uusimpia drone-julkaisuja
2023
George, A., Koivumäki, N., Hakala, T., Suomalainen, J., and E. Honkavaara, 2023. Visual-Inertial Odometry Using High Flying Altitude Drone Datasets. Drones, 7(1), 36. https://doi.org/10.3390/drones7010036
2022
Alves Oliveira, R., Marcato Junior, J., Soares Costa, C., Näsi, R., Koivumäki, N., Niemeläinen, O., Kaivosoja, J., Nyholm, L., Pistori, H., and E. Honkavaara, 2022. Silage Grass Sward Nitrogen Concentration and Dry Matter Yield Estimation Using Deep Regression and RGB Images Captured by UAV. Agronomy, 12(6), 1352. https://doi.org/10.3390/agronomy12061352
Christovam, L.E., Shimabukuro, M.H., Galo, M.D.B.T., and E. Honkavaara, 2022. Pix2pix Conditional Generative Adversarial Network with MLP Loss Function for Cloud Removal in a Cropland Time Series Remote Sensing, 1(14), 144. https://doi.org/10.3390/rs14010144
Junttila, S., Näsi, R., Koivumäki, N., Imangholiloo, M., Saarinen, N., Raisio, J., Holopainen, M., Hyyppä, H., Hyyppä, J., Lyytikäinen-Saarenmaa, P., Vastaranta, M., and E. Honkavaara, 2022. Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season. Remote Sensing, 14(4), 909. https://doi.org/10.3390/rs14040909
Kanerva, H., Honkavaara, E., Näsi, R., Hakala, T., Junttila, S., Karila, K., Koivumäki, N., Alves Oliveira, R., Pelto-Arvo, M., Pölönen, I., Tuviala, J., Östersund, M., and P. Lyytikäinen-Saarenmaa, 2022. Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network. Remote Sensing, 14, 6257. https://doi.org/10.3390/rs14246257
Karila, K., Alves Oliveira, R., Ek, J., Kaivosoja, J., Koivumäki, N., Korhonen, P., Niemeläinen, O., Nyholm, L., Näsi, R., Pölönen, I., and E. Honkavaara, 2022. Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks. Remote Sensing, 14(11), 2692. https://doi.org/10.3390/rs14112692
Nex, F., Armenakis, C., Cramer, M., Cucci, D.A., Gerke, M., Honkavaara, E., Kukko, A., Persello, C., and J. Skaloud, 2022. UAV in the advent of the twenties: Where we stand and what is next. ISPRS Journal of Photogrammetry and Remote Sensing, 184:215-242. https://doi.org/10.1016/j.isprsjprs.2021.12.006
Tienaho, N., Yrttimaa, T., Kankare, V., Vastaranta, M., Luoma, V., Honkavaara, E., Koivumäki, N., Huuskonen, S., Hynynen, J., Holopainen, M., Hyyppä, J., and N. Saarinen, 2022. Assessing Structural Complexity of Individual Scots Pine Trees by Comparing Terrestrial Laser Scanning and Photogrammetric Point Clouds. Forests, 13(8), 1305. https://doi.org/10.3390/f13081305
2021
Berveglieri, A., Imai, N.N., Christovam, L.E., Galo, M.L.B.T., Tommaselli, A.M.G., and E. Honkavaara, 2021. Analysis of trends and changes in the successional trajectories of tropical forest using the Landsat NDVI time series. Remote Sensing Applications: Society and Environment, 24, 100622. https://doi.org/10.1016/j.rsase.2021.100622
Berveglieri, A., Imai, N.N., Tommaselli, A.M.G., Martins-Neto, R.P., Miyoshi, G.T., and E. Honkavaara, 2021. Forest cover change analysis based on temporal gradients of the vertical structure and density. Ecological Indicators, 126, 107597. https://doi.org/10.1016/j.ecolind.2021.107597
Kaivosoja, J., Hautsalo, J., Heikkinen, J., Hiltunen, L., Ruuttunen, P., Näsi, R., Niemeläinen, O., Lemsalu, M., Honkavaara, E., and J. Salonen, 2021. Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases. Remote Sensing, 13(7), 1238. https://doi.org/10.3390/rs13071238
Martins-Neto, R.P., Tommaselli, A.M.G., Imai, N.N., David, H.C., Miltiadou, M., and E. Honkavaara, 2021. Identification of Significative LiDAR Metrics and Comparison of Machine Learning Approaches for Estimating Stand and Diversity Variables in Heterogeneous Brazilian Atlantic Forest. Remote Sensing, 13(13), 2444. https://doi.org/10.3390/rs13132444
Näsi, R., 2021. Drone-based spectral and 3D remote sensing applications for forestry and agriculture. Aalto University publication series DOCTORAL DISSERTATIONS 168/2021, FGI Publications 165, pp. 78 + app. 122. http://urn.fi/URN:ISBN:978-952-64-0613-8
Putkiranta, P., Kurkela, M., Ingman, M., Keitaanniemi, A., El Issaoui, A., Kaartinen, H., Honkavaara, E., Hyyppä, H., Hyyppä, J., and M.T. Vaaja, 2021. Performance Assessment of Reference Modelling Methods for Defect Evaluation in Asphalt Concrete. Sensors, 21(24), 8190. https://doi.org/10.3390/s21248190
Suomalainen, J., Oliveira, R.A., Hakala, T., Koivumäki, N., Markelin, L., Näsi, R., and E. Honkavaara, 2021. Direct reflectance transformation methodology for drone-based hyperspectral imaging. Remote Sensing of Environment, 266, 112691, https://doi.org/10.1016/j.rse.2021.112691
Wang, N., Suomalainen, J., Bartholomeus, H., Kooistra, L., Masiliūnas, D., and J.G.P.W. Clevers, 2021. Diurnal variation of sun-induced chlorophyll fluorescence of agricultural crops observed from a point-based spectrometer on a UAV. International Journal of Applied Earth Observation and Geoinformation, 96, 102276. https://doi.org/10.1016/j.jag.2020.102276
Xu, S., Atherton, J., Riikonen, A., Zhang, C., Oivukkamäki, J., MacArthur, A., Honkavaara, E., Hakala, T., Koivumäki, N., Liu, Z., and A. Porcar-Castell, 2021. Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop. Remote Sensing of Environment, 263, 112555. https://doi.org/10.1016/j.rse.2021.112555
2020
Oliveira, R. A., Näsi, R., Niemeläinen, O., Nyholm, L., Alhonoja, K., Kaivosoja, J., Jauhiainen, L., Viljanen, N., Nezami, S., Markelin, L., Hakala, T., Honkavaara, E. Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry. Remote Sensing of Environment, Vol 246, 2020, 111830. DOI: 10.1016/j.rse.2020.111830
Nezami, S., Khoramshahi, E., Nevalainen, O., Pölönen, I., Honkavaara, E. Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks. Remote Sensing, 2020, 12, 1070. DOI: 10.3390/rs12071070
Hyyppä, E., Hyyppä, J., Hakala, T., Kukko, A., Wulder, M.A., White, J.C., Pyörälä, J., Yu, X., Wang, Y., Virtanen, J.P., Pohjavirta, O., Liang, X., Holopainen, M., Kaartinen, H. Under-canopy UAV laser scanning for accurate forest field measurements. ISPRS Journal of Photogrammetry and Remote Sensing, Vol 164, 2020, Pages 41-60, ISSN 0924-2716. DOI: 10.1016/j.isprsjprs.2020.03.021
Miyoshi, G.T., Arruda, M.S., Osco, L.P., Marcato Junior, J., Gonçalves, D.N., Imai, N.N., Tommaselli, A.M.G., Honkavaara, E., Gonçalves, W.N. A Novel Deep Learning Method to Identify Single Tree Species in UAV-Based Hyperspectral Images. Remote Sensing, 2020, 12, 1294. DOI: 10.3390/rs12081294
Miyoshi, G.T., Imai, N.N., Tommaselli, A.M.G., Antunes de Moraes, M.V., Honkavaara, E. Evaluation of Hyperspectral Multitemporal Information to Improve Tree Species Identification in the Highly Diverse Atlantic Forest. Remote Sensing, 2020, 12, 244. DOI: 10.3390/rs12020244
Annala, L., Honkavaara, E., Tuominen, S., Pölönen, I. Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion. Remote Sensing, 2020, 12, 283. DOI: 10.3390/rs12020283
Hakala T., Pölönen I., Honkavaara E., Näsi R., Hakala T., Lindfors A. Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks. In: Diez P., Neittaanmäki P., Periaux J., Tuovinen T., Pons-Prats J. (eds) Computation and Big Data for Transport. Computational Methods in Applied Sciences, vol 54. Springer, Cham. DOI: 10.1007/978-3-030-37752-6_13
Anders, N., Smith, M., Suomalainen, J., Cammeraat, E., Valente, J., Keesstra S. Impact of flight altitude and cover orientation on Digital Surface Model (DSM) accuracy for flood damage assessment in Murcia (Spain) using a fixed-wing UAV. Earth Science Informatics, (2020). DOI: 10.1007/s12145-019-00427-7
2019
Khoramshahi, E., Campos, M.B., Tommaselli, A.M.G., Vilijanen, N., Mielonen, T., Kaartinen, H., Kukko, A., Honkavaara, E. Accurate Calibration Scheme for a Multi-Camera Mobile Mapping System. Remote Sensing, 2019, 11, 2778. DOI: 10.3390/rs11232778
Imangholiloo, M., Saarinen, N., Markelin, L., Rosnell, T., Näsi, R., Hakala, T., Honkavaara, E., Holopainen, M., Hyyppä, J., Vastaranta, M. Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle. Forests, 2019, 10, 415. DOI: 10.3390/f10050415
Berveglieri, A., Tommaselli, A. M. G., Santos, L. D., Honkavaara, E. Bundle Adjustment of a Time-Sequential Spectral Camera Using Polynomial Models. IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 11, pp. 9252-9263, Nov. 2019, DOI: 10.1109/TGRS.2019.2925783
Kokka, A., Pulli, T., Honkavaara, E., Markelin, L., Kärhä, P., Ikonen, E. Flat-field calibration method for hyperspectral frame cameras. Metrologia, 56, 055001. DOI: 10.1088/1681-7575/ab3261
Liang, X., Wang, Y., Pyörälä, J. Lehtomäki, M., Yu, X., Kaartinen, H., Kukko, A., Honkavaara, E., Issaoui, A.E.I., Nevalainen, O., Vaaja, M., Virtanen, J.P., Katoh, M., Deng, S. Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements. Forest Ecosystems, 6, 20 (2019). DOI: 10.1186/s40663-019-0173-3
Oliveira, R. A., Tommaselli, A.M.G. Honkavaara, E. Generating a hyperspectral digital surface model using a hyperspectral 2D frame camera. ISPRS Journal of Photogrammetry and Remote Sensing, Vol 147, 2019, Pages 345-360, ISSN 0924-2716. DOI: 10.1016/j.isprsjprs.2018.11.025
Oliveira, R. A., Näsi, R., Niemeläinen, O., Nyholm, L., Alhonoja, K., Kaivosoja, J., Viljanen, N., Hakala, T., Nezami, S., Markelin, L., Jauhiainen, L., Honkavaara, E. Assessment of RGB and hyperspectral UAV remote sensing for grass quantity and quality estimation. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 489–494. DOI: 10.5194/isprs-archives-XLII-2-W13-489-2019
Tommaselli, A.M.G., Santos, L.D., Oliveira, R.A., Berveglieri, A., Imai, N.N., Honkavaara, E. Refining the Interior Orientation of a Hyperspectral Frame Camera With Preliminary Bands Co-Registration. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 7, pp. 2097-2106, July 2019. DOI: 10.1109/JSTARS.2019.2911547
Franceschini, M.H.D., Bartholomeus, H., van Apeldoorn, D.F., Suomalainen, J., Kooistra, L. Feasibility of Unmanned Aerial Vehicle Optical Imagery for Early Detection and Severity Assessment of Late Blight in Potato. Remote Sensing, 2019, 11, 224. DOI: 10.3390/rs11030224
2018
Viljanen, N., Honkavaara, E., Näsi, R., Hakala, T., Niemeläinen, O., Kaivosoja, J. A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone. Agriculture, 70. DOI: 10.3390/agriculture8050070
Hakala, T., Markelin, L., Honkavaara, E., Scott, B., Theocharous, T., Nevalainen, O., Näsi, R.; Suomalainen, J., Viljanen, N., Greenwell, C., Fox, N. Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization. Sensors, 2018, 18, 1417. DOI: 10.3390/s18051417
Khoramshahi, E., Honkavaara, E. Modelling and automated calibration of a general multi‐projective camera. The Photogrammetric Record, 2018, Vol 33, 161, Pages 86–112. DOI: 10.1111/phor.12230
Näsi, R., Honkavaara, E., Blomqvist, M., Lyytikäinen-Saarenmaa, P., Hakala, T., Viljanen, N., Kantola, T., Holopainen, M. Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft. Urban Forestry & Urban Greening, Vol 30, 2018, Pages 72-83, ISSN 1618-8667. DOI: 10.1016/j.ufug.2018.01.010
Honkavaara, E., Khoramshahi, E. Radiometric Correction of Close-Range Spectral Image Blocks Captured Using an Unmanned Aerial Vehicle with a Radiometric Block Adjustment. Remote Sensing, 2018, 10, 256. DOI: 10.3390/rs10020256
Tuominen, S., Näsi, R., Honkavaara, E., Balazs, A., Hakala, T., Viljanen, N., Pölönen, I., Saari, H., Ojanen, H. Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity. Remote Sensing, 2018, 10, 714. DOI: 10.3390/rs10050714
Miyoshi, G., Imai, N., Tommaselli, A., Honkavaara, E., Näsi, R., Moriya, E. Radiometric block adjustment of hyperspectral image blocks in the Brazilian environment. International Journal of Remote Sensing, 2018, 143-1161 DOI: 10.1080/01431161.2018.1425570
Saarinen, N., Vastaranta, M., Näsi, R., Rosnell, T., Hakala, T., Honkavaara, E., Wulder, M.A., Luoma, V., Tommaselli, A.M.G., Imai, N.N., Ribeiro, E.A.W., Guimarães, R.B., Holopainen, M., Hyyppä, J. Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sensing, 2018, 10, 338. DOI: 10.3390/rs10020338
Näsi, R., Viljanen, N., Oliveira, R., Kaivosoja, J., Niemeläinen, O., Hakala, T., Markelin, L., Nezami, S., Suomalainen, J., Honkavaara, E. Optimizing Radiometric Processing and Feature Extraction of Drone Based Hyperspectral Frame Format Imagery for Estimation of Yield Quantity and Quality of a Grass Sward. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, Pages 1305-1310. DOI: 10.5194/isprs-archives-XLII-3-1305-2018
2017
Honkavaara, E., Rosnell, T., Oliveira, R., Tommaselli, A. Band registration of tuneable frame format hyperspectral UAV imagers in complex scenes. ISPRS Journal of Photogrammetry and Remote Sensing. Volume 134, December 2017, Pages 96–109. DOI: 10.1016/j.isprsjprs.2017.10.014
Tuominen S., Balazs A., Honkavaara E., Pölönen I., Saari H., Hakala T., Viljanen N. Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables. Silva Fennica vol. 51 no. 5 article id 7721. DOI: 10.14214/sf.7721
Jaakkola, A., Hyyppä, J., Yu, X., Kukko, A., Kaartinen, H., Liang, X., Hyyppä, H., Wang, Y. Autonomous Collection of Forest Field Reference—The Outlook and a First Step with UAV Laser Scanning. Remote Sensing, 2017, 9, 785. DOI: 10.3390/rs9080785
L. Markelin, E. Honkavaara, R. Näsi, N. Viljanen, T. Rosnell, T. Hakala, M. Vastaranta, T. Koivisto, M. Holopainen. Radiometric correction of multitemporal hyperspectral UAS image mosaics of seedling stands. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 113-118, DOI: 10.5194/isprs-archives-XLII-3-W3-113-2017
N. Saarinen, M. Vastaranta, R. Näsi, T. Rosnell, T. Hakala, E. Honkavaara, M. A. Wulder, V. Luoma, A. M. G. Tommaselli, N.N. Imai, E. A.W. Ribeiro, R.B. Guimarães, M. Holopainen, J. Hyyppä. UAV-based photogrammetric point clouds and hyperspectral imaging for mapping biodiversity indicators in boreal forests. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 171-175, DOI: 10.5194/isprs-archives-XLII-3-W3-171-2017
A. Berveglieri, A.M.G. Tommaselli, E. Honkavaara. Estimating exterior orientation parameters of hyperspectral bands based on polynomial models. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 19-25, DOI: 10.5194/isprs-archives-XLII-3-W3-19-2017
N.N. Imai, E.A.S. Morya, E. Honkavaara, G.T. Miyoshi, M.V.A. de Moares, A.M.G. Tommaselli, R. Näsi. Analysis of radiometric response of orange three crown in hyperspectral UAV images. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 73-79, DOI: 10.5194/isprs-archives-XLII-3-W3-73-2017
S. Tuominen, R. Näsi, E. Honkavaara, A. Balazsa, T. Hakala, N. Viljanen, I. Pölönen, H. Saari, J. Reinikainen. Tree species recognition in species rich area usin UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 185-194, DOI: 10.5194/isprs-archives-XLII-3-W3-185-2017
R. Näsi, N. Viljanen, J. Kaivosoja, T. Hakala, M. Pandzic, L. Markelin, E. Honkavaara. Assessment of various remote sensing technologies in biomass and nitrogen content estimaaation using an agricultural test field. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 137-141, DOI: 10.5194/isprs-archives-XLII-3-W3-137-2017
A.-L. Erkkilä, I. Pölönen, A. Lindfors, E. Honkavaara, K. Nurminen, R. Näsi. Choosing of optimal reference samples for boreal lake chlorophyll a concentration modeling using aerial hyperspectral data. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 39-46, DOI: 10.5194/isprs-archives-XLII-3-W3-39-2017
W. Liu, J. Atherton, M. Mõttus, A. MacArthur, T. Hakala, K. Maseyk, I. Robinson, E. Honkavaara, A. Porcar-Castell. Upscaling of solar induced chlorophyll fluorescence from leaf to canopy using the DART model and a realistic 3D forest scene. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 107-111, DOI: 10.5194/isprs-archives-XLII-3-W3-107-2017
Näsi, R., Honkavaara, E., Hakala, T., Viljanen, N., Peltonen-Sainio, P. How Farmer Can Utilize Drone Mapping? In proceedings of FIG Working Week 2017: Surveying the world of tomorrow – From digitalisation to augmented reality. Helsinki, Finland, May 29–June 2, 2017. Link
Nevalainen, O., Rosnell, T., Hakala, T., Honkavaara, E., Näsi, R., Nurminen, K. Unmanned Aerial Vehicles in Municipality Level 3D Topographic Data Production in Urban Areas. In proceedings of FIG Working Week 2017: Surveying the world of tomorrow – From digitalisation to augmented reality. Helsinki, Finland, May 29–June 2, 2017. Link FIG Article of the Month: July 2017
Khoramshahi, E., Honkavaara, E., Rosnell, T. An Automatic Method for Adjustment of a Camera Calibration Room. In proceedings of FIG Working Week 2017: Surveying the world of tomorrow – From digitalisation to augmented reality. Helsinki, Finland, May 29–June 2, 2017. Link
Nevalainen, O., Honkavaara, E., Tuominen, S., Viljanen, N., Hakala, T., Yu, X.; Hyyppä, J., Saari, H., Pölönen, I., Imai, N.N., Tommaselli, A.M.G. Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sensing, 2017, 9, 185. DOI: 10.3390/rs9030185 Link
Chen, Y., Hakala, T., Karjalainen, M., Feng, Z., Tang, J., Litkey, P., Kukko, A., Jaakkola, A., Hyyppä, J. UAV-Borne Profiling Radar for Forest Research. Remote Sensing, 2017; 9(1):58. DOI:10.3390/rs9010058 Link.
2016
de Oliveira, R., Tommaselli, A., Honkavaara, E. Geometric Calibration of a Hyperspectral Frame Camera. The Photogrammetric Record. 31.155 (2016): 325-347. Link.
Nevalainen, O., Honkavaara, E., Hakala T., Kaasalainen, S., Viljanen, N., Rosnell, T., Khoramshahi, E., Näsi, R. Close-range environmental remote sensing with 3D hyperspectral technologies. Proc. SPIE 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII, 1000503 (October 18, 2016). DOI: 10.1117/12.2240936 Link
Honkavaara, E., Hakala, T., Nevalainen, O., Viljanen, N., Rosnell, T., Khoramshahi, E., Näsi, R., Oliveira, R, Tommaselli, A. Geometric and reflectance signature characterization of complex canopies using hyperspectral stereoscopic images from UAV and terrestrial platforms. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XLI-B7, 77-82. DOI: 10.5194/isprs-archives-XLI-B7-77-2016 Link to full text
Näsi, R., Honkavaara, E., Tuominen, S., Saari, H., Pölönen, I., Hakala, T., Viljanen, N., Soukkamäki, J., Näkki, I., Ojanen, H., Reinikainen, J. Uas Based Tree Species Identification Using the Novel FPI Based Hyperspectral Cameras in Visible, NIR and SWIR Spectral Ranges. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XLI-B1, 1143-1148. DOI: 10.5194/isprs-archives-XLI-B1-1143-2016 Link to full text
Matikainen, L., Lehtomäki, M., Ahokas, E., Hyyppä, J., Karjalainen, M., Jaakkola, A., Kukko, A., Heinonen, T. Remote sensing methods for power line corridor surveys. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 119, pp. 10-31. DOI: 10.1016/j.isprsjprs.2016.04.011 Link.
Honkavaara, E., Eskelinen, M., Pölönen, I.; Saari, H.; Ojanen, H.; Mannila, R.; Holmlund, C.; Hakala, T.; Litkey, P.; Rosnell, T.; Viljanen, N.; Pulkkanen, M. Remote sensing of 3D geometry and surface moisture of peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard small unmanned airborne vehicle (UAV). IEEE Transactions on Geoscience and Remote Sensing, 54(9). Page(s): 5440 – 5454 DOI: 10.1109/TGRS.2016.2565471 Link to full text
Tommaselli, A. M. G., Berveglieri, A., Oliveira, R.A., Nagai, L.Y., Honkavaara E. Orientation and calibration requirements for hyperspectral imaging using UAVs: A case study. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W4, 109-115, DOI: 10.5194/isprs-archives-XL-3-W4-109-2016 Link to pdf.
Oliveira, R.A., Tommaselli, A. M. G., Honkavaara, E., Using Hyperspectral Frame Images from Unmanned Airborne Vehicle for Detailed Measurement of Boreal Forest 3D Structure. IOP Conf. Series: Earth and Environmental Science 44 (2016) 042029 DOI: 10.1088/1755-1315/44/4/042029 Link to full text
2015
Näsi, R., Honkavaara, E., Lyytikäinen-Saarenmaa, P., Blomqvist, M., Litkey, P., Hakala, T., Viljanen, N., Kantola, T., Tanhuanpää, T., Holopainen, M. Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level. Remote Sensing, 2015, 7, 15467-15493. DOI:10.3390/rs71115467 Link.
2014
Honkavaara, E., Markelin, L., Hakala, T., Peltoniemi, J., 2014. The Metrology of Directional, Spectral Reflectance Factor Measurements Based on Area Format Imaging by UAVs, PFG 2014 / 3, 0185–0198. Link.
Hakala T., Honkavaara E., Markelin L. Hemispherical Directional Reflectance Factor using UAV and a hyperspectral camera, validation and crop field test. Proc SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, Amsterdam, Netherlands, 22 – 25 September 2014. DOI: 10.1117/12.2067269 Link.
Pölönen, I., Puupponen H-H., Honkavaara E., Lindfors A., Saari H., Markelin L, Hakala T., Nurminen K. UAV-based hyperspectral monitoring of small freshwater area. Proc SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, Amsterdam, Netherlands, 22 – 25 September 2014. DOI: 10.1117/12.2067422 Link
2013
Delalieux, S., Raymaekers, D., Nackaerts, K., Honkavaara, E., Soukkamäki, J., Van Den Borne, J., 2014. High spatial and spectral remote sensing for detailed mapping of potato plant parameters. WHISPERS, 6th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing 24-27 June 2014, Lausanne, Switzerland.
Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I. Spectral imaging from UAVs under varying illumination conditions. In G. Grenzdörffer, & R. Bill (Eds.), UAV-g2013, 4–6 September 2013, Rostock, Germany (pp. 189-194). Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W2. Link.
Honkavaara, E.; Saari, H.; Kaivosoja, J.; Pölönen, I.; Hakala, T.; Litkey, P.; Mäkynen, J.; Pesonen, L. Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture. Remote Sensing. 2013, 5, 5006-5039. Link.
Kaivosoja, J., Pesonen, L., Kleemola, J., Pölönen, I., Salo, H., Honkavaara, E., Saari, H., Mäkynen, J., Rajala, A., 2013. A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data. In C. Neale, & A. Maltese (Eds.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XV (pp. 88870H). SPIE Conference Proceedings, 8887. SPIE – International Society for Optical Engineering. Link.
Lin, Y., Hyyppa, J., Rosnell, T., Jaakkola, A., Honkavaara, E., 2013. Development of a UAV-MMS-Collaborative Aerial-to-Ground Remote Sensing System – A Preparatory Field Validation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(4): 1893 – 1898. Link.
Pölönen, I., Saari, H., Kaivosoja, J., Honkavaara, E., & Pesonen, L. (2013). Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. In C. Neale, & A. Maltese (Eds.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XV. SPIE Conference Proceedings, 8887. SPIE – International Society for Optical Engineering. Link.
Saari, H., Pölönen, I., Salo, H., Honkavaara, E., Hakala, T., Holmlund, C., Mäkynen, J., Mannila, R., Antila, T., Akujärvi, A., 2013. Miniaturized hyperspectral imager calibration and UAV flight campaigns. In R. Meynart, S. P. Neeck, & H. Shimoda (Eds.), Sensors, Systems, and Next-Generation Satellites XVII. SPIE Conference Proceedings, 8889. SPIE – International Society for Optical Engineering. Link.
2012
Honkavaara, E., Kaivosoja, J., Mäkynen, J., Pellikka, I., Pesonen, L., Saari, H., Salo, H., Hakala, T., Markelin, L., and Rosnell, T, 2012. Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-7, 353-358, doi:10.5194/isprsannals-I-7-353-2012 Link.
Honkavara, E., Hakala, T., Saari, H., Markelin, L., Mäkynen, J., Rosnell, T., 2012. A process for radiometric correction of UAV image blocks. Photogrammetrie, Fernerkundung, Geoinformation (PFG) 2/2012. Link.
Pölönen, I., Salo, H., Saari, H., Kaivosoja, J., Pesonen, L., & Honkavaara, E. (2012). Biomass estimator for NIR image with a few additional spectral band images taken from light UAS. In M. S. Kim, S.-I. Tu, & K. Chao (Eds.), Sensing for Agriculture and Food Quality and Safety IV. Proceedings of SPIE, 8369. Bellingham, WA: SPIE. Link.
Rosnell, T., Honkavaara, E., 2012. Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera. Sensors, 2012, 12, pp. 453-480. Link.
2010
Jaakkola, A., Hyyppä, J., Kukko, A., Yu, X., Kaartinen, H., Lehtomäki, M., Lin, Y. A Low-cost multi sensorial mobile mapping system and its feasibility for tree measurements. ISPRS Journal of Photogrammetry and Remote Sensing. 2010, 65, 514–522. Link.
