Here you can view publications within the subject area of Forest Remote Sensing. To view all publications at SLU, visit the publication database.
Axelsson, A. (2023) Tree Species Classification: Analyzing Multitemporal Satellite Imagery and Multispectral Airborne Laser Scanning Data. Acta Universitatis Agriculturae Sueciae.
Huuva, I. (2023) Estimation of change in forest variables using synthetic aperture radar. Acta Universitatis Agriculturae Sueciae.
Axelsson, C.R., Lindberg, E., Persson, H. J., and Holmgren, J. (2023) The use of dual-wavelength airborne laser scanning for estimating tree species composition and species-specific stem volumes in a boreal forest, International Journal of Applied Earth Observation and Geoinformation, 10.1016/j.jag.2023.103251
García-Cimarras, A., Manzanera, J.A., and Valbuena, R. (2023) LiDAR Scan Density and Spatial Resolution Effects on Vegetation Fuel Type Mapping, Croatian Journal of Forest Engineering, 10.5552/crojfe.2023.1689
Gebresenbet, G., Bosona, T., Patterson, D., Persson, H.J., Fischer, B.M.C., Mandaluniz, N., Chirici, G., Zacepins, A., Komasilovs, V., Pitulac, T., and Nasirahmadi, A. (2023) A concept for application of integrated digital technologies to enhance future smart agricultural systems, Smart agricultural technology, 10.1016/j.atech.2023.100255
Goodbody, T.R.H., Coops, N.C., Queinnec, M., White, J.C., Tompalski, P., Hudak, A.T., Auty, D., Valbuena, R., LeBoeuf, A., Sinclair, I., McCartney, G., Prieur, J-F., and Woods, M.E. (2023) sgsR: a structurally guided sampling toolbox for LiDAR-based forest inventories, Forestry: An International Journal of Forest Research, 10.1093/forestry/cpac055
Gonzalez, A., ... ...Valbuena, R., ... and Torrelio, C.Z. (2023) A global biodiversity observing system to unite monitoring and guide action, Nature Ecology & Evolution, 10.1038/s41559-023-02171-0
Huo, L., Lindberg, E., Bohlin, J., and Persson, H. J. (2023) Assessing the detectability of European spruce bark beetle green attack in multispectral drone images with high spatial- and temporal resolutions, Remote Sensing of Environment, 10.1016/j.rse.2023.113484
Huo, L., Strengbom, J., Lundmark, T., Westerfelt, P., and Lindberg, E. (2023) Estimating the conservation value of boreal forests using airborne laser scanning, Ecological Indicators, 10.1016/j.ecolind.2023.109946
Huuva, I., Wallerman, J., Fransson, J.E.S., and Persson, H.J. (2023) Prediction of Site Index and Age Using Time Series of TanDEM-X Phase Heights, Remote Sensing, 10.3390/rs15174195
Karvemo, S., Huo, L., Öhrn, P., Lindberg, E., and Persson, H.J. (2023) Different triggers, different stories: Bark-beetle infestation patterns after storm and drought-induced outbreaks, Forest Ecology and Management, 10.1016/j.foreco.2023.121255
Larson, J., Wallerman, J., Peichl, M., and Laudon, H. (2023) Soil moisture controls the partitioning of carbon stocks across a managed boreal forest landscape, Scientific Reports, 10.1038/s41598-023-42091-4
Latifi, H., Valbuena, R., and Silva, C.A. (2023) Towards complex applications of active remote sensing for ecology and conservation, Methods in Ecology and Evolution, 10.1111/2041-210X.14154
Mukhopadhyay, R., Naesset, E., Gobakken, T., Mienna, I.M., Bielza, J.C., Austrheim, G., Persson, H.J., Orka, H.O., Roald, B-E., Bollandsas, O.M. (2023) Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference, Remote Sensing, 10.3390/rs15143508
Olofsson, K., and Holmgren, J. (2023) Stem Quality Estimates Using Terrestrial Laser Scanning Voxelized Data and a Voting-Based Branch Detection Algorithm, Remote Sensing, 10.3390/rs15082082
Peichl, M., Martinez-Garcia, E., Fransson, J.E.S., Wallerman, J., Laudon, H., Lundmark, T., and Nilsson, M.B. (2023) On the uncertainty in estimates of the carbon balance recovery time after forest clear-cutting, Global Change Biology, 10.1111/gcb.16772
Peng, X., Jiang, S.C., Liu, S.G., Valbuena, R., Smith, A., Zhan, Y., Shi, Y., Ning, Y., Feng, S.L., Gao, H.Q., and Wang, Z. (2023) Long-term satellite observations show continuous increase of vegetation growth enhancement in urban environment, Science of the Total Environment, 10.1016/j.scitotenv.2023.165515
Sopp, S., and Valbuena, R. (2023) Vascular Optimality Dictates Plant Morphology away from Leonardo’s Rule, Proceedings of the National Academy of Sciences of the United States of America (PNAS) 10.1073/pnas.2215047120
Scheeres, J., ... ... Valbuena, R., ... and de Almeida, D.R.A. (2023) Distinguishing forest types in restored tropical landscapes with UAV-borne LIDAR, Remote Sensing of Environment, 10.1111/rec.13890
Stoddart, J., Suarez, J., Mason, W., and Valbuena, R. (2023) Continuous Cover Forestry and Remote Sensing: A Review of Knowledge Gaps, Challenges, and Potential Directions, Current Forestry Reports, 10.1007/s40725-023-00206-0
Turubanova, S., ... ... Valbuena, R., ... and Stolle, F. (2023) Tree canopy extent and height change in Europe, 2001-2021, quantified using Landsat data archive, Remote Sensing of Environment, 10.1016/j.rse.2023.113797
Nilsson, M., Ardo, J., Söderström, M., Allard, A., Brown, A., and Webber, L. (2023) Remote sensing and Earth observation systems, In: Monitoring biodiversity: - combining environmental and social data, 10.4324/9781003179245-7
Bergström Elias, 2023. Drone images and AI for estimating stand volume and tree species proportion Applied on high-resolution low overlap orthophotos. Supervisor: Jonas Bohlin
Forslöw Erik 2023. Estimating basal area weighted mean height and stem volume by using data from stereo-matched drone imagery through pre-existing models from Skogliga grunddata. Supervisor: Jonas Bohlin
Adnan, S.; Valbuena, R.; Kauranne, T.; Gopalakrishnan, R. & Maltamo, M. (2022). Optimizing the airborne laser scanning estimation of basal area larger than mean (BALM): An indicator of cohort balance in forests. Ecological Indicators, 142.
Duncanson, L.; Kellner, J.R.; Armston, J. …Valbuena , R.;… (2022). Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission. Remote Sensing of Environment, 270.
Holmgren, J.; Lindberg, E.; Olofsson, K. & Persson, H.J. (2022). Tree crown segmentation in three dimensions using density models derived from airborne laser scanning. International Journal of Remote Sensing, 43(1)299-329.
Huo, L.; Lindberg, E. & Holmgren, J. (2022). Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD). Remote Sensing of Environment, 270.
Leite, R.V.; Silva, C.A.; Broadbent, E.N.; Amaral, C.H.; Liesenberg, V.; Almeida, D.R.A.; Mohan, M.; Godinho, S.; Cardil, A.; Hamamura, C.; Faria, B.L.; & … Valbuena, R. (2022) Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data. Remote Sensing of Environment, 268.
Li, N.; Huo, L. & Zhang, X. (2022). Classification of pine wilt disease at different infection stages by diagnostic hyperspectral bands. Ecological Indicators, 142.
Lindgren, N.; Nyström, K.; Saarela, S.; Olsson, H. & Ståhl, G. (2022). Importance of Calibration for Improving the Efficiency of Data Assimilation for Predicting Forest Characteristics. Remote Sensing, 14(18)4627.
Lindgren, N.; Olsson, H.; Nyström, K.; Nyström, M. & Ståhl, G. (2022). Data Assimilation of Growing Stock Volume Using a Sequence of Remote Sensing Data from Different Sensors. Canadian Journal of Remote Sensing, 48(2)127-143.
Nabuurs, G.G.; Harris, N.; Sheil, D.; Palahi, M.; Chirici, G.; Boissière, M.; Fay, C.; Reiche, J. & Valbuena, R. (2022). Glasgow forest declaration needs new modes of data ownership. Nature Climate Change, 12(5)415-417.
Nilsson, M.B.; Laudon, H.; Lundmark, T.; Fransson, J.E.S.; Wallerman, J. & Peichl, M. (2022). Overstory dynamics regulate the spatial variability in forest-floor CO2 fluxes across a managed boreal forest landscape. Agricultural and Forest Meteorology, 318.
Olofsson, K. & Holmgren, J. (2022). Co-registration of single tree maps and data captured by a moving sensor using stem diameter weighted linking. Silva Fennica, 56(3).
Peichl, M.; Martinez-Garcia, E.; Fransson, J.E.S.; Wallerman, J.; Laudon, H.; Lundmark, T.& Nilsson, M. B. (2022). Landscape-variability of the carbon balance across managed boreal forests. Global Change Biology, 29(4).
Persson, H.J.; Olofsson, K. & Holmgren, J. (2022). Two-phase forest inventory using very-high-resolution laser scanning. Remote Sensing of Environment, 271.
Persson, H.J.; Ekström, M. & Ståhl, G. (2022). Quantify and account for field reference errors in forest remote sensing studies. Remote Sensing of Environment, 283:113302.
Pires, R.P.; Olofsson K.; Persson, H.J.; Lindberg, E. & Holmgren, J. (2022). Individual tree detection and estimation of stem attributes with mobile laser scanning along boreal forest roads. ISPRS Journal of Photogrammetry and Remote Sensing, 187. 211224.
Silva, C.A.; Hudak, A.T.; Vierling, L.A.; Valbuena, R.; Cardil, A.; Mohan, M.; Alves Almeida, D.R.; Broadbent, E.N.; Zambrano, A.M.A.; Wilkinson, B.; Sharma, A.; Drake, J.B.; Medley, P.B.; Vogel, J.G.; Prata, G.A.; Atkins, J.W.; Hamamura, C.; Johnson, D.J. & Klauberg, C. (2022). Treetop: A Shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists. Methods in Ecology and Evolution, 13.
Stoddart, J.; Alves de Almeida, D.R.; Silva, C.A.; Gorgens, E.B.; Keller, M. & Valbuena, R. (2022). A conceptual model for detecting small-scale forest disturbances based on ecosystem morphological traits. Remote Sensing, 14(4)933.
Thulin, C.G.; Sorhammar, M. & Bohlin, J. (2022). Black Stork Back: Species distribution model predictions of potential habitats for Black Stork Ciconia nigra in Sweden. Ornis Svecia, 32.
Wallin, E.; Wiberg, V.; Vesterlund, F.; Holmgren, J.; Persson, H. J. & Servin, M. (2022). Learning multiobjective rough terrain traversability. Journal of Terramechanics, 102. 17-26.
Yu, R.; Huo, L.; Huang, H.; Yuan, Y.; Gao, B.; Liu, Y.; Yu, L.; Li, H.; Yang, L.; Ren, L.; & Luo, Y. (2022). Early detection of pine wilt disease tree candidates using time-series of spectral signatures, Frontiers in Plant
Science, 13.
Munira, Sirajum, 2022.Transferability Analysis of Individual Tree Species Classification and Volume Estimation using Dual-Wavelength Airborne Laser Scanning in Boreal Forests. Supervisor: Eva Lindberg
Lindgren, N. (2021). Data assimilation of forest variables predicted from remote sensing data. Department of Forest Resource Management, SLU, no. 2021:6.
Axelsson, A.; Lindberg, E.; Reese, H. & Olsson, H. (2021). Tree species classification using Sentinel-2 imagery and Bayesian inference. International Journal of Applied Earth Observation and Geoinformation. 100.
Bohlin, I.; Maltamo Assessment, M.; Hedenås, H.; Lämås, T.; Dahlgren, J. & Mehtätalo, L. (2021). Predicting bilberry and cowberry yields using airborne laser scanning and other auxiliary data combined with National Forest Inventory field plot data. Forest Ecology and Management. 502.
Bohlin, J.; Wallerman, J. & Fransson, J.E.S. (2021). Extraction of spectral information from airborne 3D data for of tree species proportions. Remote Sensing. 13(4).
Breidenbach, J.; Ivanovs, J.; Kangas, A.; Nord-Larsen, T.; Nilsson, M. & Astrup, R. (2021). Improving living biomass C-stock loss estimates by combining optical satellite, airborne laser scanning, and NFI data. Canadian Journal of Forest Research. 51(10)1472-1485.
Huo, L.; Persson, H-J. & Lindberg, E. (2021). Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS). Remote Sensing of Environment. 255.
Huo, L., & Xiaoli, Z. (2021). The Method of Matching Single Tree Information Extracted by Point Cloud to the Reference Data from Field Work through Bidirectional Selection. Scientia Silvae Sinica. 57(3)181-188.
Huo, L., & Xiaoli, Z. (2021). Individual Tree Information Extraction and Accuracy Evaluation Based on Airborne LiDAR Point Cloud by Multilayer Clustering Method. Scientia Silvae Sinica. 57(1)85-94.
Klein, J.; Low, M.; Thor, G.; Sjögren, J.; Lindberg, E. & Eggers, S. (2021). Tree species identity and composition shape the epiphytic lichen community of structurally simple boreal forests over vast areas. PLoS ONE. 16(9).
Lindberg, E.; Holmgren, J. & Olsson, H. (2021). Classification of tree species classes in a hemi-boreal forest from multispectral airborne laser scanning data using a mini raster cell method. International Journal of Applied Earth Observation and Geoinformation. 100.
Lindgren, N.; Wästlund, A.; Bohlin, I.; Nyström, K.; Nilsson, M. & Olsson, H. (2021). Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data. Scandinavian Journal of Forest Research. 36(5)401-407.
Lundbäck, M.; Persson, H.; Häggström, C. & Nordfjell, T. (2021). Global analysis of the slope of forest land. Forestry. 94(1)54-69.
Marra, E.; Wictorsson, R.; Bohlin, J.; Marchi, E. & Nordfjell, T. (2021). Remote measuring of the depth of wheel ruts in forest terrain using a drone. International Journal of Forest Engineering. 32(3)224-234.
Miina, J.; Bohlin, I.; Lind, T.; Dahlgren, J.; Harkonen, K.; Packalen, T. & Tolvanen, A. (2021). Lessons learned from assessing the cover and yield of bilberry and lingonberry using the national forest inventories in Finland and Sweden. Silva Fennica. 55(5).
Palahi, M. ; Valbuena, R.; Senf, C.; Acil, N.; Pugh, T. A. M.; Sadler, J.; Seidl, R.; Potapov, P; Gardiner, B.; Hetemaeki, L.; Chirici, G.; Francini, S.; Hlasny, T.; Lerink, B.J.W.; Olsson, H.; Gonzalez O.J.R.; Ascoli, D.; Asikainen, A.; Bauhus, J.; Berndes, G.; Donis, J.; Fridman, J.; Hanewinkel, M.; Jactel, H.; Lindner, M.; Marchetti, M.; Marusak, R.; Sheil, D.; Tome, M.; Trasobares, A.; Verkerk, P.J.; Korhonen, M. & Nabuurs, G-J. (2021). Concerns about reported harvests in European forests. Nature. 592(7856)E15-E17.
Persson, H.J.; Jonzen, J. & Nilsson, M. (2021). Combining TanDEM-X and Sentinel-2 for large-area species-wise prediction of forest biomass and volume. International Journal of Applied Earth Observation and Geoinformation. 96.
Santoro, M.; Cartus, O. & Fransson, J.E.S. (2021). Integration of allometric equations in the water cloud model towards an improved retrieval of forest stem volume with L-band SAR data in Sweden. Remote Sensing of Environment. 253.
Söderberg, J.; Wallerman, J.; Almang, A.; Moller, J.J. & Willen, E. (2021). Operational prediction of forest attributes using standardised harvester data and airborne laser scanning data in Sweden. Scandinavian Journal of Forest Research. 364(4).
Udali, A.; Lingua, E. & Persson, H.J. (2021). Assessing forest type and tree species classification using sentinel-1 C-band SAR data in southern Sweden. Remote Sensing. 13(16).
Genlund, Kristoffer 2021. Skattning av tidpunkt för förstagallring med hjälp av tillväxtmodeller. Supervisor: Jörgen Wallerman
Chi, J.; Nilsson, M.B.; Laudon, H.; Lindroth, A.; Wallerman, J.; Fransson, J.E.S.; Kljun, N.; Lundmark, T.; Ottosson Löfvenius, M. & Peichl, M. (2020). The net landscape carbon balance-integrating terrestrial and aquatic carbon fluxes in a managed boreal forest landscape in Sweden. Global Change Biology. 26(4):2353-2367.
Forzieri ,G.; Pecchi, M.; Girardello, M.; Mauri, A.; Klaus, M.; Nikolov, C.; Rüetschi, M.; Gardiner, B.; Tomaštík, J.; Small, D.; Nistor, C.; Jonikavicius, D.; Spinoni, J.; Feyen, L.; Giannetti, F.; Comino, R.; Wolynski, A.; Pirotti, F.; Maistrelli, F.; Savulescu, I.; Wurpillot-Lucas, S.; Karlsson, S.; Zieba-Kulawik, K.; Strejczek-Jazwinska, P.; Mokroš, M.; Franz, S.; Krejci, L.; Haidu, I.; Nilsson, M.; Wezyk, P.; Catani, F.; Chen, Y-Y.; Luyssaert, S.; Chirici, G.; Cescatti, A. & Beck, P. (2020). A spatially explicit database of wind disturbances in European forests over the period 2000-2018. Earth System Science Data. 12(1):257-276.
Huo, L. & Lindberg, E. (2020). Individual tree detection using template matching of multiple rasters derived from multispectral airborne laser scanning data. International Journal of Remote Sensing. 41(24):9525-9544.
Huuva, I.; Persson, H.J.; Soja, M.J.; Wallerman, J.; Ulander, L.M.H. & Fransson, J.E.S. (2020). Predictions of Biomass Change in a Hemi-Boreal Forest Based on Multi-Polarization L- and P-Band SAR Backscatter. Canadian Journal of Remote Sensing. 46(6):661-680.
Klein, J.; Haverkamp, P.; Lindberg, E.; Griesser, M. & Eggers, S. (2020). Remotely sensed forest understory density and nest predator occurrence interact to predict suitable breeding habitat and the occurrence of a resident boreal bird species. Ecology and Evolution. 10(4):2238-2252.
Klein, J.; Thor, G.; Low, M.; Sjögren, J.; Lindberg, E. & Eggers, S. (2020). What is good for birds is not always good for lichens: Interactions between forest structure and species richness in managed boreal forests. Forest Ecology and Management. 473.
Kozii, N.; Haahti, K.; Torngren, P.; Chi, J.; Maher Hasselquist, E.; Laudon, H.; Launiainen, S.; Oren, R.; Peichl, M.; Wallerman, J. & Hasselquist, N. (2020). Partitioning growing season water balance within a forested boreal catchment using sap flux, eddy covariance, and a process-based model Hydrology and Earth System Sciences. 24(6):2999-3014.
Leonardo, E.; Watt, M.; Pearse, G.; Dash, J. & Persson, H.J. (2020). Comparison of TanDEM-X InSAR data and high-density ALS for the prediction of forest inventory attributes in plantation forests with steep terrain. Remote Sensing of Environment. 246.
Lidberg, W.; Nilsson, M. & Ågren, A. (2020). Using machine learning to generate high-resolution wet area maps for planning forest management: A study in a boreal forest landscape. AMBIO:A Journal of the Human Environment. 49(2):475-486.
Persson, H.J.; Soja, M.J.; Fransson, J.E.S. & Ulander, L.M.H. (2020). National Forest Biomass Mapping Using the Two-Level Model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13:6391-6400.
Persson, H.J. & Ståhl, G. (2020). Characterizing Uncertainty in forest remote sensing studies. Remote Sensing. 12(3).
Stelmaszczuk-Górska, M.; Aguilar-Moreno, E.; Casteleyn, S.; Vandenboucke, D.; Miguel-Lago, M.; Dubois, C.; Lemmens, R.; Vancauwenberghe, G.; Olijslagers, M.; Lang, S.; Albrecht, F.; Belgiu, M.; Kriger, V.; Jagdhuber, T.; Fluhrer, A.; Soja, M.; Mouratidis, A.; Persson, H.J.; Colombo, R. & Masiello, G. (2020). Body of Knowledge for the Earth Observation and Geoinformation Sector – A Basis for Innovative Skills DevelopmentXLIIIB5-2020 pp:15-22. DOI:10.5194/isprs-archives-XLIIIB5-2020-15-2020
Versluijs, M.; Hekkala, A-M.; Lindberg, E. & Lämås, T. (2020). Comparing the effects of even-aged thinning and selective felling on boreal forest birds. Forest Ecology and Management. 475.
Wallerman, J.; Nyström, K.; Nilsson, M.; Axensten, P.; Egberth, M.; Jonzen, J.; Sandström, E.; Fransson, J.E.S. & Olsson, H. Nation-wide mapping of tree growth using repeated airborne laser scanning. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing
Symposium: proceedings.
Zahriban Hesari, M.; Shataee, S.; Maghsoudi, Y.; Mohammadi, J.; Fransson, J.E.S. & Persson, H.J. (2020). Forest variable estimations using TanDEM-X data in hyrcanian forests. Canadian Journal of Remote Sensing. 46(2):166-176.
Adelsköld, G.; Högström, M.; Lagerstedt, J. & Olsson, H. (2020). GET-tjänsten och infrastrukturen för distribution av geodata till universitet och högskolor. Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet. Arbetsrapport/Sveriges lantbruksuniversitet, Institutionen för skoglig resurshushållning. 512.
Forsberg, M.; Sabel, L.; Nässert Ericsson, M.; Paasch, J.; Steffen, H.; Olsson H.; Harrie, L.; Horemuz, M. & Ågren, J. (2020). Långsiktig kompetensförsörjning inom geodataområdet. Geodatarådet.
Solberg, S.; Ulander, L.M.H.; Fransson, J.E.S.; Persson, H.J. & Wallerman, J. (2020). Technical assistance in the implementation of a C-band convoy mission demonstration campaign. In Final report, European Space Agency (ESA). 136 p.
Willen, E.; Söderberg, J.; Lindgren, N.; Olsson, H. & Bohlin, J. 2020. Skogliga fjärranalysskattningar – utvärdering av fotogrammetrimetoder samt laser- och skördardata i gallringsskogar. Arbetsrapport 1067- 2020, Skogforsk. 22 p.
Nilsson, August, 2020. Kartering av lämnade hänsynsområden vid slutavverkning med hjälp av fjärranalys. Supervisor: Jonas Bohlin
Kingstad, Victor, 2020. Evaluated density estimates of young forest stands using high resolution 2D imagery from UAV. Supervisor: Jonas Bohlin
Askne, J.I.H.; Persson, H.J. & Ulander, L.M.H. (2019). On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure. Remote Sensing. 11(14).
Burian, A.; Karaya, R.; Wernersson, J.E.V.; Egberth, M.; Lokorwa, B. & Nyberg, G. (2019). A community-based evaluation of population growth and agro-pastoralist resilience in Sub-Saharan drylands. Environmental Science and Policy. 92:323-330.
Chi, J.S.; Nilsson, M.B.; Kljun, N.; Wallerman, J.; Fransson, J.E.S.; Laudon, H.; Lundmark, T. & Peichl, M. (2019). The carbon balance of a managed boreal landscape measured from a tall tower in northern Sweden. Agricultural and Forest Meteorology. 274:29-41.
Holmgren, J.; Tulldahl, M.; Nordlof, J.; Willen, E. & Olsson, H. (2019). Mobile Laser Scanning for Estimating Tree Stem Diameter Using Segmentation and Tree Spine Calibration. Remote Sensing. 11(23).
Holmgren, J. & Lindberg, E. (2019). Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning. Remote Sensing Letters. 10(12):1143-1152.
Hovi, A.; Lindberg, E.; Lang, M.; Arumae, T.; Peuhkurinen, J.; Sirparanta, S.; Pyankov, S. & Rautiainen, M. (2019). Seasonal dynamics of albedo across European boreal forests: Analysis of MODIS albedo and structural metrics from airborne LiDAR. Remote Sensing of Environment. 224:365-381.
Rodriguez-Veiga, P.; Quegan, S.; Carreiras, J.; Persson, H.J.; Fransson, J.E.S.; Hoscilo, A.; Ziolkowski, D.; Sterenczak, K.; Lohberger, S.; Stangel, M.; Berninger, A.; Siegert, F.; Avitabile, V.; Herold, M.; Mermoz, S.; Bouvet, A.; Toan, T.L.; Carvalhais, N.; Santoro, M.; Cartus, O.; Rauste, Y.; Mathieu, R.; Asner, G.P.; Thiel, C.; Pathe, C.; Schmullius, C.; Seifert, F.M.; Tansey, K. & Balzter, H. (2019). Forest biomass retrieval approaches from earth observation in different biomes. International Journal of Applied Earth Observation and Geoinformation. 77:53-68.
Santoro, M.; Cartus, O.; Fransson, J.E.S. & Wegmuller, U. (2019). Complementarity of X-, C-, and L-band SAR Backscatter Observations to Retrieve Forest Stem Volume in Boreal Forest. Remote Sensing. 11(13).
Fransson, J.E.S.; Olsson, H.; Wallerman, J.; Persson, H.J.; Ulander, L.M.H; Eriksson, L.E.B.; Soja, M.J.; & Santoro, M. (2019). Retrieval of forest biomass and biomass change using PALSAR data. In: Final Report on the 4th ALOS-2 Research Announcement, Japan Aerospace Exploration Agency (JAXA), Earth Observation Research Center (EORC), NDX-2018023. pp. 685-695.
Fransson, J.E.S. & Santoro, M. (2019). K&C Final Science Report – Phase 4, Retrieval of forest biomass and biomass change with spaceborne SAR. In: The ALOS Kyoto & Carbon Initiative, Science Team Reports, Phase
4 (2015-2019), Japan Aerospace Exploration Agency, Earth Observation Research Center, 2-1-1 Sengen, Tsukuba-shi, Ibaraki 305-8505, Japan, JAXA EORC, NDX-2019009. pp. 258-270.
Olsson, H.; Heden, P.; Fröjdenlund, J. & André, P. (2019). Rapport geodatarådets handlingsplan 2018. Aktivitet 1d: Användarbehov inom de areella näringarnas ekosystem, en del av fokusområdet Användarbehov och samhällsnytta. Geodatarådet och Lantmäteriet. Dnr: LM 2019/001170.
Holmgren, Robert, 2019. Reliabilitet i mätning av trädhöjd : en jämförelse mellan fjärranalysmetoder samt mätning i fält. Supervisor: Mattias Nyström.
Isaksson, Joakim och Johansson, Lars, 2019. Metoder för höjdkorrigering av punktmoln generade från drönarbilder. Supervisor: Jonas Bohlin.
Larsson, Karl, 2019. Skattningar av ståndortsindex – med flygburen laserskanning, allmänt tillgänglig information eller skördarmätningar? Supervisor: Jörgen Wallerman.
Lindberg, Lisa och Persson, Martin, 2019. Kan ytmodeller och punktmoln från stereomatchade flygbilder användas för att prediktera trädhöjd vid skogskanter? : en jämförelse mot flygburen laserskanning. Supervisor: Jonas Bohlin.
Udali, Alberto, 2019. Assessing the accuracy for area-based tree species classification using Sentinel-1 C-band SAR data. Supervisor: Henrik Persson.
Forsman, M. 2018. Tree stem diameter estimation from terrestrial point clouds. Department of Forest Resource Management, SLU, no. 2018:54.
Askne, J.I.H., Persson, H.J. and Ulander, L.M.H. 2018. Biomass growth from multitemporal TanDEM-X interferometric Synthetic Aperture Radar observations of a boreal forest site. Remote Sensing, vol. 10, no. 4.
Axelsson, A., Lindberg, E. and Olsson, H. 2018. Exploring multispectral ALS data for tree species classification. Remote Sensing, vol. 10, no. 2.
Ehlers, S., Saarela, S., Lindgren, N., Lindberg, E., Nyström, M., Persson, H., Olsson, H. and Ståhl, G. 2018. Assessing error correlations in remote sensing-based estimates of forest attributes for improved composite estimation. Remote Sensing, vol. 10, no. 5.
Forsman, M., Börlin, N., Olofsson, K., Reese, H. and Holmgren, J. 2018. Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths: A simulation study. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 135, pp. 84-92.
Kangas, A., Astrup, R., Breidenbach, J., Fridman, J., Gobakken, T., Korhonen, K.T., Maltamo, M., Nilsson, M., Nord-Larsen, T., Naesset, E. and Olsson, H. 2018. Remote sensing and forest inventories in Nordic countries - roadmap for the future. Scandinavian Journal of Forest Research, vol. 33, no. 4, pp. 397-412.
Liang, X., Hyyppä, J., Kaartinen, H., Lehtomäki, M., Pyörälä, J., Pfeifer, N., Holopainen, M., Brolly, G., Francesco, P., Hackenberg, J., Huang, H., Jo, H.-W., Katoh, M., Liu, L., Mokroš, M., Morel, J., Olofsson, K., Poveda-
Lopez, J., Trochta, J., Wang, D., Wang, J., Xi, Z., Yang, B., Zheng, G., Kankare, V., Luoma, V., Yu, X., Chen, L., Vastaranta, M., Saarinen, N. and Wang, Y. 2018. International benchmarking of terrestrial laser scanning approaches for forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 144, pp. 137-179.
Vastaranta, M., Yu, X., Luoma, V., Karjalainen, M., Saarinen, N., Wulder, M.A., White, J.C., Persson, H.J., Hollaus, M., Yrttimaa, T., Holopainen M. and Hyyppä J. 2018. Aboveground forest biomass derived using multiple dates of WorldView-2 stereo-imagery: Quantifying the improvement in estimation accuracy. International Journal of Remote Sensing, vol. 39, no. 23, pp. 8766-8783.
Mononen, L., Auvinen, A.-P., Packalen, P., Virkkala, R., Valbuena, R., Bohlin, I., Valkama, J. and Vihervaara, P. 2018. Usability of citizen science observations together with airborne laser scanning data in determining the habitat preferences of forest birds. Forest Ecology and Management, vol. 430, pp. 498-508.
Olofsson, K. and Olsson, H. 2018. Estimating tree stem density and diameter distribution in single-scan terrestrial laser measurements of field plots: A simulation study. Scandinavian Journal of Forest Research, vol. 33, no. 4, pp. 365-377.
Pearse, G.D., Dash, J.P., Persson, H.J. and Watt, M.S. 2018. Comparison of high-density LiDAR and satellite photogrammetry for forest inventory. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 142, pp. 257-267.
Persson, M., Lindberg, E. and Reese, H. 2018. Tree species classification with multi-temporal sentinel-2 data. Remote Sensing, vol. 10, no. 11.
Soja, M.J., Persson, H.J. and Ulander, L.M.H. 2018. Modeling and detection of deforestation and forest growth in multitemporal TanDEMX data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 10, pp. 3548-3563.
Wästlund, A., Holmgren, J., Lindberg, E. and Olsson, H. 2018. Forest variable estimation using a high altitude single photon lidar system. Remote Sensing, vol. 10, no. 9.
Olsson, H., Lindberg, E., Wallerman, J. and Holmgren, J. 2018. Fjärranalysforskning på Remningstorp – exempel från SLU. Arbetsrapport, Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet, vol. 479.
Ellingsson, Anders, 2018. Field- and aerial image estimation of residual timber volumes in Medelpad after the storms of the 2010s. Supervisor: Jörgen Wallerman.
Jansson, Carl, 2018. Identification of uneven-aged stands using photogrammetry and airborne laser scanning. Supervisor: Eva Lindberg.
Larsson, Helene, 2018. Classification of ground lichen using Sentinel-2 and airborne laser data. Supervisor: Heather Reese.
Persson, Magnus, 2018. Tree species classification using multi-temporal Sentinel-2 data. Supervisors: Heather Reese and Eva Lindberg.
Selin, Lina, 2018. Modeling of Effective Leaf Area Index. Supervisor: Henrik Persson.
Wennerlund, Lisa, 2018. Evaluating the need of cleaning using 3D point clouds derived from high resolution images collected with a drone. Supervisors: Jonas Bohlin and Jonas Jonzén.
Bohlin, J. 2017. Data collection for forest management planning using stereo photogrammetry. Department of Forest Resource Management, SLU, no. 2017:109.
Bohlin, J., Bohlin, I., Jonzen, J. and Nilsson, M. 2017. Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the National Forest Inventory. Silva Fennica, vol. 51, no. 2, 18 p.
Bohlin, I., Olsson, H., Bohlin, J. and Granström, A. 2017. Quantifying post-fire fallen trees using multi-temporal lidar. International Journal of Applied Earth Observation and Geoinformation, vol. 63, pp. 186-195.
De Conto, T., Olofsson, K., Görgens, E., Rodriguez, L. and Almeida, G. 2017. Performance of stem denoising and stem modelling algorithms on single tree point clouds from terrestrial laser scanning. Computers and Electronics in Agriculture, vol. 143, pp. 165-176.
Granholm, A-H., Lindgren, N., Olofsson, K., Nyström, M., Allard, A. and Olsson, H. 2017. Estimating vertical canopy cover using dense image-based point cloud data in four vegetation types in southern Sweden. International Journal of Remote Sensing, vol. 38, no. 7, pp. 1820-1838.
Husson, E., Reese, H and Ecke, F. 2017. Combining spectral data and a DSM from UASimages for improved classification of non-submerged aquatic vegetation. Remote Sensing, vol. 9, no. 3, 15 p.
Lindberg, E. and Holmgren, J. 2017. Individual tree crown methods for 3D data from remote sensing. Current Forestry Reports, vol. 3, no. 1, pp. 19-31
Lindgren, N., Persson, H.J., Nyström, M., Nyström, K., Grafström, A., Muszta, A., Willén, E., Fransson J.E.S., Ståhl, G. and Olsson, H. 2017. Improved prediction of forest variables using data assimilation of interferometric synthetic aperture radar data. Canadian Journal of Remote Sensing, vol. 43, no. 4, pp. 374-383.
Milenkovic, M., Schnell, S., Holmgren, J., Ressl, C., Lindberg, E., Hollaus, M., Pfeifer, N. and Olsson, H. 2017. Influence of footprint size and geolocation error on the precision of forest biomass estimates from space-borne waveform LiDAR. Remote Sensing of Environment, vol. 200, pp. 74-88.
Nilsson, M., Nordkvist, K., Jonzen, J., Lindgren, N., Axensten, P., Wallerman, J., Egberth, M., Larsson, S., Nilsson, L., Eriksson, J. and Olsson, H. 2017. A nationwide forest attribute map of Sweden predicted using airborne laser scanning data and field data from the National Forest Inventory. Remote Sensing of Environment, vol. 194, pp. 447-454.
Persson, H.J. and Fransson, J.E.S. 2017. Comparison between TanDEM-X- and ALS-based estimation of aboveground biomass and tree height in boreal forests. Scandinavian Journal of Forest Research, vol. 32, no. 4, pp. 306-319.
Persson, H.J., Olsson, H., Soja, M.J., Ulander, L.M.H. and Fransson, J.E.S. 2017. Experiences from large-scale forest mapping of Sweden using TanDEM-X data. Remote Sensing, vol. 9, no. 12, 26 p
Olofsson, K., Holmgren, J., Lindberg, E., Nyström, M. and Olsson. H. 2017. Markbaserad laserskanning. Fakta Skog, no. 2, Sveriges lantbruksuniversitet.
Axelsson, Arvid, 2017. Using multispectral ALS for tree species identification. Supervisor: Eva Lindberg, SLU.
Benjaminson, Simon, 2017. Forest inventory on individual tree level using stereo matching of aerial images taken from a drone. Supervisor: Jörgen Wallerman, SLU.
Jakobsson, Oscar, 2017. Control assessment using drones at Norra Skogsägarna. Supervisor: Jonas Bohlin, SLU.
Granholm, Ann-Helen (2016). Segmentation of forest patches and estimation of canopy cover using 3D information from stereo photogrammetry. Umeå : Sveriges lantbruksuniv.
Bohlin, J., Wallerman, J. and Fransson, J.E.S. 2016. Deciduous forest mapping using change detection of multi-temporal canopy height models from aerial images acquired at leaf-on and leaf-off conditions. Scandinavian Journal of Forest Research, vol. 31, no. 5, pp. 517-525.
Forsman, M., Börlin, N. and Holmgren, J. 2016. Estimation of tree stem attributes using terrestrial photogrammetry with a camera rig. Forests, vol. 7, no. 3.
Forsman, M., Holmgren, J. and Olofsson, K. 2016. Tree stem diameter estimation from mobile laser scanning using line-wise intensitybased clustering. Forests, vol. 7, no. 9.
Husson, E., Ecke, F. and Reese, H. 2016. Comparison of manual mapping and automated object-based image analysis of non-submerged aquatic vegetation from very-high-resolution UAS Images. Remote Sensing, vol. 8, no. 9.
Karlson, M., Ostwald, M., Reese, H., Bazié, H-R. and Tankoano, B. 2016. Assessing the potential of multi-seasonal WorldView-2 imagery for mapping West African agroforestry tree species. International Journal of Applied Earth Observation and Geoinformation, vol. 50, pp. 80-88.
Naesset, E., Orka, H-O., Solberg, S., Bollandsås, O-M., Hansen, E-H., Mauya, E., Zahabu, E., Malimbwi, R., Olsson, H. and Gobakken, T. 2016. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision. Remote Sensing of Environment, vol. 175, pp. 282-300.
Olofsson, K. and Holmgren, J. 2016. Single tree stem profile detection using terrestrial laser scanner data, flatness saliency features and curvature properties. Forests, vol. 7, no. 9.
Persson, H. 2016. Estimation of boreal forest attributes from very high resolution pleiades data. Remote Sensing, vol. 8, no. 9.
Persson, H. and Fransson, J.E.S. 2016. Estimating site index from short term TanDEM-X canopy height models. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 8, pp. 3598-3606.
Persson, H. and Perko, R. 2016. Assessment of boreal forest height from WorldView-2 satellite stereo images. Remote Sensing Letters, vol. 7, no. 12, pp. 1150-1159.
Roberge, C., Wulff, S., Reese, H. and Ståhl, G. 2016. Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information. Environmental Monitoring and Assessment, vol. 188, no. 4.
Saad, R., Wallerman, J., Holmgren, J. and Lämås, T. 2016. Local pivotal method sampling design combined with micro stands utilizing airborne laser scanning data in a long term forest management planning setting. Silva Fennica, vol. 50, no. 2.
Wang, Y., Hyyppä, J., Liang, X., Kaartinen, H., Yu, X., Lindberg, E., Holmgren, J., Qin, Y., Mallet, C., Ferraz, A. and Torabzadeh, H. 2016. International benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning. IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 9, pp. 5011-5027.
Fransson, J.E.S., Santoro, M., Wallerman, J., Persson, H., Monteith, A.R., Eriksson, L.E.B., Nilsson, M., Olsson, H., Soja, M.J. and Ulander, L.M.H. 2016. Estimation of forest stem volume using ALOS-2 PALSAR-2 satellite images. Proc. IGARSS 2016 - Advancing the understanding of our living planet, IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 2016.
Balzter, H., Rodriguez-Veiga, P., Tansey, K., Carreiras, J., Quegan, S., Persson, H., Hoscilo, A., Dabrowska-Zielinska, K., Stereczak, K. and Schmullius, C. 2016. GLOBBIOMASS - Regional case studies, preparing the ground for global forest biomass mapping. Proc. Living Planet Symposium, Proc. of ESA Living Planet Symposium, Prague, Czech Republic, 9-13 May, 2016.
Ulander, L.M.H., Monteith, A.R., Soja, M.J., Persson, H., Fransson, J.E.S. and Eriksson, L.E.B. 2016. BorealScat: A tower experiment for understanding of temporal changes in P- and Lband backscattering from a boreal forest. Proc. Living Planet Symposium, Proc. of ESA Living Planet Symposium, Prague, Czech Republic, 9-13 May, 2016.
Larsson, S., Nilsson, L., Persson, A., André, P., Eriksson, J., Kristiansson, K., Lysell, G., Nilsson, M., Jonzén, J. and Olsson, H. 2016. Skogliga skattningar från laserdata, Meddelande/ Skogsstyrelsen, no. 4.
Persson, H. 2016. Forestry applications of satellite stereogrammetry using very high resolution (VHR) optical data. The 2016 annual meeting of SRS.
Persson, H., Fransson, J.E.S., Olsson, H., Soja M,J. and Ulander, L.M.H. 2016. TanDEM-X radar challenges airborne laser. The 2016 annual meeting of SRS.
Ulander, L.M.H., Soja M,J., Monteith, A.R., Eriksson, L.E.B., Persson, H. and Fransson, J.E.S. 2016. BorealScat a tower based tomographic and polarimetric radar experiment in the boreal forest. The 2016 annual meeting of SRS.
Forsman, Karl, 2016. Using structure from motion for stockpile inentory in the forest industry. Supervisor: Jonas Bohlin, SLU and Mattias Nyström, SLU.
Romlin Fredriksson, Anton, 2016. Fjärranalysstödd objektiv uppskattning av virkesförråd för värdering av fastigheter. Supervisor: Håkan Olsson, SLU.
Sjödin, Edward, 2016. Analys av säsongsvariationer vid skattning av skogliga variabler med InSAR teknik. Supervisor: Henrik Persson, SLU and Mattias Nyström, SLU.
Straker, Adrian, 2016. Comparison of forest fire severity classification models based on aerial images and Landsat 8 OLI/TIRS images of a forest fire area in central Sweden. Supervisor: Jonas Bohlin, SLU.
Wästlund, André, 2016. Framskrivning av ALS data med TanDEM-X. Supervisor: Henrik Persson, SLU and Nils Lindgren, SLU.
Bohlin, J., Wallerman, J. and Fransson, J.E.S. 2015. Deciduous forest mapping using change detection of multi-temporal canopy height models from aerial images acquired at leaf-on and leaf-off conditions. Scandinavian Journal of Forest Research, vol. 31(5), 517-525.
Eysn, L., Hollaus, M., Lindberg, E., Berger, F., et al. 2015. A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space. Forests, vol. 6(5), 1721-1747.
Granholm, A.-H., Olsson, H., Nilsson, M., Allard, A. and Holmgren, J. 2015. The potential of digital surface models based on aerial images for automated vegetation mapping. International Journal of Remote Sensing, vol. 36(7), 1855-1870.
Karlson, M., Ostwald, M., Reese, H., Sanou, J., Tankoano, B. and Mattsson, E. 2015. Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest. Remote Sensing, vol. 7(8), 10017-10041.
Lindberg, E., Roberge, J-M., Johansson, T. and Hjältén J. 2015. Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest? Remote Sensing, vol. 7(4), 4233-4252.
Lindgren, N., Christensen, P., Nilsson, B., Åkerholm, M., Allard, A., Reese, H. and Olsson, H. 2015. Using Optical Satellite Data and Airborne Lidar Data for a Nationwide Sampling Survey. Reomte Sensing, vol. 7(4), 4253-4267.
Lämås, T., Sandström, E., Jonzén, J., Olsson, H., and Gustafsson, L. 2015. Tree retention practices in boreal forests – what kind of future landscapes are we creating? Scandinavian Journal of Forest Research, vol. 30(6).
Nyström, M., Lindgren, N., Wallerman, J., et al. 2015. Data Assimilation in Forest Inventory: First Empirical Results. Forests, vol. 6(12), 4540-4557.
Reese, H., Nordkvist, K., Nyström, M., Bohlin, J. and Olsson, H. 2015. Combining point clouds from image matching with SPOT 5 multispectral data for mountain vegetation classification. International Journal of Remote Sensing, vol. 36(2), 403-416.
Saad, R., Wallerman, J. and Lämås, T. 2015. Estimating stem diameter distributions from airborne laser scanning data and their effects on long term forest management planning. Scandinavian Journal of Forest Research, vol. 30(2), 186-196.
Saarela, S., Grafström, A., Ståhl, G., Kangas, A., Holopainen, M., Tuominen, S., Nordkvist, K., Hyyppä, J. 2015. Model-assisted estimation of growing stock volume using different combinations of LiDAR and Landsat data as auxiliary information. Remote Sensing of Environment, vol. 158, 431-440.
Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J.E.S, et al. 2015. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sensing of Environment, vol. 168, 316-334.
Santoro, M., Eriksson, L.E.B. and Fransson, J.E.S. 2015. Reviewing ALOS PALSAR Backscatter Observations for Stem Volume Retrieval in Swedish Forest. Remote Sensing, vol. 7(4), 4290-4317.
Soja, M.J., Persson, H. and Ulander, L.M.H. 2015. Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data. IEEE Transactions on Geoscience and Remote Sensing, vol. 53(9), 5083-5099.
Soja, M.J., Persson, H. and Ulander, L.M.H. 2015. Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient. IEEE Geoscience and Remote Sensing Letters, vol. 12(3), 646-650.
Solberg, S., Gizachew, B., Nasset, E., et al. 2015. Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+. Carbon Balance and Management, vol. 10(14).
Adler, S., Blicharska, M., Esselin, A., Hedblom, M., Hedenås, H., Mikusinski, G., Sandström, S., Sandström, P., Svensson, J., Wardel, D. and Reese, H. 2015. Modelling the distribution of reindeer lichens as a proxy for the Ecosystem service reindeer meat: An example from the project “National monitoring for assessing and valuating ecosystem services in Fennoscandian alpine and boreal landscapes”. Poster Tartu Aug 2015 – in press.
Bohlin, J., Blombäck, J., Wallerman, J. and Fransson, J. 2015. Updating the National Forest Attribute Map using stereo matching of aerial images, the national terrain model and data from the National Forest Inventory? SilviLaser 2015, La Grand Motte, France, September 28-30, 2015.
Granholm, A., Lindgren, N., Olofsson, K., Allard, A. and Olsson, H. 2015. Estimating vertical canopy cover with dense point cloud data from matching of digital aerial photos. EARSel, 2015, Stockholm, Sweden, June 15-18, 2015.
Holmgren, J., Olofsson, K., Nyström, M. and Olsson, H. 2015. Estimation of tree stem attributes using ground based and airborne laser scanning. SilviLaser 2015, La Grand Motte, France, September 28-30, 2015.
Husson, E., Reese, H. and Ecke, F. 2015. Comparison of manual mapping and object-based digital image analysis for identifying aquatic vegetation in 5cm-resolution remote sensing images. 14th International Symposium on Aquatic Plants, Edinburgh, Scotland, September 14-18, 2015.
Lindgren, N., Nyström, M., Wallerman, J., Ehlers, S., Grafström, A., Muszta, A., Nyström, K., Willén, E., Fransson, J.E.S., Bohlin, J., Olsson, H. and Ståhl, G. 2015. Data assimilation in stand level forest inventory – first results. IBFRA 2015, Rovaniemi, Finland, May 24-29, 2015.
Lindberg, E., Roberge, J-M., Johansson, T., Hollaus, M., Holmgren, J. and Hjältén, J. 2015. Individual tree properties from ALS data as input to habitat analysis in boreal forest. SilviLaser 2015, La Grand Motte, France, September 28-30, 2015.
Lindberg, E., Roberge, J-M., Johansson, T. and Hjältén, J. 2015. Does detailed vegetation structure derived from airborne laser scanning (ALS) contribute to prediction of abundance and species richness of birds and beetles in boreal forest? Book of Abstracts, IUFROLE WG Conference in Tartu, Estonia, 2015: Sustaining ecosystem services in forest landscapes. pp.96-96.
Lindberg, E., Briese, C., Doneus, M., Hollaus, M., Schroiff, A. and Pfeifer, N. 2015. Multi-wavelength Airborne Laser Scanning for Characterization of Tree Species. Proceedings of SilviLaser 2015: 14th conference on Lidar Applications for Assessing and Managing Forest Ecosystems. La Grande Motte, France. pp 271-273.
Nilsson, M., Nordkvist, K., Jonzén, J., Lindgren, N., Axensten, P., Wallerman, J., Egberth, M., Larsson, S., Nilsson, L., Eriksson, J. and Olsson, H. 2015. A nationwide forest attribute map of Sweden derived using airborne laser scanning data and field data from the national forest inventory. SilviLaser 2015, La Grand Motte, France, September 28-30, 2015.
Nyström, M., Lindgren, N., Wallerman, J., Ehlers, S., Grafström, A., Muszta, A., Nyström, K., Willén, E., Fransson, J.E.S., Bohlin, J., Olsson, H. and Ståhl, G. 2015. Assimilating remote sensing data with forest growth models. EARSeL, 2015, Stockholm, Sweden, June 15-18, 2015.
Nyström, M., Lindgren, N., Wallerman, J., Grafström, A., Muszta, A., Nyström, K., Ståhl, G. and Olsson, H. 2015. Data assimilation in forestry, first practical results using ALS data. SilviLaser 2015, La Grand Motte, France, September 28-30, 2015.
Olsson, H., Granström, A-H., Tyboni, M. and Nilsson, M. 2015. Photo plot interpretation of a major forest fire in Sweden. EARSeL SIG Forestry meeting Cyprus.
Olsson, H. 2015. Forestry Remote Sensing in Sweden. 35th EARSeL Symposium, Stockholm, June 15-18.
Persson, H.J., Soja M.J., Ulander, L.M.H. and Fransson, J.E.S. 2015. Detection of thinning and clear-cuts using TanDEM-X data. In Proceedings of IGARSS 2015 Symposium, Remote Sensing for a Dynamic Earth, Milan, Italy, 26-31 July, 2015. Oral presentation.
Persson, H.J. and Fransson, J.E.S. 2015. Analysis of tree height growth with TanDEM-X data. In Proceedings of 35th EARSeL 2015 Symposium, Stockholm, Sweden, 15-19 June, 2015. Oral presentation.
Soja, M.J., Persson, H. and Ulander L.M.H. 2015. Detection of forest change and robust estimation of forest height from two-level model inversion of multi-temporal, single-pass insar data. IGARSS 2015, Remote Sensing: Understanding the Earth for a Safer World, Milan, Italy, July 26-31, 2015.
Wallerman, J., Nyström, K., Bohlin, J., Persson, H.J., Soja, M.J. and Fransson, J.E.S. 2015. Estimating forest age and site productivity using time series of 3D remote sensing data. Geoscience and Remote Sensing Symposium (IGARSS), 2015.
Lämås, T., Roberge, J-M., Felton, A., Gustafsson, L., Jonzén J., Lundmark, T., Nordin, A., Olsson H., Ranius, T. and Sandström, E. 2015. Generell naturhänsyn och frivilliga avsättningar - Mängden död ved och grova träd ökar i framtidens skogslandskap. Fakta Skog no. 10, SLU.
Persson, H., Soja, M., Olsson, H. och Fransson, J. 2015. Satellitbaserade 3D-data till hjälp för skogliga skattningar. Fakta Skog no. 1, SLU.
Olsson, H. 2015. Försvann fotogrammetrin från akademin? Nyhetsbrev november 2015, avdelningen för Geodesi och satellitpositionering, KTH.
Reese, H. and Högström, M. 2015. GET: a web-based service for downloading free geodata for Swedish universities. EuroSDR Annual Report 2014.
Blombäck, Johanna, 2015. Uppdatering av Södras skogsbruksplaner med hjälp av stereomatchning av flygbilder i kombination med den nya nationella höjdmodellen och Riksskogstaxeringens provytor. Supervisor: Jörgen Wallerman, SLU, Jonas Bohlin, SLU, Heather Reese, SLU and Mats Johansson, Södra Skog.
Olofsson, Linnéa, 2015. Automatisk metod för att identifiering av stormskador med hjälp av kronhöjdsmodeller. Supervisor: Jonas Bohlin, SLU, Mattias Nyström, SLU, Johan Viklund, SCA Skog.
Singhania, Monica, 2015. Forest estimates derived from airborne laser scanning data in southern Sweden : a comparison of regional and local model calibration. Supervisor: Mats Nilsson, SLU and Jörgen Wallerman, SLU.
Söderberg, Jon, 2015. A method for using harvester data in airborne laser prediction of forest variables in mature coniferous stands. Supervisor: Jörgen Wallerman, SLU, Jonas Bohlin, SLU, Anders Almäng, Sveaskog and Johan J. Möller, Skogforsk.
Nyström, Mattias (2014). Mapping and monitoring of vegetation using airborne laser scanning. Diss. (sammanfattning/summary) Umeå : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2014:9
Persson, Henrik (2014). Estimation of forest parameters using 3D satellite data. Diss. (sammanfattning/summary) Umeå : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2014:84
Karlson, M., Reese, H. and Ostwald, M. 2014. Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis. Sensors, 14(12), 22643-22669.
Lindberg, E., Eysn, L., Hollaus, M., Holmgren,J. and Pfeifer, N. 2014. Delineation of TreeCrowns and Tree Species Classification FromFull-Waveform Airborne Laser Scanning DataUsing 3-D Ellipsoidal Clustering. Ieee JournalOf Selected Topics In Applied Earth ObservationsAnd Remote Sensing, vol. 7, no. 7, pp.3174-3181.
Nyström, M., Holmgren, J., Fransson J.E.S., Olsson, H. 2014. Detection of windthrown trees using airborne laser scanning. International Journal of Applied Earth Observation and Geoinformation, vol. 30, 21-29.
Olofsson, K. & Holmgren, J., 2014. Forest stand delineation from lidar point-clouds using local maxima of the crown height model and region merging of the corresponding Voronoi cells. Remote Sensing Letters, 5:3, 268-276.
Olofsson, K., Holmgren, J. and Olsson H. 2014. Tree Stem and Height Measurements using Terrestrial Laser Scanning and the RANSAC Algorithm. Remote Sens. 6(5), 4323-4344.
Pantze, A., Santoro, M. and Fransson, J.E.S. 2014. Change detection of boreal forest using bi-temporal ALOS PALSAR backscatter data. Remote Sensing of Environment, vol. 155, 120-128.
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Krantz, Anders, 2009. Mapping of clear-cuts in Swedish forest using satellite images acquired by the radar sensor ALOS PALSAR. Supervisor: Johan Fransson
Larsson, Henrik 2009. Flygburen laserskanning kopplat till skördarmätning för datainsamling till operativ planering. Supervisor: Johan Holmgren
Mukesh, Kumar, 2009. Geospatial monitoring and evaluation of UNESCO world heritage forest areas in the Tropics . Supervisor: Mikael Egberth
Wiklund, Olle, 2009. Gallringsinventering från helikopter utrustad med profilerande laser och kamera för låghöjdsfotografering. Supervisor: Mats Nilsson