Endre Hofstad Hansen

• Hansen, Endre Hofstad; Wold, Julius; Dalponte, Michele; Gobakken, Terje; Noordermeer, Lennart & Ørka, Hans Ole (2023). Estimation of the occurrence, severity, and volume of heartwood rot using airborne laser scanning and optical satellite data. European Journal of Remote Sensing. ISSN 2279-7254. 56(1). doi: 10.1080/22797254.2023.2229501.
• Hansen, Endre Hofstad; Rahlf, Johannes; Astrup, Rasmus Andreas & Gobakken, Terje (2023). Taper, volume, and bark thickness models for spruce, pine, and birch in Norway. Scandinavian Journal of Forest Research. ISSN 0282-7581. 38(6), p. 413–428. doi: 10.1080/02827581.2023.2243821. Show summary

  Taper models, which describe the shape of tree stems, are central to estimating stem volume. Literature provides both taper- and volume models for the three main species in Norway, Norway spruce, Scots pine, and birch. These models, however, were mainly developed using approaches established over 50 years ago, and without consistency between taper and volume. We tested eleven equations for taper and six equations for bark thickness. The models were fitted and evaluated using a large dataset covering all forested regions in Norway. The selected models were converted into volume functions using numerical integration, providing both with- and without-bark volumes and compared to the volume functions in operational use. Taper models resulted in root mean squared error (RMSE) of 7.2, 7.9, and 9.0 mm for spruce, pine, and birch respectively. Bark thickness models resulted in RMSE of 2.5, 6.1, and 4.1 mm, for spruce, pine, and birch respectively. Validation of volume models with bark resulted in RMSE of 12.7%, 13.0%, and 19.7% for spruce, pine, and birch respectively. Additional variables, tree age, site index, elevation, and live crown proportion, were tested without resulting in any strong increase in predictive power.

• Ørka, Hans Ole; Hansen, Endre Hofstad; Dalponte, Michele; Gobakken, Terje & Næsset, Erik (2021). Large-area inventory of species composition using airborne laser scanning and hyperspectral data. Silva Fennica. ISSN 0037-5330. 55(4). doi: 10.14214/sf.10244.
• Fischer, Carolin; Høibø, Olav Albert; Vestøl, Geir Isak; Hauglin, Marius; Hansen, Endre Hofstad & Gobakken, Terje (2018). 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. ISSN 0282-7581. 33(6), p. 603–612. doi: 10.1080/02827581.2018.1427790.
• Hauglin, Marius; Hansen, Endre Hofstad; Sørngård, Erik; Næsset, Erik & Gobakken, Terje (2018). Utilizing accurately positioned harvester data: modelling forest volume with airborne laser scanning. Canadian Journal of Forest Research. ISSN 0045-5067. 48(8), p. 913–922. doi: 10.1139/cjfr-2017-0467.
• Ørka, Hans Ole; Bollandsås, Ole Martin; Hansen, Endre Hofstad; Næsset, Erik & Gobakken, Terje (2018). Effects of terrain slope and aspect on the error of ALS-based predictions of forest attributes. Forestry (London). ISSN 0015-752X. 91(2), p. 225–237. doi: 10.1093/forestry/cpx058.
• Hansen, Endre Hofstad; Ene, Liviu Theodor; Gobakken, Terje; Ørka, Hans Ole; Bollandsås, Ole Martin & Næsset, Erik (2017). Countering negative effects of terrain slope on airborne laser scanner data using procrustean transformation and histogram matching. Forests. ISSN 1999-4907. 8(10). doi: 10.3390/f8100401.
• Hauglin, Marius; Hansen, Endre Hofstad; Næsset, Erik; Busterud, Bjørn Even; Gjevestad, Jon Glenn Omholt & Gobakken, Terje (2017). Accurate single-tree positions from a harvester: a test of two global satellite-based positioning systems. Scandinavian Journal of Forest Research. ISSN 0282-7581. 32(8), p. 774–781. doi: 10.1080/02827581.2017.1296967.
• Hansen, Endre Hofstad; Ene, Liviu Theodor; Mauya, Ernest William; Patocka, Zdenek; Mikita, Tomas & Gobakken, Terje [Show all 7 contributors for this article] (2017). Comparing empirical and semi-empirical approaches to forest biomass modelling in different biomes using airborne laser scanner data. Forests. ISSN 1999-4907. 8(5). doi: 10.3390/f8050170.
• Solberg, Svein; Hansen, Endre Hofstad; Gobakken, Terje; Næsset, Erik & Zahabu, Eliakimu (2017). Biomass and InSAR height relationship in a dense tropical forest. Remote Sensing of Environment. ISSN 0034-4257. 192, p. 166–175. doi: 10.1016/j.rse.2017.02.010. Show summary

  In the present study we applied X-band interferometric SAR (InSAR) data from the TanDEM-X mission, and investigated the relationship between InSAR height above ground and above-ground biomass (AGB) in a forest with very high biomass. We carried out this study in the East Usambara Mountains in Tanzania, with AGB ranging up to N1000 t/ha. Field inventory provided AGB data for 153 plots of 900 m2 in size. An airborne laser scanning (ALS) provided a DTM as well as AGB predictions for larger 8100 m2 cells over the entire study area. Three TanDEM-X acquisitions provided single-pass InSAR data, from which we generated a Digital Surface Models (DSM) and InSAR height by subtracting the ALS DTM. The results showed that proportionality may represent the relationship where AGB increased with 18.4 t/ha per m increase in InSAR height. The accuracy was low with RMSE = 203 t/ha (44%), which was partly attributable to small field plots and partly to a limited sensitivity of InSAR height to variations in basal area and stand density. An identical proportionality model, with less residual noise, was achieved by replacing the small field plots with the 8100 m2 cells having AGB predictions from ALS data.

• Næsset, Erik; Ørka, Hans Ole; Solberg, Svein; Bollandsås, Ole Martin; Hansen, Endre Hofstad & Mauya, Ernest William [Show all 11 contributors for this article] (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. ISSN 0034-4257. 175, p. 282–300. doi: 10.1016/j.rse.2016.01.006.
• Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Zahabu, Eliakimu & Næsset, Erik (2015). Modeling aboveground biomass in dense tropical submontane rainforest using airborne laser scanner data. Remote Sensing. ISSN 2072-4292. 7, p. 788–807. doi: 10.3390/rs70100788. Full text in Research Archive
• Hansen, Endre Hofstad; Gobakken, Terje & Næsset, Erik (2015). Effects of pulse density on digital terrain models and canopy metrics using airborne laser scanning in a tropical rainforest. Remote Sensing. ISSN 2072-4292. 7(7), p. 8453–8468. doi: 10.3390/rs70708453. Full text in Research Archive
• Hansen, Endre Hofstad; Gobakken, Terje; Solberg, Svein; Kangas, Annika; Ene, Liviu Theodor & Mauya, Ernest William [Show all 7 contributors for this article] (2015). Relative efficiency of ALS and InSAR for biomass estimation in a Tanzanian rainforest. Remote Sensing. ISSN 2072-4292. 7(8), p. 9865–9885. doi: 10.3390/rs70809865. Full text in Research Archive Show summary

  Forest inventories based on field sample surveys, supported by auxiliary remotely sensed data, have the potential to provide transparent and confident estimates of forest carbon stocks required in climate change mitigation schemes such as the REDD+ mechanism. The field plot size is of importance for the precision of carbon stock estimates, and better information of the relationship between plot size and precision can be useful in designing future inventories. Precision estimates of forest biomass estimates developed from 30 concentric field plots with sizes of 700, 900, …, 1900 m2, sampled in a Tanzanian rainforest, were assessed in a model-based inference framework. Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radio detection and ranging (InSAR) were used as auxiliary information. The findings indicate that larger field plots are relatively more efficient for inventories supported by remotely sensed ALS and InSAR data. A simulation showed that a pure field-based inventory would have to comprise 3.5–6.0 times as many observations for plot sizes of 700–1900 m2 to achieve the same precision as an inventory supported by ALS data.

• Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernerst & Næsset, Erik (2015). 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. ISSN 1750-0680. 10. doi: 10.1186/s13021-015-0021-x. Full text in Research Archive

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• Hansen, Endre Hofstad & Sjølie, Hanne Kathrine (2023). Importance of ownership type on forest management.
• Ørka, Hans Ole; Hansen, Endre Hofstad & Bollandsås, Ole Martin (2016). Lasertakst i Vestlandsterreng.
• Næsset, Erik; Hansen, Endre Hofstad; Mauya, Ernest; Gobakken, Terje & Zahabu, Eliakimu (2015). Technical issues related to improved performance of laser scanning for topographic terrain modelling and biomass estimation. In Næsset, Erik (Eds.), Forest monitoring with airborne laser scanning in Tanzania. Norwegian University of Life Sciences. ISSN 1891-2281. p. 15–21.
• Næsset, Erik; Hansen, Endre Hofstad; Mauya, Ernest; Gobakken, Terje & Zahabu, Eliakimu (2015). Modeling and mapping of forest biomass and tree species diversity. In Næsset, Erik (Eds.), Forest monitoring with airborne laser scanning in Tanzania. Norwegian University of Life Sciences. ISSN 1891-2281. p. 7–14.
• Saarela, Svetlana; Næsset, Erik; Gobakken, Terje; Ørka, Hans Ole; Hansen, Endre Hofstad & Mauya, Ernest William [Show all 8 contributors for this article] (2014). Model-dependent inference for biomass estimation in a LiDAR sample survey in Liwale, Tanzania.
• Næsset, Erik; Gobakken, Terje; Hansen, Endre Hofstad; Mauya, Ernest & Zahabu, Eliakimu (2014). Impact of plot size on precision of lidar-assisted estimation of aboveground biomass in a submontane rain forest in Tanzania.

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