This list contains recent relevant papers and reports authored by researchers at the Norwegian Computing Center.

Journal papers

• Næsset, E., Mc Roberts, R.E., Pekkarinen, A., Saatchi, S., Santoro, M., Trier, Ø.D., Zahabu, E., Gobakken, T., 2020. Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania. International Journal of Applied Earth Observation and Geoinformation 89, 102109.
• Trier, Ø.D., Salberg, A.-B., Haarpaintner, J., Aarsten, D., Gobakken, T., Næsset, E., 2018. Multi-sensor forest vegetation height mapping methods for Tanzania. European Journal of Remote Sensing 51(1), pp 587-606.
• Salberg, A.-B., Jenssen, R, 2012. Land-cover classification of partly missing data using support vector machines. International Journal of Remote Sensing 33 (14), pp. 4471-4481.
• Salberg, A.-B., 2011. Land Cover Classification of Cloud-Contaminated Multitemporal High-Resolution Images. IEEE Transactions on Geoscience and Remote Sensing 49 (1), pp. 377-387.
• Storvik, B., Storvik, G., Fjørtoft, R., 2009. On the Combination of Multisensor Data Using Meta-Gaussian Distributions. IEEE Transactions on Geoscience and Remote Sensing 47 (7), pp. 2372-2379.

Conference papers/presentations

• Salberg, A.-B., Trier, Ø. D., 2012. Temporal analysis of multisensor data for forest change detection using hidden Markov models. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012.
• Zortea, M., Salberg, A.-B., Trier, Ø. D., 2012. Object-based cloud and cloud shadow detection in Landsat images for tropical forest monitoring. 4th International Conference on Geographic Object-Based Image Analysis (GEOBIA), 7-9 May 2012, Rio de Janeiro, Brazil, pp. 326-331. [PDF]
• Trier, Ø.D., Salberg, A.-B., 2011. Time-series analysis of satellite images for forest cover change monitoring in Tanzania. 1st EARSeL Workshop on Operational Remote Sensing in Forest Management, Prague, Czech Republic, 2–3 June, 2011. Presentation, paper.
• Salberg, A.-B., 2011. Retraining maximum likelihood classifiers using a low-rank model. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011, pp. 166-169.
• Salberg, A.-B.; Trier, Ø.D., 2011. Temporal analysis of forest cover using hidden Markov models. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011, pp. 2322-2325.
• Aurdal, L., Huseby, R. B., Vikhamar, D., Eikvil, L., Solberg, A. H. S., Solberg, R., 2005. Classification of multitemporal satellite images using phenological models. In: Third International Workshop on the Analysis of Multitemporal Remote Sensing Images, Biloxi, Mississippi, USA, 16-18 May 2005, pp. 220-224.
• Huseby, R. B., Aurdal, L., Vikhamar, D., Eikvil, L., Solberg, A. H. S., Solberg, R., 2005. Alignment of Growth Seasons from Satellite Data. In: Third International Workshop on the Analysis of Multitemporal Remote Sensing Images, Biloxi, Mississippi, USA, 16-18 May 2005, pp. 213-216.

Internal reports

• Rudjord, Ø., Trier, Ø. D., 2012. Evaluation of FLAASH atmospheric correction. NR Note No. SAMBA/10/12.
• Zortea, M., Trier, Ø. D., Salberg, A.-B., 2012. Cloud and cloud shadow detection on Landsat images for monitoring tropical forests in Tanzania. NR Note No. SAMBA/06/12. 157 pp.
• Trier, Ø. D., 2011. LEDAPS atmospheric correction production line. User guide. NR-Note No. SAMBA/39/11.
• Zortea, M., Trier, Ø. D., Salberg, A.-B., 2011. Evaluation of the Landsat surface reflectance estimated by LEDAPS. NR-Note No. SAMBA/37/11.
• Salberg, Arnt-Børre, 2009. Land cover classification of cloud-contaminated multi-temporal high-resolution satellite images. NR-Note No. SAMBA/45/09.