Laserkeilausaineiston ja katunäkymäkuvien hyödyntäminen tieympäristön seurannassa

Utilization of laser scanning has increased during the past few years in many fields of applications, for example, in road environment monitoring. Mild winters, increasing rainfalls and frost are deteriorating the surface and structure of the road causing road damages. The road environment and its condition can be examined for example with laser scanning and street view images. Utilization of laser scanning data and street view images in road environment monitoring was studied in this thesis. The main focus was on the road damages and drainage. Also individual trees were detected nearby road scenes. TerraModeler and TerraScan software were used for investigations. Five different lidar datasets were used to detect road damages and drainage. Both mobile and helicopter-based lidar data were available from Jakomäki area. In Rauma case, there were two datasets collected from the helicopter but the point densities were different. In addition, to helicopter-based lidar data, there were also street view images available from BlomSTREET service in Hyvinkää case. The results between the datasets were compared. Aim was to investigate if same damages can be found from the several datasets that have different point densities. Lidar data for individual tree detection was collected by helicopter from Korppoo area. Tree locations were also measured with a tachymeter to get reference data for automatic detection. Heights of the trees were manually determined from the point cloud. Manually measured heights and locations were compared with automatically detected ones. Detection of rut depths, slopes and drainage is possible from the high point density datasets. From lower point density datasets it is not possible to detect for example rut depths. Point cloud is possible to color by slopes, which may give some information about rut locations even from lower point density datasets. Obtaining slopes and drainage accurately is also possible from lower point density data. With TerraModeler water gathering points can be obtained. Panorama pictures from BlomSTREET can be utilized for ensuring if there is a rainwater outlet or if water will gather as a puddle. Tree locations were detected in a meter accuracy with automatic method. Successful detection of tree heights and locations is dependent on many things. Successful classification of the data and creation of tree models are the most important parameters.Laserkeilaus on yleistynyt ja sitä hyödynnetään useissa eri sovelluksissa kuten esimerkiksi tiesovelluksissa. Leudot ja sateiset talvet sekä routa kuluttavat tien pintaa ja rakennetta aiheuttaen tievaurioita, jotka voivat olla vaaraksi liikenteelle. Tienkuntoa ja sen ympäristöä voidaan tarkastella esimerkiksi laserkeilausaineistojen sekä katunäkymäkuvien avulla. Työssä tutkittiin kuinka laserkeilausaineistoa ja katunäkymäkuvia voidaan hyödyntää tieympäristön seurannassa. Tutkimuksessa keskityttiin tarkastelemaan tievaurioita ja kuivatusta sekä tiealueiden läheisyydessä sijaitsevien puiden tunnistusta. Tutkimuksessa käytettiin TerraModeler ja TerraScan ohjelmistoja. Tievaurioita ja kuivatusta tutkittiin viidestä eri aineistosta kolmelta eri alueelta. Jakomäen alueelta tien ominaisuuksia tutkittiin sekä mobiili- että helikopterilaserkeilausaineistosta ja Rauman alueelta vaurioita kartoitettiin kahdesta eri helikopterilla kerätystä pistetiheyden aineistosta. Hyvinkäältä helikopterilla kerätyn laserkeilausaineiston lisäksi oli saatavilla katunäkymäkuvia BlomSTREET palvelusta. Aineistoista saatuja tuloksia vertailtiin keskenään ja tutkittiin, onko niistä mahdollista havaita samankaltaisia tuloksia. Yksittäisen puun tunnistukseen käytettiin helikopterilla kerättyä laserkeilausaineistoa Korppoon alueelta ja referenssinä aineistolle toimi maastossa mitatut puiden sijainnit. Automaattisesti määritettyjen puiden sijaintia verrattiin maastossa mitattuihin sijainteihin. Myös puiden korkeus määritettiin pistepilvestä manuaalisesti ja tätä verrattiin automaattiseen korkeuden määritykseen. Korkean pistetiheyden laserkeilausaineistoilla on mahdollista tutkia tien urautumista, tien kaltevuuksia ja kuivatusta. Matalamman pistetiheyden aineistoista ei pystytä määrittämään esimerkiksi urasyvyyksiä. Pistepilvi on mahdollista värjätä kaltevuuksien mukaan, minkä avulla urautumista voidaan havaita jossain määrin myös matalampien pistetiheyksien aineistoista. Tien kaltevuuksia ja kuivatusta pystytään havaitsemaan tarkasti jopa alhaisista pistetiheyden aineistoista. TerraModelerin avulla voidaan määrittää alueet, johon sadevesi kasautuu. BlomSTREET 360 panoraamakuvien avulla pystytään tarkastamaan onko kohdassa sadevesikaivo vai kerääntyykö vesi lammikoiksi. Yksittäisten puiden sijainnin määrittäminen onnistui noin metrin tarkkuudella, mutta sijainnin ja korkeuden määrittämisen onnistuminen on riippuvainen monesta tekijästä. Pistepilven luokittelun onnistumisen lisäksi yksi tärkeä tekijä on puiden muodoista tehdyt mallit, joiden avulla TerraScan ohjelmisto etsii yksittäisiä puita

Optimizing the Sampling Area across an Old-Growth Forest via UAV-Borne Laser Scanning, GNSS, and Radial Surveying

Aboveground biomass, volume, and basal area are among the most important structural attributes in forestry. Direct measurements are cost-intensive and time-consuming, especially for old-growth forests exhibiting a complex structure over a rugged topography. We defined a methodology to optimize the plot size and the (total) sampling area, allowing for structural attributes with a tolerable error to be estimated. The plot size was assessed by analyzing the semivariogram of a CHM model derived via UAV laser scanning, while the sampling area was based on the calculation of the absolute relative error as a function of allometric relationships. The allometric relationships allowed the structural attributes from trees’ height to be derived. The validation was based on the positioning of a number of trees via total station and GNSS surveys. Since high trees occlude the GNSS signal transmission, a strategy to facilitate the positioning was to fix the solution using the GLONASS constellation alone (showing the highest visibility during the survey), and then using the GPS constellation to increase the position accuracy (up to PDOP~5−10). The tree heights estimated via UAV laser scanning were strongly correlated (r2 = 0.98, RMSE = 2.80 m) with those measured in situ. Assuming a maximum absolute relative error in the estimation of the structural attribute (20% within this work), the proposed methodology allowed the portion of the forest surface (≤60%) to be sampled to be quantified to obtain a low average error in the calculation of the above mentioned structural attributes (≤13

Prediction of Timber Quality Parameters of Forest Stands by Means of Small Footprint Airborne Laser Scanner Data

The aim of this study was to explore the capability of airborne laser scanner (ALS) data to explain the variation in field-measured variables representing timber quality within square 0.25 ha grid cells in a mature conifer forest in the southeast of Norway. These variables were the mean ratio between stem diameter at six m above ground and the diameter at breast height (R D6 ), the volume of saw logs (V SL ), the proportion of saw logs relative to the total volume (P SL ), the ratio between tree height and diameter at breast height (HD), mean basal area diameter (D g ), and crown height (CH). Each of these variables was modeled using a mixed modeling approach. Model fit was expressed by the Pseudo-R 2 , and were 0.85, 0.50, 0.78, 0.57, 0.74, and 0.58 for the respective quality variables. Furthermore, much of the residual error could be attributed to the different forest stands from which the grid cells originated even though we used field-observed tree species proportions as auxiliary information. It was concluded that more auxiliary information is needed to estimate models that are general across stands, but that the relationships between ALS-data and the quality variables considered here seem strong enough to be utilized for example to prioritize between stands in relation to harvest when specific quality distributions are sought

Derivation of forest inventory parameters from high-resolution satellite imagery for the Thunkel area, Northern Mongolia. A comparative study on various satellite sensors and data analysis techniques.

With the demise of the Soviet Union and the transition to a market economy starting in the 1990s, Mongolia has been experiencing dramatic changes resulting in social and economic disparities and an increasing strain on its natural resources. The situation is exacerbated by a changing climate, the erosion of forestry related administrative structures, and a lack of law enforcement activities. Mongolia’s forests have been afflicted with a dramatic increase in degradation due to human and natural impacts such as overexploitation and wildfire occurrences. In addition, forest management practices are far from being sustainable. In order to provide useful information on how to viably and effectively utilise the forest resources in the future, the gathering and analysis of forest related data is pivotal. Although a National Forest Inventory was conducted in 2016, very little reliable and scientifically substantiated information exists related to a regional or even local level. This lack of detailed information warranted a study performed in the Thunkel taiga area in 2017 in cooperation with the GIZ. In this context, we hypothesise that (i) tree species and composition can be identified utilising the aerial imagery, (ii) tree height can be extracted from the resulting canopy height model with accuracies commensurate with field survey measurements, and (iii) high-resolution satellite imagery is suitable for the extraction of tree species, the number of trees, and the upscaling of timber volume and basal area based on the spectral properties. The outcomes of this study illustrate quite clearly the potential of employing UAV imagery for tree height extraction (R2 of 0.9) as well as for species and crown diameter determination. However, in a few instances, the visual interpretation of the aerial photographs were determined to be superior to the computer-aided automatic extraction of forest attributes. In addition, imagery from various satellite sensors (e.g. Sentinel-2, RapidEye, WorldView-2) proved to be excellently suited for the delineation of burned areas and the assessment of tree vigour. Furthermore, recently developed sophisticated classifying approaches such as Support Vector Machines and Random Forest appear to be tailored for tree species discrimination (Overall Accuracy of 89%). Object-based classification approaches convey the impression to be highly suitable for very high-resolution imagery, however, at medium scale, pixel-based classifiers outperformed the former. It is also suggested that high radiometric resolution bears the potential to easily compensate for the lack of spatial detectability in the imagery. Quite surprising was the occurrence of dark taiga species in the riparian areas being beyond their natural habitat range. The presented results matrix and the interpretation key have been devised as a decision tool and/or a vademecum for practitioners. In consideration of future projects and to facilitate the improvement of the forest inventory database, the establishment of permanent sampling plots in the Mongolian taigas is strongly advised.2021-06-0

Aspects of Accuracy, Scanning Angle Optimization, and Intensity Calibration Related to Nationwide Laser Scanning

Osajulkaisut: Publication 1: Ahokas, E., Kaartinen, H., Hyyppä, J. 2004. A quality assessment of repeated airborne laser scanner observations. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Istanbul, Turkey, Vol. XXXV, part B3, pp. 237-242. ISSN 1682-1750. Publication 2: Ahokas, E., Hyyppä, J., Kaartinen, H., Kukko, A., Kaasalainen, S., Krooks, A. 2010. The effect of biomass and scanning angle on laser beam transmittance. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vienna, Austria, Vol. XXXVIII(7A), pp. 1-6. ISSN 1682-1777. http://www.isprs.org/proceedings/XXXVIII/part7/a/pdf/1_XXXVIII-part7A.pdf Publication 3: Ahokas, E., Hyyppä, J., Yu, X., Holopainen, M. 2011. Transmittance of Airborne Laser Scanning Pulses for Boreal Forest Elevation Modeling. Remote Sensing. 3, 1365-1379. ISSN 2072-4292. http://www.mdpi.com/2072-4292/3/7/1365/ Publication 4: Kaasalainen, S., Ahokas, E., Hyyppä, J., Suomalainen, J. 2005. Study of surface brightness from backscattered laser intensity: Calibration of laser data. IEEE Geoscience and remote sensing letters, Vol. 2, No. 3, pp. 255-259, ISSN 1545-598X. Publication 5: Ahokas, E., Kaasalainen, S., Hyyppä, J., Suomalainen, J. 2006. Calibration of the Optech ALTM 3100 laser scanner intensity data using brightness targets. ISPRS Commission I Symposium, Paris Marne-la-Vallee, 4-6 July 2006, ISPRS Volume XXXVI Part 1/A. pp. 14-20. CD-ROM publication. Also in Revue Française de Photogrammétrie et de Télédétection, No. 182, (2006-2), pp. 10-16. Publication 6: Honkavaara, E., Peltoniemi J., Ahokas, E., Kuittinen R., Hyyppä, J., Jaakkola, J., Kaartinen, H., Markelin, L., Nurminen, K., Suomalainen, J. 2008. A Permanent Test Field for Digital Photogrammetric Systems. Photogrammetric Engineering and Remote Sensing. Vol. 74, No. 1, pp. 95-106.Airborne laser scanning is a technique that produces three-dimensional coordinates of the Earth’s surface as well as generating intensity values. Nationwide airborne laser scanning was launched in Finland in 2008 and some 180 000 km2 had been scanned by the end of 2012. While the main goal in this endeavour is to produce an accurate digital elevation/terrain model (2 x 2 m2 grid size) of the whole of the country, other applications, e.g. forestry, will benefit from the data as well. This study deals with the accuracy of airborne laser scanning, the optimization of the scanning angle, and the calibration of intensity. Accuracy assessments of airborne laser scanning have shown that the geometric accuracy of the method can fulfill the accuracy requirements for producing a nationwide digital elevation model with a grid of 2 x 2 m2. When studying the effect of scanning angle and biomass on elevation modeling capability, it was found that it would be possible to increase the scanning angle applied in Finland’s nationwide laser scanning. Even though the accuracy of the elevation model in the conditions prevailing in Finland allows increasing of the scanning angle, other applications would most probably not benefit from this. For example, these same data are sometimes used in nationwide forest inventory in Finland. A method for relative and absolute calibration of airborne laser scanning intensity was developed. The portable reference targets have proved their usefulness for calibration purposes. An intensity correction method should be used in pre-processing the airborne laser data. As a result of this, the usability of the intensity values may increase in practical applications, such as in classification. The studies constituting this dissertation have already impacted on the practical aspects of the nationwide airborne laser scanning dealing with accuracy assessment, the work done in the field of intensity calibration, and scanning angle analysis may have a further impact on nationwide laser scanning in the coming years. The optimization of airborne laser scanning flight parameters for multi-use nationwide laser scanning is a topic deserving further research.Ilmasta tehtävä laserkeilaus tuottaa 3D-koordinaatteja maan pinnalta sekä intensiteettiarvoja. Suomen valtakunnallinen laserkeilaus aloitettiin vuonna 2008 ja noin 180000 km2 oli keilattu vuoden 2012 loppuun mennessä. Vaikka päätarkoituksena on tuottaa tarkka digitaalinen korkeus/maastomalli (2 x 2 m2 ruutukoko) koko maasta, muutkin sovellukset, kuten metsätalous, hyötyvät tästä aineistosta. Tämä tutkimus käsittelee ilmasta tehtävän laserkeilauksen tarkkuutta, keilauskulman optimointia sekä intensiteetin kalibrointia. Laserkeilauksen tarkkuusarviointi on osoittanut, että menetelmän geometrinen tarkkuus täyttää valtakunnallisen digitaalisen korkeusmallin tuottamisen tarkkuusvaatimukset. Kun tutkittiin keilauskulman ja biomassan vaikutusta korkeusmallin tuottamiseen, huomattiin että olisi mahdollista kasvattaa valtakunnallisen laserkeilauksen havaintokulmaa. Vaikka korkeusmallin tarkkuus mahdollistaisi Suomen oloissa keilauskulman kasvattamisen, muut sovellukset eivät luultavasti hyötyisi tästä. Esimerkiksi tätä samaa aineistoa käytetään Suomen valtakunnallisessa metsien inventoinnissa. Laserkeilauksen intensiteetin suhteellista ja absoluuttista kalibrointia varten kehitettiin menetelmä. Siirrettävät referenssikohteet osoittivat käyttökelpoisuutensa intensiteetin kalibroinnissa. Intensiteetin kalibrointimenetelmää tulisi käyttää laserkeilausaineiston esikäsittelyssä. Tämän tuloksena intensiteettiarvojen käyttökelpoisuus kasvaisi käytännön sovelluksissa, kuten luokittelussa. Tämän väitöskirjan muodostaneet tutkimukset ovat jo käytännössä vaikuttaneet valtakunnallisen laserkeilauksen tarkkuusarvioinnissa. Intensiteetin kalibrointityö ja keilauskulman analysointi vaikuttanevat valtakunnalliseen laserkeilaukseen tulevina vuosina. Lisätutkimusta tarvitaan ilmasta tehtävän laserkeilauksen lentoparametrien optimoimiseksi monikäyttöistä valtakunnallista laserkeilausta varten

Transmittance of Airborne Laser Scanning Pulses for Boreal Forest Elevation Modeling

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Puistute takseertunnuste hindamine aerolidari mõõtmisandmete põhjal hemiboreaalsetes metsades

A Thesis for applying for the degree of Doctor of Philosophy in Forestry.Forest management and planning requires up-to-date data, which commonly is acquired using field experts and ground measurements. Nowadays, more and more of data about forest stands is measured using remotely sensing methods. Most common methods include aerial photography and laser scanning from airplanes, also spectral measurements from satellites or even drone images and applications. This doctoral thesis focuses on developing applications and methods for utilising the airborne laser scanning (ALS) data that is freely available for the whole Estonia. The ALS measurements are carried out by the Estonian Land Board on a routine basis twice a year – in spring and summer. The first variable that was studied in this thesis was forest height. Based on the thesis, the most reliable method for forest height assessment was using the ALS point-cloud 80th height percentile (HP80). The small circular plot (radius of 15…30 m) and stand based studies showed high correlations with the field-measured forest heights and with great confidence it can be said, that ALS-based forest height estimations are close or even with higher accuracy, than field inspected. The second studied variable was standing wood volume. The ALS-based methods and models that were developed throughout this thesis used the idea, that standing wood volume is based on forest height and density. For this the HP80 and a threshold-based point count ratio was used (canopy cover - CC). ALS-based CC (CCALS) estimates were studied and compared with digital hemispherical photo based measurements. The results showed similar errors as were shown in other similar studies, with around 10-15% root mean square error (RMSE). The strongest correlation was shown using all echoes above a 1.3 metre threshold. Combining the CCALS and HP80 showed standing wood volume estimates with a similar error as we would receive from field measurements (<20%). The freely available multitemporal ALS data showed promising results for forest height growth monitoring and detecting small-scale disturbances. CCALS was shown to have strong predictive value, when compared with a four year difference in thinned and unthinned stands. The nation-wide ALS data can also be combined with forest height predictions from satellites, providing a faster update compared to the ALS data. Promising results were shown using the interferometric synthetic aperture radar (InSAR). Stand species maps generated using self-learning algorithms and satellite based spectral data can be used for developing species specific models of standing wood volume prediction. By combining these different datasets we can construct a nation-wide forest resource to help make better decisions for forest management and targeting fieldwork.Metsades majandamisotsuste langetamiseks ja metsamajanduslike tööde planeerimiseks on metsaomanikel vaja andmeid. Harjumuspäraselt on andmete kogumiseks tehtud metsas maapealseid mõõtmisi. Viimastel aastakümnetel on metsade inventeerimiseks üha enam aga kasutatud mittekontaktseid mõõtmisi - lennukitelt tehtavad aerofotosid, laserskaneerimist, satelliitidelt tehtavaid kiirgusmõõtmisi või viimastel aastatel ka droonidelt tehtud pilte. Antud doktoritöö on võtnud fookusesse aerolaserskaneerimise (ALS) andmete põhjal Eesti metsadesse sobilike rakenduste väljatöötamise. ALS mõõtmisi teeb Eesti Maa-amet rutiinsete lendude käigus kaks korda aastas, nii kevadel kui ka suvel. Aastast 2008 alustatud mõõtmiste tulemusel on Eesti üks väheseid riike maailmas, kus on vabalt kasutada mitmekordselt kogu riiki kattev ALS andmestik. Doktoritöö tulemusel töötati välja metsa kõrguse hindamiseks sobilikud meetodid, kasutades selleks punktipilvede kõrgusprotsentiile. Tugevamaid seoseid metsas proovitükkidel mõõdetud kõrgustega näitas punktipilve 80-protsentiil (HP80) ja uuringute põhjal võib väita, et metsa kõrguse määramine suvistelt aerolidari andmetelt on ligilähedane täpsustele, mida saadakse metsas kohapeal mõõtes. Teine oluline tunnus, mida metsade majandamise planeerimisel silmas peetakse, on kasvava metsa tagavara. Teadustöö põhjal töötati välja mudelite kujud ja metoodika, mille abil prognoositud tagavara oli sarnase veapiiriga, mis on lubatud metsas hinnanguid tegevatele taksaatoritele (<20%). Väljatöötatud ALS-põhine mudeli kuju järgib loogikat, et metsa tagavara on otseselt seotud mõõdetud kõrguse ja metsa tihedusega. Tihenduse hindamiseks aerolidari andmetelt kasutatakse nivoopõhist punktide suhtearvu ehk nn katvushinnangut (CCALS). Katvushinnangu täpsuse valideerimiseks ja tihedas metsas sobiva prognoosimeetodi väljatöötamiseks tehti välimõõtmisi kasutades poolsfäärikaameraid. Poolsfääripiltide põhjal tehtud valideerimise tulemused andsid sarnaseid veahinnanguid, mida on ka varasemates teadusuuringutes esitletud (RMSE = 10…15%). Kahe sarnasest fenoloogilisest perioodist ALS andmestiku lahutamisel uuriti ka muutuste tuvastamise võimalikkust. Uuringud andsid paljulubavaid tulemusi metsade kõrguskasvu hindamiseks ja CCALS osutus ka oluliseks tunnuseks väiksemate häiringute, nagu näiteks harvendusraie, tuvastamiseks. Kogu riiki katva ALS andmestiku kombineerimisel erinevate satelliitandmetega või näiteks spektraalsete mõõtmiste põhjal tehtud puistu liigiliste koosseisu kaartidega on võimalik antud töös välja pakutud meetodite abil anda igal aastal kogu Eesti metsaressursside ülevaade. Samuti on võimalik koostada vaid kaugseirevahendeid ja proovitükkidel lähendatud mudeleid kasutades eraldiste põhised takseerkirjeldused, mida siis taksaatorid saavad näiteks kasutada oma välitööde kavandamisel.  Publication of this thesis is supported by the Estonian University of Life Sciences

Comparing accuracy of airborne laser scanning and TerraSAR-X radar images in the estimation of plot-level forest variables

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