipuolisen kuvan AHP:n eri mahdollisuuksista käytännön sotilaallisissa ongelmissa. Kolmannen osan tavoitteena on osoittaa AHP:n käyttömahdollisuus Puolustusvoimien suunnittelujärjestelmän tukena." Yhteenvedossa kirjoittajat toteavat lopuksi, että tutkimuksen kohteena ollut menetelmä on hyvä työkalu hyödynnettäväksi Puolustusvoimien suunnittelujärjestelmässä. Heidän mukaansa etuja ovat muun muassa analyyttisyys, loogisuus, joustavuus ja havainnollisuus. Lisäksi se on helppokäyttöinen ja soveltuu myös esikuntatyöskentelyyn. "Hyötypotentiaalinsa vuoksi tulisi menetelmän soveltamista käsitellyllä alueella mielestämme tutkia syvällisemmin ja todellisissa päätöstilanteissa.

Attractiveness of Different Districts in Helsinki: Segregation in Terms of Poor Financial and Educational Status of the Residents

The aim of this research is to study attractiveness of different districts in Helsinki. The research tries to find out if there are differences, and on the other hand, similarities between different districts in Helsinki if the financial and educational status of the residents are compared. The main research question is; are there some districts in Helsinki that have a risk to segregate in terms of poor financial and educational status of the residents? Previous researches related to this topic were mainly related to either educational segregation or economic segregation but there is a lack of researches which concentrate on the both aspects at the same time, and take also bad credit history into consideration. This study is based on three different open data sets, two datasets from Paavo and one from Suomen Asiakastieto. In order to find out if there is segregation based on the average income, education level and bad credit history we use clustering analysis and especially dendrograms to analyze the data. In this study dendrograms are used for hierarchical cluster analysis. All of the dendrograms are created in IBM SPSS Statistics 22 -program. The results derived from two dendrograms and a proximity matrix created indicate that in general all of the areas in Helsinki are quite similar with each other. However, the dissimilarity between the extremities is eminent

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

Uncrewed aircraft system spherical photography for the vertical characterization of canopy structural traits

The plant area index (PAI) is a structural trait that succinctly parametrizes the foliage distribution of a canopy and is usually estimated using indirect optical techniques such as digital hemispherical photography. Critically, on-the-ground photographic measurements forgo the vertical variation of canopy structure which regulates the local light environment. Hence new approaches are sought for vertical sampling of traits. We present an uncrewed aircraft system (UAS) spherical photographic method to obtain structural traits throughout the depth of tree canopies. Our method explained 89% of the variation in PAI when compared with ground-based hemispherical photography. When comparing UAS vertical trait profiles with airborne laser scanning data, we found highest agreement in an open birch (Betula pendula/pubescens) canopy. Minor disagreement was found in dense spruce (Picea abies) stands, especially in the lower canopy. Our new method enables easy estimation of the vertical dimension of canopy structural traits in previously inaccessible spaces. The method is affordable and safe and therefore readily usable by plant scientists.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