Browsing by Subject "laser scanning"

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  • Puttonen, Eetu; Lehtomäki, Matti; Litkey, Paula; Näsi, Roope; Feng, Ziyi; Liang, Xinlian; Wittke, Samantha; Pandzic, Milos; Hakala, Teemu; Karjalainen, Mika; Pfeifer, Norbert (Frontiers Reseach Foundation, 2019)
    Frontiers in Plant Science
    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 was evaluated using TLS time series collected from two Norway maples (Acer platanoides) and a control target, a lamppost. The results showed that the processing framework presented can capture a plant's circadian rhythm in crown and branches down to a spatial resolution of 1 cm. The largest movements in both Norway maples were observed before sunrise and at their crowns' outer edges. The individual cluster movements were up to 0.17 m (99th percentile) for the taller Norway maple and up to 0.11 m (99th percentile) for the smaller tree from their initial positions before sunset.
  • Korpela, Ilkka; Polvivaara, Antti; Papunen, Saija; Jaakkola, Laura; Tienaho, Noora; Uotila, Johannes; Puputti, Tuomas; Flyktman, Aleksi (2022)
    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.
  • Kaartinen, Harri (Finnish Geodetic Institute, 2013)
    Publications of the Finnish Geodetic Institute
    Comparing different feature extraction methods based on remote sensing or remote sensing systems is difficult as there are but few common data sets or test fields with reference data of high standard available for analysis. State-of-the-art methods and systems are often in still evolving stage and can be run only by the developers themselves. Establishing a high-quality test field is laborious, but once such a test field has been established, it becomes easier to set up the systems to collect data from the field than to collect reference data from new areas. Comparing either different systems or the same system with different parameters is easier when the number of variables is kept to a minimum; the remotely sensed areas are kept constant and any changes in them can be controlled more easily. The benchmarking results provide valuable information to both developers and users of remote sensing data products. The benchmarked feature extraction methods studied included extraction of buildings and individual trees using data from common test fields. The performance of the mobile laser scanning systems was benchmarked using data collected from an established urban test field. In all cases, it was concluded that the primary factor affecting the results was the method or the system, and this enabled a high degree of comparability for the results of the given extraction or mapping tasks. Erilaisten kaukokartoitukseen perustuvien kohdemallinnusmenetelmien tai kaukokartoitusjärjestelmien vertailu on vaikeaa koska yhteisesti käytettävissä olevia aineistoja tai testikenttiä, joista on saatavissa korkealaatuista referenssiaineistoa, on olemassa vain vähän. Uusimmat menetelmät ja järjestelmät ovat usein vielä kehitysvaiheessa ja niiden käyttö onnistuu vain niiden kehittäjiltä. Korkealaatuisen testikentän tekeminen on työlästä, mutta kun testikenttä on perustettu, on helpompaa kerätä aineistoja siltä eri järjestelmillä kuin mitata referenssiaineistoa uusilta alueilta. Eri järjestelmien tai yhden järjestelmän eri asetuksien vertailu on helpompaa kun muuttujien määrä on mahdollisimman pieni; tässä tapauksessa kaukokartoitetut alueet pysyvät vakiona ja mahdolliset muutokset niissä ovat helpommin kontrolloitavissa. Vertailujen tulokset antavat hyödyllistä tietoa sekä kaukokartoitustuotteiden kehittäjille että niiden käyttäjille. Vertaillut kohdemallinnusmenetelmät olivat rakennusten ja yksittäisten puiden mallinnus yhteisiltä testikentiltä kerättyjä aineistoja käyttäen. Liikkuvien laserkeilausjärjestelmien suorituskykyä vertailtiin käyttäen perustetulta kaupunkitestikentältä kerättyjä aineistoja. Kaikissa tapauksissa todettiin että tärkein tuloksiin vaikuttava tekijä oli menetelmä tai järjestelmä itse, joten annetun mallinnus- tai kartoitustehtävän tulokset ovat hyvin vertailukelpoisia.
  • Järnstedt, Janne (Helsingfors universitet, 2010)
    The objective of this study was to develop a method for estimation of forest stand variables and updating the forest resource data, based on a well known and widely used method among forest sector, aerial photography. The second objective was to produce information of cost-effectiveness and accuracy of digital surface model (DSM) generated from very high resolution aerial images in comparison of methods based on aerial laser scanning (ALS). The study area covering circa 2000 hectares is located in state owned forest in Hämeenlinna, Southern Finland. The study material consisted of 85 digitised and orthorectified colour-infrared (CIR) aerial photographs, LiDAR measurements of the corresponding area and field measurements of 402 concentric circular plots. Both the remote sensing data and the field measurements were acquired in 2009. In this study, the accuracy of DSM generated from very high resolution CIR - aerial images was examined in the estimation of forest stand variables. Estimation of forest stand variables was made using non-parametric k-nearest neighbour method. Sequential forward selection was used for selecting features from remote sensing data and the examination of accuracy was done with cross validation. The variables examined were mean diameter, basal area, mean height, dominant height and mean volume. Relative RMSE -values of DMS estimation were at the best with mean diameter, basal area, mean height, dominant height and mean volume 33,67 %, 36,23 %, 25,33 %, 23,53 % and 40,39 %. For the reference ALS-data, relative RMSE-values were 25,26 %, 27,89 %, 19,94 %, 16,76 % ja 31,26 %. Photogrammetric DSM was best suited for estimating dominant and mean height and produced estimates slightly more inaccurate than those of reference ALS-data. When estimating mean diameter, photogrammetric DSM was slightly better, but at mean volume estimation, ALS-data proved again to be a little more a accurate than photogrammetric DSM. At basal area estimation, ALS-data gave considerably better results than photogrammetric DSM. This research showed that the photogrammetric DSM suits well for updating the forest resource data, and also satisfies the requirements in a more economic way.
  • Kankare, Ville; Joensuu, Marianna; Vauhkonen, Jari; Holopainen, Markus; Tanhuanpaa, Topi; Vastaranta, Mikko; Hyyppa, Juha; Hyyppa, Hannu; Alho, Petteri; Rikala, Juha; Sipi, Marketta (2014)
  • Niemi, Mikko (2021)
    The pulse density of airborne Light Detection and Ranging (LiDAR) is increasing due to technical developments. The trade-offs between pulse density, inventory costs, and forest attribute measurement accuracy are extensively studied, but the possibilities of high-density airborne LiDAR in stream extraction and soil wetness mapping are unknown. This study aimed to refine the best practices for generating a hydrologically conditioned digital elevation model (DEM) from an airborne LiDAR -derived 3D point cloud. Depressionless DEMs were processed using a stepwise breaching-filling method, and the performance of overland flow routing was studied in relation to a pulse density, an interpolation method, and a raster cell size. The study area was situated on a densely ditched forestry site in Parkano municipality, for which LiDAR data with a pulse density of 5 m–2 were available. Stream networks and a topographic wetness index (TWI) were derived from altogether 12 DEM versions. The topological database of Finland was used as a ground reference in comparison, in addition to 40 selected main flow routes within the catchment. The results show improved performance of overland flow modeling due to increased data density. In addition, commonly used triangulated irregular networks were clearly outperformed by universal kriging and inverse-distance weighting in DEM interpolation. However, the TWI proved to be more sensitive to pulse density than an interpolation method. Improved overland flow routing contributes to enhanced forest resource planning at detailed spatial scales.
  • Junttila, Samuli; Kaasalainen, Sanna; Vastaranta, Mikko; Hakala, Teemu; Nevalainen, Olli; Holopainen, Markus (2015)
    Global warming is posing a threat to the health and condition of forests as the amount and length of biotic and abiotic disturbances increase. Most methods for detecting disturbances and measuring forest health are based on multi- and hyperspectral imaging. We conducted a test with spruce and pine trees using a hyperspectral Lidar instrument in a laboratory to determine the capability of combined range and reflectance measurements to investigate forest health. A simple drought treatment was conducted by leaving the harvested trees outdoors without a water supply for 12 days. The results showed statistically significant variation in reflectance after the drought treatment for both species. However, the changes differed between the species, indicating that drought-induced alterations in spectral characteristics may be species-dependent. Based on our results, hyperspectral Lidar has the potential to detect drought in spruce and pine trees.
  • Jaakkola, A (Aalto University, 2015)
    Aalto University publication series DOCTORAL DISSERTATIONS
  • Junttila, Samuli; Vastaranta, Mikko; Liang, Xinlian; Kaartinen, Harri; Kukko, Antero; Kaasalainen, Sanna; Holopainen, Markus; Hyyppä, Hannu; Hyyppä, Juha (2017)
    Decreased leaf moisture content, typically measured as equivalent water thickness (EWT), is an early signal of tree stress caused by drought, disease, or pest insects. We investigated the use of two terrestrial laser scanners (TLSs) employing different wavelengths for improving the understanding how EWT can be retrieved in a laboratory setting. Two wavelengths were examined for normalizing the effects of varying leaf structure and geometry on the measured intensity. The relationship between laser intensity features, using red (690 nm) and shortwave infrared (1550 nm) wavelengths, and the EWT of individual leaves or groups of needles were determined with and without intensity corrections. To account for wrinkles and curvatures of the leaves and needles, a model describing the relationship between incidence angle and backscattered intensity was applied. Additionally, a reflectance model describing both diffuse and specular reflectance was employed to remove the fraction of specular reflectance from backscattered intensity. A strong correlation (R-2 = 0.93, RMSE = 0.004 g/cm(2)) was found between a normalized ratio of the two wavelengths and the measured EWT of samples. The applied intensity correction methods did not significantly improve the results of the study. The backscattered intensity responded to changes in EWT but more investigations are needed to test the suitability of TLSs to retrieve EWT in a forest environment.
  • Hirvonen, Martti (Helsingfors universitet, 2013)
    Determining the market value of forest properties is needed for several purposes. In Finland the most used methods for valuation of forests are summation approach, income approach and market approach. Real estate valuation methods are standardized by the International Valuation Standards Council (IVSC). The council publishes standards that have been the premise for real estate valuation also in Finland. However, standard for the valuation of forests doesn’t exist due to significant problems in every method used. From International Valuation Standards Councils perspective valuation should always be market-based. Figures for the calculations should be derived from the market. This has been problematic for forest properties as the specific forest inventory data has been too expensive and difficult to collect. The new forest inventory data system of The Finnish Forest Centre, which is based on airborne laser scanning, creates new possibilities for combining the data with the market prices. This enables a better examination of the valuation methods used and a possibility for the creation of a standardized method. The purpose of this study was to compare the attributes and suitability of the most used valuation methods when determining the market value of forest properties. Research material of this study consists of 15 representative forest property transactions (areas over 10 hectares) from Central Finland and the laser scanning based inventory data of these properties. The attributes investigated were the size of correction from total value when using summation approach, the internal rate of return in the income approach, possible net income for the near future and the accuracy of these valuation methods. In addition, taxation of forest revenues, transfer taxes, administration costs of forests and trade costs were applied in examination of these methods. Processing and calculations of data were carried out with MELA, Motti, Tforest and Excel programs. The average internal rate of return was 5,3 percent and median 4,3 percent, which is similar to previous studies. Investments in forest properties are categorized to an average risk-return investment class. The correction from total value when using summation approach was similar to previous studies as it varied from -2 to -60 percent and was -26 percent on average (and -13 percent when expectation values were left out). The possible net income from these forest properties from the period of five years could cover 64 percent of market prices; however notable differences were among properties. When taking taxes, administration and trade costs into account the average internal rate of return sets down between 3 - 4 percent. The total value correction in summation approach is only -4,5 percent on average (+12,9 percent without expectation values). The problems of the valuation methods can be seen when looking at the accuracy of the methods. Standard deviation of every method varies from 25 - 35 percent when comparing them to the market values. Notable is that with a very simple method; multiplying the growing stock with the average stumpage prices, the results are as accurate as with more complex methods. The most accurate results for the whole research material were calculated with the income approach using 5 percent interest rate. Also using the summation approach and taking taxes, administration and trade costs into account was very accurate. More research is still needed for every method. Perhaps in practical valuation tasks the market value of forest properties should be investigated using multiple methods side by side, as IVSC has proposed. The results of this study are similar to previous studies and therefore support the intention for combining the new laser scanning based forest inventory data to the market prices. The use and research of extensive and up-to-date market data of forest properties could also open new possibilities in valuation of non-market benefits.
  • Rintarunsala, Juhani (Helsingin yliopisto, 2018)
    As an internationally important topic for forestry, climate change has long been a topic of concern, as well as the ability of the forests to accumulate carbon. In addition, in Finland, these values have essentially been associated with the economic, cultural and social value of forests. In view of these values, it is important to be able to maintain forest resources at a sustainable level for all the different sectors. As far as sustainability is concerned, knowing the current state of forests is significant. This information is collected through the inventory of forests, and today it is mainly based on different remote sensing methods. In order to support reliable decisionmaking, forest information needs to be up-to-date and accurate. The aim of the thesis was to examine the accuracy of different tree attribute estimates and compare them between themselves and to investigate the accuracy of growth models in producing the estimates. In addition, the aim was to evaluate the effects of the accuracy of the remote sensing estimates on the determination of the timing harvests. The research area was located in boreal coniferous forest zone in Southern Finland, Evo (61.19˚N, 25.11˚E). The area comprised a 5 km x 5 km area, comprising about 2000 hectares of forest treated in different ways. Field measurements, aerial imagery, and airborne laser scanning data were generated using estimates for forest inventory attributes based on three different statistical features derived from the remote sensing data in the preparation of estimates. The forest inventory attributes were volume V, basal area-weighted mean diameter Dg, basal area-weighted mean height, number of the stems per hectare, and basal area G. In the prediction of the forest inventory attributes a non-parametric k-NN method was used, and random forest -algorithm was used in the selection of the nearest neighbors. Growth modeling was carried out using SIMO software. It can be seen from the results that, as a rule, more accurate results are obtained by producing airborne lasers canning estimates than by aerial imagery estimates. In addition, prediction precisions were better in coniferous trees than in deciduous trees. In forest inventory attribute estimates, especially the basal area G and volume V are generally underestimated, which is likely to delay the scheduled timing of harvests. Updating remote sensing estimates with growth models would appear to yield more biased estimates compared to the new remote sensing inventory.
  • Niemi, Mikko (Helsingfors universitet, 2013)
    Accurate and economical remote sensing method with good temporal resolution is required for mapping up-to-date information about the forest resources. Detecting forests by optical satellite images is an inaccurate procedure with the saturation problem. Airborne laser scanning (ALS) is a precise application, but the inventory process is slow and expensive. Recently the new synthetic aperture radar (SAR) satellites with a high spatial resolution have caused a renaissance of radar-based remote sensing. The purpose of the master’s thesis was to investigate the accuracy of forest mapping by radargrammetric processing of TerraSAR-X satellite images. The radargrammetry is based on stereoscopic measurement, which calculates 3D coordinates for corresponding points of the SAR image pair. In the research an area-based approach (ABA) was utilized to estimate forest attributes from the 3D points, and digital terrain model (DTM) produced by ALS was used to calculate height of the corresponding points. In plot-level the relative RMSEs for stem volume, biomass, basal area and mean height were 40.3 %, 39.9 %, 34.0 % and 15.9 %. In stands larger than 2 hectares the corresponding RMSEs were 20.2 %, 20.4 %, 36.1 % and 6.9 %. It’s notable that the estimation of basal area didn’t improve in stand-level at all. According to the research SAR radargrammetry is a precise technology to estimate forest canopy height, but the mapping of forest density is very unclear. Nevertheless the results about the estimation accuracy of forest stem volume and biomass by SAR radargrammetry were clearly better than the comparable estimation accuracy of optical satellite images.
  • Kukko, Antero (Finnish Geodetic Institute, 2013)
    Publications of the Finnish Geodetic Institute
    Laser scanning is a surveying technique used for mapping topography, vegetation, urban areas and infrastructure, ice, and other targets of interest. Its application on a terrestrial mobile platform is a promising method for effectively collecting three-dimensional data for complex environments and for producing model information for location-based services necessitating rapidly collected and up-to-date data. Development of mobile laser scanning (MLS) systems for such purposes is presented in this study. Different aspects of this technology were analyzed in laboratory experiments, simulations and field tests, in order to understand their effects on the ranging, intensity and point cloud data, especially in terms of point distribution and accuracy. In order to validate the performance of the developed ROAMER and AKHKA MLS systems, various three-dimensional mapping tasks were performed during an international benchmarking test, as well as in the field in numerous projects. The results showed that the proposed systems can reliably provide accurate data. It has also been shown that the various modalities of the systems allow data acquisition in numerous application scenarios and environments not previously possible. MLS improves the data output compared to terrestrial laser scanning (TLS) and outperforms airborne laser scanning (ALS) in ranging precision and point density. As a result, MLS is well suited to fill the gap between these two previously dominant 3D data acquisition techniques. Laserkeilaus on mittaustekniikka, jota käytetään maaston topografian kasvillisuuden, rakennettujen alueiden, infrastruktuurin, jään ja muiden kohteiden kartoitukseen. Tekniikan soveltaminen liikkuvalle alustalle on lupaava menetelmä monimuotoisten ympäristöjen tehokkaaseen kolmiulotteiseen mittaamiseen ja mallinnustiedon tuottamiseen paikkatietopalveluihin, jotka edellyttävät tiedon nopeaa hankintaa ja ajantasaisuutta. Tässä tutkimuksessa kehitettiin liikkuvia laserkeilausjärjestelmiä (MLS). Eri tekijöiden vaikutuksia etäisyys- ja intensiteettihavaintoihin, pistejakaumaan ja tarkkuuteen selvitettiin laboratoriokokein, simuloimalla ja koetöin. Tutkimuksessa kehitettyjen ROAMER ja AKHKA MLS-järjestelmien suorituskykyä kolmiulotteisen mittaustiedon tuottamiseen erilaisissa kartoitustehtävissä tutkittiin kansainvälisessä vertailututkimuksessa kaupunkitestikentän avulla, mutta lisäksi käytännön sovelluksissa useassa eri projektissa. Tutkimuksen tulokset osoittavat, että kehitetyt MLS järjestelmät tuottavat tarkkaa tietoa luotettavasti. Järjestelmien monikäyttöisyys mahdollistaa aineistonhankinnan eri sovellustapauksissa ja ympäristöissä tavalla, joka ei ole aikaisemmin ollut mahdollista. Liikkuva laserkeilaus parantaa merkittävästi mittauksen tehokkuutta maalaserkeilaukseen verrattuna, ja ylittää lentolaserkeilauksen suorituskyvyn etäisyysmittauksen tarkkuudessa ja pistetiheydessä. Liikkuva laserkeilaus tarjoaakin näitä kahta aikaisemmin vallitsevaa 3D-mittausteknologiaa hyvin täydentävän kartoitusmenetelmän.
  • Matikainen, Leena (Finnish Geodetic Institute, 2012)
    Publications of the Finnish Geodetic Institute
    There is a growing demand for high-quality spatial data and for efficient methods of updating spatial databases. In the present study, automated object-based interpretation methods were developed and tested for coarse land use mapping, detailed land cover and building mapping, and change detection of buildings. Various modern remotely sensed datasets were used in the study. An automatic classification tree method was applied to building detection and land cover classification to automate the development of classification rules. A combination of a permanent land cover classification test field and the classification tree method was suggested and tested to allow rapid analysis and comparison of new datasets. The classification and change detection results were compared with up-to-date map data or reference points to evaluate their quality. The combined use of airborne laser scanner data and digital aerial imagery gave promising results considering topographic mapping. In automated building detection using laser scanner and aerial image data, 96% of all buildings larger than 60 m2 were correctly detected. This accuracy level (96%) is compatible with operational quality requirements. In automated change detection, about 80% of all reference buildings were correctly classified. The overall accuracy of a land cover classification into buildings, trees, vegetated ground and non-vegetated ground using laser scanner and aerial image data was 97% compared with reference points. When aerial image data alone were used, the accuracy was 74%. A comparison between first pulse and last pulse laser scanner data in building detection was also carried out. The comparison showed that the use of last pulse data instead of first pulse data can improve the building detection results. The results yielded by automated interpretation methods could be helpful in the manual updating process of a topographic database. The results could also be used as the basis for further automated processing steps to delineate and reconstruct objects. The synthetic aperture radar (SAR) and optical satellite image data used in the study have their main potential in land cover monitoring applications. The coarse land use classification of a multitemporal interferometric SAR dataset into built-up areas, forests and open areas lead to an overall accuracy of 97% when compared with reference points. This dataset also appeared to be promising for classifying built-up areas into subclasses according to building density. Important topics for further research include more advanced interpretation methods, new and multitemporal datasets, optimal combinations of the datasets, and wider sets of objects and classes. From the practical point of view, work is needed in fitting automated interpretation methods in operational mapping processes and in further testing of the methods. Laadukkaan paikkatiedon tarve kasvaa jatkuvasti, ja paikkatietokantojen ajantasaistukseen tarvitaan tehokkaita menetelmiä. Tässä tutkimuksessa käytettiin useita uudenaikaisia kaukokartoitusaineistoja. Niiden pohjalta kehitettiin ja testattiin automaattisia, objektipohjaisia tulkintamenetelmiä yleispiirteiseen maankäytön luokitteluun, yksityiskohtaiseen maanpeitteen ja rakennusten kartoitukseen sekä rakennusten muutostulkintaan. Rakennusten tulkintaan ja maanpeiteluokitteluun sovellettiin automaattista luokittelupuumenetelmää, jonka avulla voidaan automatisoida luokittelusääntöjen kehittäminen. Uusia aineistoja voidaan analysoida ja vertailla nopeasti, kun luokittelupuumenetelmää käytetään yhdessä pysyvän maanpeiteluokittelutestikentän kanssa. Luokittelu- ja muutostulkintatuloksia verrattiin niiden laadun arvioimiseksi ajantasaiseen kartta-aineistoon tai referenssipisteisiin. Ilmalaserkeilausaineisto ja digitaalinen ilmakuva-aineisto yhdessä antoivat lupaavia tuloksia maastotietojen kartoitusta ajatellen. Automaattisessa rakennusten tulkinnassa 96 % kaikista yli 60 m2:n rakennuksista tunnistettiin oikein. Tämä tarkkuustaso (96 %) vastaa käytännön laatuvaatimuksia. Automaattisessa muutostulkinnassa noin 80 % kaikista referenssirakennuksista luokiteltiin oikein. Maanpeiteluokittelussa neljään luokkaan saavutettiin laserkeilaus- ja ilmakuva-aineistoa käyttäen 97 %:n kokonaistarkkuus referenssipisteisiin verrattuna. Pelkkää ilmakuva-aineistoa käytettäessä tarkkuus oli 74 %. Tutkimuksessa verrattiin myös ensimmäiseen ja viimeiseen paluupulssiin perustuvia laserkeilausaineistoja rakennusten tulkinnassa. Vertailu osoitti, että viimeisen paluupulssin käyttö ensimmäisen sijasta voi parantaa tulkintatuloksia. Automaattisten tulkintamenetelmien tuloksista voisi olla hyötyä maastotietojen manuaalisessa ajantasaistusprosessissa tai lähtötietoina kohteiden automaattisessa rajauksessa ja mallinnuksessa. Tutkimuksessa käytettyjen synteettisen apertuurin tutkan (SAR) tuottamien kuvien ja optisen satelliittikuvan tärkeimmät hyödyntämismahdollisuudet liittyvät maanpeitteen kartoitukseen. Yleispiirteisessä maankäyttöluokittelussa kolmeen luokkaan saavutettiin moniaikaista interferometrista SAR-aineistoa käyttäen 97 %:n kokonaistarkkuus referenssipisteisiin verrattuna. Aineisto osoittautui lupaavaksi myös rakennettujen alueiden jatkoluokitteluun rakennustiheyden perusteella. Jatkotutkimusten kannalta tärkeitä aiheita ovat edistyneemmät tulkintamenetelmät, uudet ja moniaikaiset aineistot, eri aineistojen optimaalinen yhdistäminen sekä useampien kohteiden ja luokkien tarkastelu. Käytännön näkökulmasta työtä tarvitaan automaattisten tulkintamenetelmien sovittamiseksi operatiivisiin kartoitusprosesseihin. Myös menetelmien testausta on jatkettava.
  • Luoma, Ville; Yrttimaa, Tuomas; Kankare, Ville; Saarinen, Ninni; Pyorala, Jiri; Kukko, Antero; Kaartinen, Harri; Hyyppa, Juha; Holopainen, Markus; Vastaranta, Mikko (2021)
    Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.
  • Karila, Kirsi; Matikainen, Leena; Litkey, Paula; Hyyppä, Juha; Puttonen, Eetu (Taylor & Francis, 2018)
    International Journal of Remote Sensing
    Multispectral airborne laser scanning (MS-ALS) sensors are a new promising source of data for auto-mated mapping methods. Finding an optimal time for data acquisition is important in all mapping applica-tions based on remotely sensed datasets. In this study, three MS-ALS datasets acquired at different times of the growing season were compared for automated land cover mapping and road detection in a suburban area. In addition, changes in the intensity were studied. An object-based random forest classi-fication was carried out using reference points. The overall accuracy of the land cover classification was 93.9% (May dataset), 96.4% (June) and 95.9% (August). The use of the May dataset acquired under leafless conditions resulted in more complete roads than the other datasets acquired when trees were in leaf. It was concluded that all datasets used in the study are applicable for suburban land cover map-ping, however small differences in accuracies between land cover classes exist.
  • Puttonen, Eetu (Finnish Geodetic Institute, 2012)
    Publications of the Finnish Geodetic Institute
    Remote sensing is a study that provides information on targets of interest without direct interaction with them. Generally, the term is used for measurement techniques that detect electro-magnetic radiation emitted or reflected from the targets. Commonly used wavelength ranges include visible, infra-red, microwaves, and thermal bands. This information can be exploited to determine the structural and spectral properties of targets. Remote sensing techniques are typically utilized in mapping solutions, environment monitoring, target recognition, change detection, and in creation of physical models. In Finland, remote sensing research is of specific importance in forest sciences and industry as they need precise information on tree quantity and quality over large forest ranges. Tree species information on individual tree level is an important parameter to achieve this goal. The aim of this thesis is to study how individual tree species information can be extracted with multiple source remote sensing data. The aim is achieved by combining spatial and spectral remote sensing data. Structural properties of individual trees are determined from three dimensional point clouds collected with laser scanners. Spectral properties of trees are collected with cameras or spectrometers. The thesis consists of four separate studies. The first study examined how shading information of trees canopies could be exploited to improve tree species classification in data collected with airborne sensors. The second study examined the classification performance of a low-cost, multi-sensor, mobile mapping system. The third study investigated the classification performance and accuracy of a novel, active hyperspectral laser scanner. Finally, the fourth study evaluated the suitability of artificial surfaces as on-site intensity calibration targets. The results of the three classification studies showed that the use of combined point cloud and spectral information yielded the best classification results in all study cases when compared against classification results obtained with only structural or spectral information. Moreover, the studies showed that the improved results could be achieved with a low total number of mixed structural and spectral classification parameters. The fourth study showed that the artificial surfaces work as calibration surfaces only in limited cases. The main outcome of the thesis was that the active remote sensing systems measuring multiple wavelengths simultaneously should be promoted. They have a significant potential to improve tree species classification performance even with a few application-specific wavelengths. Kaukokartoitus on tutkimusala, jossa tutkittavia kohteita havainnoidaan ilman suoraa vuorovaikutusta. Yleisimmin kaukokartoituksella tarkoitetaan mittaustekniikoita, joilla havaitaan kohteiden lähettämää tai heijastamaa elektromagneettista säteilyä. Havainnointi tapahtuu tavallisesti näkyvän valon, infrapunan, mikroaaltojen ja lämpösäteilyn aallonpituusalueilla. Havaittua säteilyä voidaan hyödyntää kohteiden rakenteellisten ja spektraalisten ominaisuuksien määrittämisessä. Kaukokartoitusmenetelmiä käytetään tyypillisesti kartoitussovelluksissa, ympäristönseurannassa, kohde- ja muutostulkinnassa sekä fysikaalisten ilmiöiden mallinnuksessa. Kaukokartoitustutkimuksella on tärkeä osa suomalaisessa metsäntutkimuksessa ja -teollisuudessa. Molemmat tarvitsevat tarkkaa tietoa puuston määrästä ja laadusta suurilta metsäalueilta. Yksittäisten puiden lajitulkinta on tärkeä parametri tavoitteen saavuttamisessa. Väitöskirjatutkimuksen tarkoituksena on selvittää, kuinka yksittäisten puiden lajitieto voidaan määrittää eri mittauslaitteilla kerätystä kaukokartoitusaineistosta käyttämällä samanaikaisesti puustoa kuvaavia muotopiirteitä ja spektrivastetta. Muotopiirteiden keräys tehdään laserkeilaimilla. Spektrivasteet kerätään kameroilla tai spektrometreillä. Väitöskirjan sisältö koostuu neljästä erillisestä tutkimuksesta. Ensimmäisessä tutkimuksessa selvitetään, kuinka ilmasta kerättyä tietoa puiden latvustojen varjostumisesta voidaan hyödyntää puulajitulkinnassa. Toisessa tutkimuksessa arvioidaan puulajitulkinnan toteutettavuutta aineistosta, joka on kerätty edullisista komponenteista kootulla liikkuvalla kaukokartoituslaitteistolla. Kolmas tutkimus tarkastelee uuden, aktiivisesti mittaavan hyperspektrilaserin suorituskykyä ja tarkkuutta puulajitulkinnassa. Neljännessä tutkimuksessa selvitetään voidaanko rakennettuja pintoja hyödyntää intensiteetin maastokalibrointikohteina. Kaikki kolme luokittelututkimusta osoittivat yhdistetyn pistepilvi- ja spektriaineiston suoriutuvan parhaimmin lajitulkinnasta, kun tuloksia verrataan pelkästä rakenne- tai spektrisestä aineistosta laskettuihin tuloksiin. Lisäksi parantuneet tulokset saavuttiin yhdistämällä vain muutamaa rakenne- ja spektri-luokitteluparametria kerrallaan. Neljännen tutkimuksen tulokset osoittivat, että rakennetut pinnat soveltuvat kalibraatiokohteiksi vain rajatuissa tapauksissa. Väitöskirjan tärkein johtopäätös on, että aktiivisten, useaa aallonpituutta samanaikaisesti mittaavien kaukokartoituslaitteistojen kehitystä tulisi edistää. Tällaiset laitteistot voisivat parantaa puuston lajitulkintaa huomattavasti jo muutamaa sovellukseen sopivinta aallonpituutta käyttämällä.