Dec 22 2021
Ilkka Korpela

Articles in international refereed scientific journals (39)

Ribas Costa, Vicent ; Durand, Maxime; Robson, T Matthew; Porcar-Castell, Albert; Korpela, Ilkka; Atherton, Jon 2022,  UAS spherical photography for the vertical characterisation of canopy structural traitsNew Phytologist pp-pp. 

Eelis Halme, Olli Ihalainen, Ilkka Korpela and Matti Mottus 2022,  Assessing spatial variability and estimating mean crown diameter in boreal forests using variograms and amplitude spectra of very-high-resolution remote sensing dataInternational Journal of Remote Sensing pp-pp.

Alekseychik, P.,  Korrensalo, A., Mammarella, I., Launiainen, S., Tuittila, E.-S., Korpela, I., Vesala, T. 2021. Carbon balance of a Finnish bog: temporal variability and limiting factors based on 6 years of eddy-covariance dataBiogeosciences 18(16):4681-4704.

Alekseychik, P., Katul, G., Korpela, I., Launiainen, S. 2021. Eddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videosAtmos. Meas. Tech. AMT 14(5): 3501-3521.

Korpela, I., Haapanen, R., Korrensalo, A., Tuittila, E.-S., Vesala, T. 2020.  Fine-resolution mapping of microforms on a boreal bog using aerial images and waveform-recording LiDAR. Mires and Peat. DOI: 10.19189/MaP.2018.OMB.388

Blomley, R., Hovi, A., Weinmann, M., Hinz, S., Korpela, I., Jutzi, B. 2017. Tree species classification using within crown localization of waveform LiDAR attributes. ISPRS JPRS.

Majasalmi, T., Korhonen, L., Korpela, I., Vauhkonen, J. 2017. Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index. International Journal of Applied Earth Observation and Geoinformation

Korpela, I. 2017..Acquisition and evaluation of radiometrically comparable multi-footprint airborne LiDAR data for forest remote sensing. Remote Sensing of Environment

Matthieu Molinier *, Carlos A. López-Sánchez, Timo Toivanen, Ilkka Korpela, José J.  Corral-Rivas, Renne Tergujeff, Tuomas Häme. 2016. Mobile and Participative In-Situ Forest Biomass Measurements Supporting Satellite Image Mapping. Remote Sensing.

Hovi, A., Korhonen, L., Vauhkonen, J., Korpela, I. 2015.LiDAR waveform features for tree species classification and their sensitivity to tree- and acquisition related parameters.Remote Sensing of Environment.

Korpela, I., Mehtätalo, L., Markelin, L., Seppänen, A. &Kangas, A. 2014.Tree species identification in aerial image data using directional reflectance signatures. Silva Fennica 48(3) ID 1087.

Pant, P., Heikkinen, V., Korpela, I. , Hauta-Kasari, M.& Tokola, T. 2014.
Logistic Regression Based Spectral Band Selection for Tree Species Classification – Effects of Spatial Scale and Balance in Training Samples. IEEE Geoscience and Remote Sensing Letters 11(9).

Hovi A.& Korpela I. 2013. Real and simulated waveform-recording LiDAR data in juvenile boreal forest vegetation. Remote Sensing of Environment 140, 665-678.,

Pant, P., Heikkinen, V., Hovi, A., Korpela, I., Hauta-Kasari, M. & Tokola, T. 2013.
Evaluation of simulated bands in airborne optical sensors for tree species identification. Remote Sensing of Environment 138, p. 27-37.
Korhonen, L., Heiskanen, J. & Korpela, I. 2013. Modelling lidar-derived boreal forest canopy cover with SPOT 4 HRVIR data. International Journal of Remote Sensing. 34, 22, p. 8172-8181.

Korpela, I., Hovi,. A. &Korhonen, L. 2013.
Backscattering of individual LiDAR pulses from forest canopies explained by photogrammetrically derived vegetation structure. ISPRS Journal of Photogrammetry and Remote Sensing 83, p. 81-93.

Korhonen, L., Vauhkonen, J., Virolainen, A., Hovi, A.& Korpela, I. 2013. Estimation of tree crown volume from airborne lidar data using computational geometry.
International Journal Remote Sensing 34(20), 7236-7248.

Markelin, L., Honkavaara, E., Schläpfer, D., Bovet, S.& Korpela, I. 2012.
Assessment of radiometric correction methods for ADS40 imageryPhotogrammetrie, Ferkundung, Geoinformation (PFG) 2012/3, 251-266.

Korpela, I., Hovi, A. &Morsdorf, F. 2012.
Understory trees in airborne LiDAR data - Selective mapping due to transmission losses and echo-triggering mechanisms. Remote Sensing of Environment 119, 92-104.

Vastaranta, M., Korpela, I., Hovi, A., Uotila, A. &Holopainen, M. 2011.
Mapping of snow-damaged trees based on bitemporal airborne LiDAR data. European Journal of Forest Reserach 131(4) 1217-1228.

Korpela, I., Heikkinen, V., Honkavaara, E., Rohrbach F. &Tokola, T. 2011. Variation and anisotropy of reflectance of forest trees in radiometrically calibrated airborne line sensor images – implications for species classification in digital aerial images. Remote Sensing of Environment 115(8),

Heikkinen, V., Korpela I., Honkavaara E., Parkkinen, J.&Tokola, T. 2011.Classification of tree species using support vector machines and radiometrically corrected multiangular airborne image data. IEEE Transactions on Geoscience and Remote Sensing48(3), 1355-1364.

Korhonen L., Korpela, I., Heiskanen, J.&Maltamo, M. 2010. Airborne discrete-return LiDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index. Remote Sensing of Environment 115(4), 1065-1080.
Korpela I, Ørka H.O., Heikkinen V, Tokola T, &Hyyppä J. 2010. Range- and AGC normalization of LIDAR intensity data for vegetation classification. ISPRS Journal of Photogrammetry and Remote Sensing 65(4), 369-379.

Korpela, I., Ørka, H.O., Maltamo, M., Tokola, T. & Hyyppä, J. 2010. Tree species classification using airborne LiDAR – effects of stand and tree parameters, downsizing of training set, intensity normalization and sensor type. Silva Fennica 44(2).

Vauhkonen J., Korpela, I., Maltamo, M. &Tokola, T. 2010. Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape.Remote Sensing of Environment 114(6), 1265-1276.

Heikkinen, V., Tokola, T., Parkkinen, J., Korpela,I. &Jääskeläinen T. 2009 Simulated Multispectral Imagery for Tree Species Classification Using Support Vector MachinesIEEE Transactions on Geoscience and Remote Sensing48(3), 1355-1364.

Korpela, I., Koskinen, M., Vasander, H., Holopainen, M. &Minkkinen, K., 2009. Airborne small-footprint discrete-return LiDAR data in the assessment of boreal mire surface patterns, vegetation and habitats. Forest Ecology and Management 258 (7):1549-1566.

Korpela I., Tuomola T., Tokola T. & Dahlin, B. 2008. Appraisal of seedling stand vegetation with airborne imagery and discrete-return LiDAR – an exploratory analysis.Silva Fennica 42(5): 753-772.

Korpela, I. 2008. Mapping of understory lichens with airborne discrete-return LiDAR data. Remote Sensing of Environment. 112(10): 3891-3897.

Korpela I., Tuomola, T. &Välimäki, E. 2007. Mapping forest plots: An efficient method combining photogrammetry and field triangulation
Silva Fennica 41(3): 457-469.

Korpela I. 2007.
3D treetop positioning by multiple image matching of aerial images in a 3D search volume bounded by lidar surface models. Photogrammetrie, Ferkundung, Geoinformation (PFG) 1/2007: 35-44. ---

Mäkinen, A., Korpela, I., Tokola, T. & Kangas, A. 2006. Effects of imaging conditions on crown diameter measurements from high resolution aerial images. Canadian Journal of Forest Research 36: 1206-1217.

Korpela I. 2006. Geometrically accurate time series of archived aerial images and airborne lidar data in a forest environment.
Silva Fennica 40(1): 109-126.

Korpela I., Anttila, P. & Pitkänen J. 2006. A local maxima method in detecting individual trees in color-infrared aerial photographsInternational Journal of Remote Sensing. 27/6: 1159-1175.

Korpela, I. &Tokola T. 2006.Potential of aerial image-based monoscopic and multiview single-tree forest inventory - a simulation approach. Forest Science  52(2):136-147

Korpela, I. & Anttila, P. 2004.Appraisal of the mean height of trees by means of image matching of digitised aerial photographs. The photogrammetric Journal of Finland 19/1: 23-36.---

Korpela I. 2004. Individual tree measurements by means of digital aerial photogrammetry. Silva Fennica monographs 3. 93 p.

Articles in international conference proceedings with a peer review (4)

Vastaranta, M., Korpela, I., Uotila, M., Hovi, A. and Holopainen, M. Area-based snow  damage classification of forest canopies using bi-temporal lidar data. In Lichti, D. &  Habib, A.. 2011. ISPRS LaserScanning 2011 proceedings.

Markelin L., Honkavaara, E., Beisl, U., Korpela, I. 2010. Validation of the radiometric correction chain of the airborne photogrammetric ADS40 imaging system. ISPRS 2010 conference in Vienna.International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 38: 7A.

Korpela, I., B. Dahlin, H. Schäfer, E. Bruun, F. Haapaniemi, J. Honkasalo, S. Ilvesniemi, V. Kuutti, M. Linkosalmi, J. Mustonen, M. Salo, O. Suomi, and H. Virtanen. 2007. Single-tree forest inventory using LiDAR and aerial images for 3D treetop positioning, species recognition, height and crown width estimation. IAPRS Volume XXXVI, Part 3 / W52, 2007. pp. 227-233

Korpela I. 2006. 3D treetop positioning by multiple image matching of aerial images in a 3D search volume bounded by lidar surface models. In: International archives of the photogrammetry, remote sensing and spatial information sciences. Volume XXXVI, Part 3. Symposium of ISPRS Commission III. Photogrammetric Computer Vision, PCV '06. Bonn, 20-22 September 2006. Editors: Wolfgang Förstner, Richard Steffen. pp. 191-196. ISSN 1682-1750.

Articles in refereed Finnish scientific journals

Fish, S., Haakana, M., Korpela, I. &Melkas, T. 1998. Spatial relationships in a forest stand. In: Spatial Statistics in GIS Applications. (Eds. Artimo, K. and Haggrén, H.) Cartography and Geoinformatics Publications 4. Helsinki University of Technology. pp. 7-39.

Korpela, I. &Välimäki, E. 2007. Talousmetsän maanpintamallinnus arkistoilmakuvilta ja laserkeilauksella. [Elevation modeling in forests using archived aerial images and modern LiDAR].Maanmittaus 2/2007.

Scientific monographs (3)

Korpela I. 2003.Individual tree measurements by means of digital aerial photogrammetry PhD thesis. University of Helsinki. Department of Forest Resource Management. 132 p. Oct 1, 2003.

Korpela I. 2000. 3-D Matching of tree tops using digitized panchromatic aerial photographs. Licentiate thesis. University of Helsinki. Department of Forest Resource Management. 109 p.

Korpela I. 1993.Neste Oy:n Porvoon tuotantolaitosten vaikutus lähimetsien kasvuun. MSc thesis. University of Helsinki. Department of Forest Resource Management. 92 p. (English and Swedish Summary)

Articles in international conference proceedings without a review (10)

Korpela, I., Hovi, A., Korhonen, L. 2013. Backscattering of individual LiDAR pulses from forest canopies explained by photogrammetrcally derived vegetation structure. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W1, ISPRS Hannover Workshop 2013, 21 – 24 May 2013, Hannover, Germany

Korpela, I., Hovi. A., Morsdorf, F. 2011.Mapping of understory trees in discrete-return LiDAR data.ISPRS Hannover workshop, June 2011. CD-rom.

E. Honkavaara, R. Arbiol, L. Markelin, L. Martinez, S. Bovet, M. Bredif, L. Chandelier, V. Heikkinen, I. Korpela, L. Lelegard, F. Pérez, D.  Schläpfer, T. Tokola, 2011. EuroSDR project "Radiometric Aspects of Digital Photogrammetric Images" - Results of Empirical Phase. ISPRS Hannover workshop 2011.

Korpela I., Rohrbach F. 2010. Variation and anisotropy of forest trees in radiometrically calibrated airborne line-sensor images - implications for species classification.ISPRS Commission VII Symposium. Vienna 2010. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 38: 7A, #-#.

Korpela, I., Tokola, T., Ørka, H.O., Koskinen, M. 2009. Small footprint discrete-return LiDAR in tree species recognition. Proceedings of the ISPRS Hannover Workshop 2009, Hannover, Germany, June 2-5, 2009.

Honkavaara, E., Arbiol, R., Markelin, L., Martinez L., Cramer, M., Korpela, I., Bovet, S., Thom, C., Chandelier, L., Ilves, R., Klonus, S., Reulke, R., Marshall, P., Tabor, M., Schläpfer, D., and N. Veje, 2009. Status report of the EuroSDR project Radiometric aspects of digital photogrammetric airborne images. Proceedings of the ISPRS Hannover Workshop 2009, Hannover, Germany, June 2-5, 2009.

Korpela, I. 2007.Incorporation of allometry in single-tree remote sensing with LiDAR and multiple images.ISPRS Hannover workshop 2007. High Resolution Earth Imaging for Geospatial Information. Hannover, Germany, May 29-June 1, 2007.Editors: C. Heipke, K. Jacobsen, M. Gerke. ISPRS XXXVI Part I/W51, ISSN No. 1682-1777.  CD-Rom.

Anttila, P., Korpela, I. and Pitkänen, J. 2005. The performance of a local maxima method in detecting individual trees in aerial photographs. Proc 1st Göttingen GGRS days. Remote Sensing and Geographical Information Systems for Environmental Studies. Applications in Forestry. Schriften aus der Forstlichen Fakultät der Universität Göttingen und der Niedersächsishen Forstlichen Versuchanstalt, Band 138. pp. 15-24. ISBN 3-7939-5138-3.

Korpela, I.,  Rasinmäki, J. and Tokola, T. 2005. Estimation Chains for Single Tree Based Forest Inventory Using using GIS and Digitised Aerial Photography. Proc 1st Göttingen GGRS days. Remote Sensing and Geographical Information Systems for Environmental Studies. Applications in Forestry. Schriften aus der Forstlichen Fakultät der Universität Göttingen und der Niedersächsishen Forstlichen Versuchanstalt, Band 138. pp. 63-73. ISBN 3-7939-5138-3.

Korpela, I.  and Tokola, T. 2004. Comparison of Alternatives Estimation Chains for Single Tree Based Forest Inventory Using Digitised Aerial Photography - a Simulation Approach. Proc 2nd International Conference on Forest Measurements and Quantitative Methods and Management & the 2004 Southern Mensurationists Meeting. Hot Springs, Arkansas. June 15-18, 2004.

Other publications

Kaikki irti laserkeilauksesta. Maanmittaustieteiden päivät 2011 (Moniulotteinen maanmittaus, toim. Kirsikka Niukkanen). 1.-2.12.2011 Tieteiden talo. Maanmittaustieteiden Seuran julkaisu n:o 48. p. 61-71. 

Tokola, T., Korpela, I., Andersson, K. 2007. Automaattinen puuston kartoitus ja mittaus ilmasta käsin - Kolmiulotteinen kuvatulkinta lentotiedustelun lennokkikuvilla. MATINE Tutkimusraportti 679.

Korpela I., Kallonen, J., Välimäki, E. 2006.Aika- ja paikkamatkailua Hyytiälän metsissa. Time-travelling in Hyytiälä 1946-2006. Web-site. Published August 31, 2006.

Soiden luokitus. (Classification of mires) In: Metsälehden Metsäkoulu. Metsälehti Kustannus. 1998. pp. 20-21.

Helsingin yliopisto on tutkinut metsien kasvua Skölvikin öljynjalostamon  ympäristössä. Helsingfors Universitet har utfört en undersökning om barrskogarnas tillväxt kring Sköldvik. Press release 15.5.1992. 7 p.

Poster presentations & Talks in conferences/meetings (with abstracts)

Kaikki irti laserkeilauksesta. Invited talk at Maanmittaustieteiden päivät (Geodesy & Surveying days). Helsinki. Dec 2, 2011.

Mapping mires from the air – What can we do with timestamped and free photons? Talk at UMB Norway.  Use of Airborne Laser Scanner Data for Ecological Applications –seminar. June 23, 2011.

Mapping understory  trees in discrete-return data. Talk at ISPRS Hannover workshop, June 14, 2011

Airborne optical remote sensing of the forests and mires of Hyytiälä 1997 - 2011. Finnish Geodetic Institute's Research seminar, March 22, 2011.

Variation and directional anisotropy of reflectance at the crown scale – implications for tree species classification in digital aerial images. Nordic Remote Sensing Days, VTT Espoo, Nov 2010.

Puulajitulkinta digi-ilmakuvilta- mitä LEICA ADS40-kuvat paljastavat? 
Aaltomuotolaser metsässä – pelkkää kovalevyn täytettäkö?
Näkeekö laser metsän puilta seminaari. Evo / Hamk, Nov 9, 2010.

Laserkokeiluja Hyytiälän metsissä ja soilla 2004-2010. Maanmittauslaitoksen laserkeilaus- ja korkeusmalliseminaari 2010. Oct 8, 2010.

Laserkeilausinformaation hyödyntäminen puunkorjuun suunnittelussa (Utilizing airborne LiDAR in wood procurement planning - peatlands) . Metla/Metsähallitus research excursion. Hyytiälä Sept 14, 2010.

Turvemaiden kartoitus ilmasta käsin – Riittääkö auringonvalo vai pannaanko laseria peliin? Mapping peatlands from the air – is daylight enough or do we need to bring our own lasers? Invited talk at Metsähallitus seminar for experts in forestry and environmental monitoring. Feb 4, 2010.

Yksittäisten puiden inventointi laser- ja ilmakuva-aineistosta. Single-tree remote sensing methods based on airborne LiDAR and images. Invited talk at Evo Forest School / HAMK – Remote sensing seminar for foresters, Nov 25, 2008.

Mapping of Understory Lichens with Airborne Discrete-Return LiDAR Data. (Academic) Physense seminar at UH. June 3, 2008.

Laserkeilaus ilmakuvaperustaisessa puiden kartoituksessa ja mittauksessa. Combining lidar surface models with aerial image -based 3D positioning of trees. An invited talk at the meeting of Taksaattoriklubi. Helsinki, March 30, 2006.

Metsäalueen historian rekonstruointi ilmakuva-aikasarjoista. Reconstructing the silvicultural history using a time-series of archived aerial photographs. An invited talk at the annual surveying expo "Paikkatietomarkkinat". Helsinki, Sept 27, 2005.

Puiden tunnistus rakennetun tai rakennettavan ympäristön visualisointitarpeisiin, menetelmäkuvaus. Mapping trees for visualization of built non-built areas, method description. Rakennetun ympäristön 3D visualisointimallien luominen –seminaari. Seminar of TEKES MASI program. VTT Espoo. May 9, 2005.

Puiden kartoitus ja mittaus ilmakuvilta. Mapping and measuring tree in aerial images. An invited talk at the annual meeting of the Finnish Society of Forest Science. Helsinki, April 29, 2004.

Pystymittaus digitaalisen fotogrammerian menetelmin. Stand cruising by means of digital aerial photogrammetry. An invited talk at the meeting of the Finnish society of forest inventory and management planning experts, Taksaattoriklubi. Helsinki, March 30, 2004.

Tree detection from digital aerial photographs. Presentation at the Nordic workshop in image analysis and spatial statistics in forestry. Frederiksberg, Denmark. Nov 2, 1999.

A  forest growth study in the vicinity of a petrochemical complex. Abstract and presentation. 4th International Conference on Statistical Methods for the Environmental Sciences. Conference on Environmetrics in Espoo, Finland. August 17-21, 1992.


Research and teaching

KUVAMITT. 1999-2015. An digital photogrammetric workstation written in Visual Basic & C/C++ and Matlab dlls. 

* Aerial triangulation by means of hybrid bundle block adjustment,
* Anaglyphic stereo, i.e. computation and visualization of streo normalized imagery (to epipolar geometry)
* Area-based image matching, semiautomatic (for polygons) and manual (for points), stereo and triplet images.
* Feature-based treetop positiong in multiview imagery (up to 9 images, free scale)
* Manual image-matching of multiple images, using epipolar constraints (forward intersection)
* Support for frame and line-sensor imagery: monochromatic, RGB, RGBN, ADS40; raw, epipolar and ortho
* Support for raster (BIP, raw binary) and TIN (ascii) surfaces models, DEM or DSM
* Integrated analyses of LiDAR data and images, e.g. monoplotting, and WLS-modeling of surfaces in LiDAR points

Used at several UH and UEF (NOVA) courses and by several researchers.

RESECTION. 2006-2014. Program that performs network adjustment for planimetric positioning (of trees),

* Using redundant interpoint azimuth and distance observations.
* Includes a simulator version for teaching.
* Used at UH courses MARV1 and MARV4/2 and in field measurement campaigns to improve
the efficiency of accurate, dm-level tree positiong under canopy.

DTM-FILTER. 2006-2014.

         * An iterative gradient-based DEM creation by filtering of TIN-models generated from LiDAR data, or image-matching (KUVAMITT) point clouds.

AT-MONTECARLO. 2006-2008. Monte-Carlo simulator for hybrid aerial triangulation (weighted non-linear regression),

Allows the study of the effects different observation errors (XYZ-, XY-, and Z control points, XYZ-, XY-, and Z distances, image observations, direct sensor orientation observations) image overlaps and scale, and interior orientation parameters on the accuracy of reconstructed points and exterior orientation parameters.

AT 2000-2014. Aerial (image) triangulation (block adjustment),

* Uses Weighted-Least-Squares,
* All XYZ points are weighted, tie points can have Z or XY constraints,
* Image orientation parameters are all given a priori weights.


MARV4. 1999-2000. Interface between forest compartment data in landscape ecological planning and MELA simulator/optimization program. The program formulated the MELA tasks from the ecological classifications and data.

MARV3. 1997-2000. Calculations of basic plot level, static and increment-related stand variables from measurements on permanent forest plots.

MARV1. 1995-1998 (-2009). A selection of routines: Computation of single tree volumes and stem bucking based on polynomial taper curve functions. Calculations of stratified forest inventory results. Calculation of permanent forest plot results. The source code from 1995-96 is still in use on the MARV1 course.

Teaching material

Links to past course material can be found at