Publications

A selection of the research group's publications. For publications prior to 2015, please see these pages on Forestinventory.no

Publications

2018

  • Z. Asrat, H. Taddese, H. Ørka, T. Gobakken, I. Burud, and E. Næsset, “Estimation of forest area and canopy cover based on visual interpretation of satellite images in ethiopia,” Land, vol. 7, iss. 3, p. 92, 2018.
    [Download PDF]
  • [DOI] C. Babcock, A. O. Finley, H. Andersen, R. Pattison, B. D. Cook, D. C. Morton, M. Alonzo, R. Nelson, T. Gregoire, L. Ene, T. Gobakken, and E. Næsset, “Geostatistical estimation of forest biomass in interior alaska combining landsat-derived tree cover, sampled airborne lidar and field observations,” Remote sensing of environment, vol. 212, pp. 212-230, 2018.
    [Download PDF]
  • [DOI] O. M. Bollandsås, L. T. Ene, T. Gobakken, and E. Næsset, “Estimation of biomass change in montane forests in norway along a 1200 km latitudinal gradient using airborne laser scanning: a comparison of direct and indirect prediction of change under a model-based inferential approach,” Scandinavian journal of forest research, vol. 33, iss. 2, pp. 155-165, 2018.
    [Download PDF]
  • M. Dalponte, L. Ene, T. Gobakken, E. Næsset, and D. Gianelle, “Predicting selected forest stand characteristics with multispectral als data,” Remote sensing, vol. 10, iss. 4, p. 586, 2018.
    [Download PDF]
  • [DOI] M. Dalponte, L. Frizzera, H. O. Ørka, T. Gobakken, E. Næsset, and D. Gianelle, “Predicting stem diameters and aboveground biomass of individual trees using remote sensing data,” Ecological indicators, vol. 85, pp. 367-376, 2018.
    [Download PDF]
  • [DOI] L. T. Ene, T. Gobakken, H. Andersen, E. Næsset, B. D. Cook, D. C. Morton, C. Babcock, and R. Nelson, “Large-area hybrid estimation of aboveground biomass in interior alaska using airborne laser scanning data,” Remote sensing of environment, vol. 204, iss. Supplement C, pp. 741-755, 2018.
    [Download PDF]
  • [DOI] C. Fischer, O. A. Høibø, G. I. Vestøl, M. Hauglin, E. H. Hansen, and T. Gobakken, “Predicting dynamic modulus of elasticity of norway spruce structural timber by forest inventory, airborne laser scanning and harvester-derived data,” Scandinavian journal of forest research, pp. 1-10, 2018.
    [Download PDF]
  • [DOI] F. Giannetti, G. Chirici, T. Gobakken, E. Næsset, D. Travaglini, and S. Puliti, “A new approach with dtm-independent metrics for forest growing stock prediction using uav photogrammetric data,” Remote sensing of environment, vol. 213, pp. 195-205, 2018.
    [Download PDF]
  • [DOI] M. Hauglin, E. Hansen, E. Sørngård, E. Næsset, and T. Gobakken, “Utilizing accurately positioned harvester data: modelling forest volume with airborne laser scanning,” Canadian journal of forest research, pp. 1-10, 2018.
    [Download PDF]
  • [DOI] A. Kangas, R. Astrup, J. Breidenbach, J. Fridman, T. Gobakken, K. T. Korhonen, M. Maltamo, M. Nilsson, T. Nord-Larsen, E. Næsset, and H. Olsson, “Remote sensing and forest inventories in nordic countries – roadmap for the future,” Scandinavian journal of forest research, vol. 33, iss. 4, pp. 397-412, 2018.
    [Download PDF]
  • [DOI] A. Kangas, T. Gobakken, S. Puliti, M. Hauglin, and E. Naesset, “Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making,” Silva fennica, vol. 52, iss. 1, p. article id 9923, 2018.
    [Download PDF]
  • [DOI] R. E. McRoberts, E. Næsset, and T. Gobakken, “Comparing the stock-change and gain–loss approaches for estimating forest carbon emissions for the aboveground biomass pool,” Canadian journal of forest research, vol. 48, iss. 12, pp. 1535-1542, 2018.
    [Download PDF]
  • [DOI] R. E. McRoberts, E. Næsset, T. Gobakken, G. Chirici, S. Condés, Z. Hou, S. Saarela, Q. Chen, G. Ståhl, and B. F. Walters, “Assessing components of the model-based mean square error estimator for remote sensing assisted forest applications,” Canadian journal of forest research, vol. 48, iss. 6, pp. 642-649, 2018.
    [Download PDF]
  • [DOI] R. E. McRoberts, S. V. Stehman, G. C. Liknes, E. Næsset, C. Sannier, and B. F. Walters, “The effects of imperfect reference data on remote sensing-assisted estimators of land cover class proportions,” Isprs journal of photogrammetry and remote sensing, vol. 142, pp. 292-300, 2018.
    [Download PDF]
  • [DOI] L. Noordermeer, O. M. Bollandsås, T. Gobakken, and E. Næsset, “Direct and indirect site index determination for norway spruce and scots pine using bitemporal airborne laser scanner data,” Forest ecology and management, vol. 428, pp. 104-114, 2018. [Download PDF]
  • I. Oveland, M. Hauglin, F. Giannetti, N. Schipper Kjørsvik, and T. Gobakken, “Comparing three different ground based laser scanning methods for tree stem detection,” Remote sensing, vol. 10, iss. 4, p. 538, 2018.
    [Download PDF]
  • [DOI] S. Puliti, S. Saarela, T. Gobakken, G. Ståhl, and E. Næsset, “Combining uav and sentinel-2 auxiliary data for forest growing stock volume estimation through hierarchical model-based inference,” Remote sensing of environment, vol. 204, pp. 485-497, 2018. [Download PDF]
  • S. Saarela, S. Holm, S. P. Healey, H. Andersen, H. Petersson, W. Prentius, P. L. Patterson, E. Næsset, T. G. Gregoire, and G. Ståhl, “Generalized hierarchical model-based estimation for aboveground biomass assessment using gedi and landsat data,” Remote sensing, vol. 10, iss. 11, p. 1832, 2018. [Download PDF]
  • [DOI] Ø. D. Trier, A. Salberg, J. Haarpaintner, D. Aarsten, T. Gobakken, and E. Næsset, “Multi-sensor forest vegetation height mapping methods for tanzania,” European journal of remote sensing, vol. 51, iss. 1, pp. 587-606, 2018.
    [Download PDF]
  • [DOI] Ø. D. Trier, A. Salberg, M. Kermit, Ø. Rudjord, T. Gobakken, E. Næsset, and D. Aarsten, “Tree species classification in norway from airborne hyperspectral and airborne laser scanning data,” European journal of remote sensing, vol. 51, iss. 1, pp. 336-351, 2018.
    [Download PDF]
  • [DOI] H. O. Ørka, O. M. Bollandsås, E. H. Hansen, E. Næsset, and T. Gobakken, “Effects of terrain slope and aspect on the error of als-based predictions of forest attributes,” Forestry: an international journal of forest research, vol. 91, iss. 2, pp. 225-237, 2018.
    [Download PDF]

2017

  • [DOI] M. Egberth, G. Nyberg, E. Næsset, T. Gobakken, E. Mauya, R. Malimbwi, J. Katani, N. Chamuya, G. Bulenga, and H. Olsson, «Combining airborne laser scanning and landsat data for statistical modeling of soil carbon and tree biomass in tanzanian miombo woodlands,» Carbon balance and management, vol. 12, iss. 1, p. 8, 2017. 
    [Download PDF]
  • [DOI] L. T. Ene, E. Næsset, T. Gobakken, O. M. Bollandsås, E. W. Mauya, and E. Zahabu, «Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data,» Remote sensing of environment, vol. 188, pp. 106-117, 2017. 
    [Download PDF]
  • E. Hansen, L. Ene, T. Gobakken, H. Ørka, O. Bollandsås, and E. Næsset, «Countering negative effects of terrain slope on airborne laser scanner data using procrustean transformation and histogram matching,» Forests, vol. 8, iss. 10, p. 401, 2017. 
    [Download PDF]
  • E. Hansen, L. Ene, E. Mauya, Z. Patocka, T. Mikita, T. Gobakken, and E. Næsset, «Comparing empirical and semi-empirical approaches to forest biomass modelling in different biomes using airborne laser scanner data,» Forests, vol. 8, iss. 5, p. 170, 2017. 
    [Download PDF]
  • [DOI] M. Hauglin, E. H. Hansen, E. Næsset, B. E. Busterud, J. G. O. Gjevestad, and T. Gobakken, «Accurate single-tree positions from a harvester: a test of two global satellite-based positioning systems,» Scandinavian journal of forest research, vol. 32, iss. 8, pp. 774-781, 2017. 
    [Download PDF]
  • D. Kachamba, H. Ørka, E. Næsset, T. Eid, and T. Gobakken, «Influence of plot size on efficiency of biomass estimates in inventories of dry tropical forests assisted by photogrammetric data from an unmanned aircraft system,» Remote sensing, vol. 9, iss. 6, p. 610, 2017. 
    [Download PDF]
  • [DOI] K. Kandare, H. O. Ørka, M. Dalponte, E. Næsset, and T. Gobakken, «Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data,» International journal of applied earth observation and geoinformation, vol. 60, pp. 72-82, 2017. 
    [Download PDF]
  • [DOI] K. Lone, A. Mysterud, T. Gobakken, J. Odden, J. Linnell, and L. E. Loe, «Temporal variation in habitat selection breaks the catch-22 of spatially contrasting predation risk from multiple predators,» Oikos, vol. 126, iss. 5, pp. 624-632, 2017. 
    [Download PDF]
  • [DOI] R. E. McRoberts, Q. Chen, G. M. Domke, E. Næsset, T. Gobakken, G. Chirici, and M. Mura, «Optimizing nearest neighbour configurations for airborne laser scanning-assisted estimation of forest volume and biomass,» Forestry: an international journal of forest research, vol. 90, iss. 1, pp. 99-111, 2017. 
    [Download PDF]
  • [DOI] P. Moser, A. C. Vibrans, R. E. McRoberts, E. Næsset, T. Gobakken, G. Chirici, M. Mura, and M. Marchetti, «Methods for variable selection in lidar-assisted forest inventories,» Forestry: an international journal of forest research, vol. 90, iss. 1, pp. 112-124, 2017. 
    [Download PDF]
  • [DOI] W. A. Mugasha, O. M. Bollandsås, T. Gobakken, E. Zahabu, J. Z. Katani, and T. Eid, «Decision-support tool for management of miombo woodlands: a matrix model approach,» Southern forests: a journal of forest science, vol. 79, iss. 1, pp. 65-77, 2017. 
    [Download PDF]
  • [DOI] W. A. Mugasha, T. Eid, O. M. Bollandsås, and L. Mbwambo, «Modelling diameter growth, mortality and recruitment of trees in miombo woodlands of tanzania,» Southern forests: a journal of forest science, pp. 1-14, 2017. 
    [Download PDF]
  • I. Oveland, M. Hauglin, T. Gobakken, E. Næsset, and I. Maalen-Johansen, «Automatic estimation of tree position and stem diameter using a moving terrestrial laser scanner,» Remote sensing, vol. 9, iss. 4, p. 350, 2017. 
    [Download PDF]
  • [DOI] S. Puliti, L. T. Ene, T. Gobakken, and E. Næsset, «Use of partial-coverage uav data in sampling for large scale forest inventories,» Remote sensing of environment, vol. 194, pp. 115-126, 2017. 
    [Download PDF]
  • S. Puliti, S. Solberg, E. Næsset, T. Gobakken, E. Zahabu, E. Mauya, and R. Malimbwi, «Modelling above ground biomass in tanzanian miombo woodlands using tandem-x worlddem and field data,» Remote sensing, vol. 9, iss. 10, p. 984, 2017. 
    [Download PDF]
  • [DOI] S. Saarela, H. Andersen, A. Grafström, S. Schnell, T. Gobakken, E. Næsset, R. F. Nelson, R. E. McRoberts, T. G. Gregoire, and G. Ståhl, «A new prediction-based variance estimator for two-stage model-assisted surveys of forest resources,» Remote sensing of environment, vol. 192, pp. 1-11, 2017. 
    [Download PDF]
  • [DOI] S. Solberg, E. H. Hansen, T. Gobakken, E. Næssset, and E. Zahabu, «Biomass and insar height relationship in a dense tropical forest,» Remote sensing of environment, vol. 192, pp. 166-175, 2017. 
     [Download PDF]
  • [DOI] V. F. Strïmbu, L. T. Ene, T. Gobakken, T. G. Gregoire, R. Astrup, and E. Næsset, «Post-stratified change estimation for large-area forest biomass using repeated als strip sampling,» Canadian journal of forest research, vol. 47, iss. 6, pp. 839-847, 2017. 
    [Download PDF]

2016

  • [DOI] L. T. Ene, E. Næsset, and T. Gobakken, «Simulation-based assessment of sampling strategies for large-area biomass estimation using wall-to-wall and partial coverage airborne laser scanning surveys,» Remote sensing of environment, vol. 176, pp. 328-340, 2016. 
    [Download PDF]
  • [DOI] L. T. Ene, E. Næsset, T. Gobakken, E. W. Mauya, O. M. Bollandsås, T. G. Gregoire, G. Ståhl, and E. Zahabu, «Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data,» Remote sensing of environment, vol. 186, pp. 626-636, 2016. 
    [Download PDF]
  • [DOI] B. Gizachew, S. Solberg, E. Næsset, T. Gobakken, O. M. Bollandsås, J. Breidenbach, E. Zahabu, and E. W. Mauya, «Mapping and estimating the total living biomass and carbon in low-biomass woodlands using landsat 8 cdr data,» Carbon balance and management, vol. 11, iss. 1, p. 13, 2016. [Download PDF]
  • [DOI] T. G. Gregoire, E. Næsset, R. E. McRoberts, G. Ståhl, H. Andersen, T. Gobakken, L. Ene, and R. Nelson, «Statistical rigor in lidar-assisted estimation of aboveground forest biomass,» Remote sensing of environment, vol. 173, pp. 98-108, 2016. [Download PDF]
  • [DOI] R. Halvorsen, S. Mazzoni, J. W. Dirksen, E. Næsset, T. Gobakken, and M. Ohlson, «How important are choice of model selection method and spatial autocorrelation of presence data for distribution modelling by maxent?,» Ecological modelling, vol. 328, pp. 108-118, 2016. [Download PDF]
  • M. Hauglin and E. Næsset, «Detection and segmentation of small trees in the forest-tundra ecotone using airborne laser scanning,» Remote sensing, vol. 8, iss. 5, p. 407, 2016. [Download PDF]
  • [DOI] M. Hauglin and H. O. Ørka, «Discriminating between native norway spruce and invasive sitka spruce—a comparison of multitemporal landsat 8 imagery, aerial images and airborne laser scanner data,» Remote sensing, vol. 8, iss. 5, p. 363, 2016. [Download PDF]
  • D. Kachamba, T. Eid, and T. Gobakken, «Above- and belowground biomass models for trees in the miombo woodlands of malawi,» Forests, vol. 7, iss. 2, p. 38, 2016. [Download PDF]
  • D. Kachamba, H. O. Ørka, T. Gobakken, T. Eid, and W. Mwase, «Biomass estimation using 3d data from unmanned aerial vehicle imagery in a tropical woodland,» Remote sensing, vol. 8, iss. 11, p. 968, 2016. [Download PDF]
  • [DOI] A. Kangas, M. Myllymäki, T. Gobakken, and E. Næsset, «Model-assisted forest inventory with parametric, semiparametric, and nonparametric models,» Canadian journal of forest research, vol. 46, iss. 6, pp. 855-868, 2016. [Download PDF]
  • [DOI] L. Korhonen, C. Salas, T. Østgård, V. Lien, T. Gobakken, and E. Næsset, «Predicting the occurrence of large-diameter trees using airborne laser scanning,» Canadian journal of forest research, pp. 461-469, 2016. [Download PDF]
  • [DOI] S. Magnussen, D. Mandallaz, A. Lanz, C. Ginzler, E. Næsset, and T. Gobakken, «Scale effects in survey estimates of proportions and quantiles of per unit area attributes,» Forest ecology and management, vol. 364, pp. 122-129, 2016. [Download PDF]
  • [DOI] S. Magnussen, E. Næsset, G. Kändler, P. Adler, J. P. Renaud, and T. Gobakken, «A functional regression model for inventories supported by aerial laser scanner data or photogrammetric point clouds,» Remote sensing of environment, vol. 184, pp. 496-505, 2016. [Download PDF]
  • [DOI] M. Maltamo, O. M. Bollandsås, T. Gobakken, and E. Næsset, «Large-scale prediction of aboveground biomass in heterogeneous mountain forests by means of airborne laser scanning,» Canadian journal of forest research, vol. 46, iss. 9, pp. 1138-1144, 2016. [Download PDF]
  • [DOI] R. E. McRoberts, G. M. Domke, Q. Chen, E. Næsset, and T. Gobakken, «Using genetic algorithms to optimize k-nearest neighbors configurations for use with airborne laser scanning data,» Remote sensing of environment, vol. 184, pp. 387-395, 2016. [Download PDF]
  • [DOI] R. E. McRoberts, E. Næsset, and T. Gobakken, «The effects of temporal differences between map and ground data on map-assisted estimates of forest area and biomass,» Annals of forest science, vol. 73, iss. 4, pp. 839-847, 2016. [Download PDF]
  • [DOI] R. E. McRoberts, A. C. Vibrans, C. Sannier, E. Næsset, M. C. Hansen, B. F. Walters, and D. V. Lingner, «Methods for evaluating the utilities of local and global maps for increasing the precision of estimates of subtropical forest area,» Canadian journal of forest research, vol. 46, iss. 7, pp. 924-932, 2016. [Download PDF]
  • [DOI] M. Myllymäki, T. Gobakken, E. Næsset, and A. Kangas, «The efficiency of post-stratification compared to model-assisted estimation,» Canadian journal of forest research, 2016. [Download PDF]
  • [DOI] M. Myllymäki, T. Gobakken, E. Næsset, and A. Kangas, «The efficiency of poststratification compared with model-assisted estimation,» Canadian journal of forest research, vol. 47, iss. 4, pp. 515-526, 2016. [Download PDF]
  • E. Næsset, «Discrimination between ground vegetation and small pioneer trees in the boreal-alpine ecotone using intensity metrics derived from airborne laser scanner data,» Remote sensing, vol. 8, iss. 7, p. 548, 2016. [Download PDF]
  • [DOI] E. Næsset, H. O. Ørka, S. Solberg, O. M. Bollandsås, E. H. Hansen, E. Mauya, E. Zahabu, R. Malimbwi, N. Chamuya, H. Olsson, and T. Gobakken, «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, 2016. [Download PDF]
  • [DOI] S. Puliti, T. Gobakken, H. O. Ørka, and E. Næsset, «Assessing 3d point clouds from aerial photographs for species-specific forest inventories,» Scandinavian journal of forest research, pp. 1-12, 2016. [Download PDF]
  • [DOI] A. H. Ringvall, G. Ståhl, L. T. Ene, E. Næsset, T. Gobakken, and T. G. Gregoire, «A poststratified ratio estimator for model-assisted biomass estimation in sample-based airborne laser scanning surveys,» Canadian journal of forest research, vol. 46, iss. 11, pp. 1386-1395, 2016. [Download PDF]
  • [DOI] S. Saarela, S. Holm, A. Grafström, S. Schnell, E. Næsset, T. G. Gregoire, R. F. Nelson, and G. Ståhl, «Hierarchical model-based inference for forest inventory utilizing three sources of information,» Annals of forest science, pp. 1-16, 2016. [Download PDF]
  • [DOI] G. Ståhl, S. Saarela, S. Schnell, S. Holm, J. Breidenbach, S. P. Healey, P. L. Patterson, S. Magnussen, E. Næsset, R. E. McRoberts, and T. G. Gregoire, «Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation,» Forest ecosystems, vol. 3, iss. 1, pp. 1-11, 2016. [Download PDF]
  • [DOI] V. F. Strîmbu, L. T. Ene, and E. Næsset, «Spatially consistent imputations of forest data under a semivariogram model,» Canadian journal of forest research, vol. 46, iss. 9, pp. 1145-1156, 2016. [Download PDF]
  • [DOI] A. Sverdrup-Thygeson, H. O. Ørka, T. Gobakken, and E. Næsset, «Can airborne laser scanning assist in mapping and monitoring natural forests?,» Forest ecology and management, vol. 369, pp. 116-125, 2016. [Download PDF]
  • [DOI] H. O. Ørka, T. Gobakken, and E. Næsset, «Predicting attributes of regeneration forests using airborne laser scanning,» Canadian journal of remote sensing, vol. 42, iss. 5, pp. 541-553, 2016. [Download PDF]

2015

  • [DOI] P. Borges, E. Bergseng, T. Eid, and T. Gobakken, «Impact of maximum opening area constraints on profitability and biomass availability in forestry – a large, real world case,» Silva fennica, vol. 49, iss. 5, 2015. [Download PDF]
  • [DOI] P. Borges, I. Martins, E. Bergseng, T. Eid, and T. Gobakken, «Effects of site productivity on forest harvest scheduling subject to green-up and maximum area restrictions,» Scandinavian journal of forest research, pp. 1-10, 2015. [Download PDF]
  • [DOI] M. Dalponte, L. T. Ene, M. Marconcini, T. Gobakken, and E. Næsset, «Semi-supervised svm for individual tree crown species classification,» Isprs journal of photogrammetry and remote sensing, vol. 110, pp. 77-87, 2015. [Download PDF]
  • [DOI] T. G. Gregoire, A. H. Ringvall, G. Ståhl, and E. Næsset, «Conditioning post-stratified inference following two-stage, equal-probability sampling,» Environmental and ecological statistics, vol. 23, iss. 1, pp. 141-154, 2015. [Download PDF]
  • E. Hansen, T. Gobakken, O. Bollandsås, E. Zahabu, and E. Næsset, «Modeling aboveground biomass in dense tropical submontane rainforest using airborne laser scanner data,» Remote sensing, vol. 7, iss. 1, pp. 788-807, 2015. [Download PDF]
  • E. Hansen, T. Gobakken, and E. Næsset, «Effects of pulse density on digital terrain models and canopy metrics using airborne laser scanning in a tropical rainforest,» Remote sensing, vol. 7, iss. 7, pp. 8453-8468, 2015. [Download PDF]
  • E. Hansen, T. Gobakken, S. Solberg, A. Kangas, L. Ene, E. Mauya, and E. Næsset, «Relative efficiency of als and insar for biomass estimation in a tanzanian rainforest,» Remote sensing, vol. 7, iss. 8, pp. 9865-9885, 2015. [Download PDF]
  • [DOI] T. Kristensen, E. Næsset, M. Ohlson, P. V. Bolstad, and R. Kolka, «Mapping above- and below-ground carbon pools in boreal forests: the case for airborne lidar,» Plos one, vol. 10, iss. 10, p. e0138450, 2015. [Download PDF]
  • [DOI] S. Magnussen, E. Næsset, and T. Gobakken, «Lidar-supported estimation of change in forest biomass with time-invariant regression models,» Canadian journal of forest research, vol. 45, iss. 11, pp. 1514-1523, 2015. [Download PDF]
  • [DOI] Maltamo, Ørka, Bollandsås, Gobakken, and Næsset, «Using pre-classification to improve the accuracy of species-specific forest attribute estimates from airborne laser scanner data and aerial images,» Scandinavian journal of forest research, vol. 30, iss. 4, pp. 336-345, 2015. [Download PDF]
  • E. Mauya, L. Ene, O. Bollandsas, T. Gobakken, E. Naesset, R. Malimbwi, and E. Zahabu, «Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of tanzania,» Carbon balance and management, vol. 10, iss. 1, p. 28, 2015. [Download PDF]
  • E. Mauya, E. Hansen, T. Gobakken, O. Bollandsas, R. Malimbwi, and E. Naesset, «Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of tanzania,» Carbon balance and management, vol. 10, iss. 1, p. 10, 2015. [Download PDF]
  • [DOI] R. E. McRoberts, E. Næsset, and T. Gobakken, «Optimizing the k-nearest neighbors technique for estimating forest aboveground biomass using airborne laser scanning data,» Remote sensing of environment, vol. 163, pp. 13-22, 2015. [Download PDF]
  • [DOI] R. E. McRoberts, E. Næsset, T. Gobakken, and O. M. Bollandsås, «Indirect and direct estimation of forest biomass change using forest inventory and airborne laser scanning data,» Remote sensing of environment, vol. 164, pp. 36-42, 2015. [Download PDF]
  • E. Næsset, «Vertical height errors in digital terrain models derived from airborne laser scanner data in a boreal-alpine ecotone in norway,» Remote sensing, vol. 7, iss. 4, p. 4702, 2015. [Download PDF]
  • [DOI] E. Næsset, O. M. Bollandsås, T. Gobakken, S. Solberg, and R. E. McRoberts, «The effects of field plot size on model-assisted estimation of aboveground biomass change using multitemporal interferometric sar and airborne laser scanning data,» Remote sensing of environment, vol. 168, pp. 252-264, 2015. [Download PDF]
  • E. Næsset and T. Gobakken, «Ressursregistrering og skogbruksplanlegging – en renessanse for flybildene?,» Norsk skogbruk, vol. 2, pp. 34-37, 2015. 
  • [DOI] M. A. Njana, O. M. Bollandsås, T. Eid, E. Zahabu, and R. E. Malimbwi, «Above- and belowground tree biomass models for three mangrove species in tanzania: a nonlinear mixed effects modelling approach,» Annals of forest science, 2015. [Download PDF]
  • [DOI] S. Puliti, H. Ørka, T. Gobakken, and E. Næsset, «Inventory of small forest areas using an unmanned aerial system,» Remote sensing, vol. 7, iss. 8, pp. 9632-9654, 2015. [Download PDF]
  • S. Solberg, B. Gizachew, E. Naesset, T. Gobakken, O. Bollandsas, E. Mauya, H. Olsson, R. Malimbwi, and E. Zahabu, «Monitoring forest carbon in a tanzanian woodland using interferometric sar: a novel methodology for redd+,» Carbon balance and management, vol. 10, iss. 1, p. 14, 2015. [Download PDF]
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Published 30. September 2018 - 18:15 - Updated 7. November 2019 - 15:52