Fachbereich 6 Mathematik/Informatik

Institut für Informatik

Navigation und Suche der Universität Osnabrück



Peer-reviewed journal papers 


Muro, J., Varea, A., Strauch, A., Guelmami, A., Fitoka, E., Thonfeld, F., Diekkrüger, B., & Waske, B. (2020). Multitemporal optical and radar metrics for wetland mapping at national level in Albania. Heliyon, 6, doi.org/10.1016/j.heliyon.2020.e04496

Fenske, K., Feilhauer, H., Förster, M., Stellmes, M., & Waske, B. (2020). Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series. International Journal of Applied Earth Observation and Geoinformation, 87, 102036.

Rosentreter, J., Hagensieker, R., & Waske, B. (2020). Towards large-scale mapping of local climate zones using multitemporal Sentinel 2 data and convolutional neural networks. Remote Sensing of Environment, 237, 111472.


Bauer, J., Jarmer, T., Schittenhelm, S., Siegmann, B. & Aschenbruck, N., 2019. Processing and filtering of leaf area index time series assessed by in-situ wireless sensor networks. Computers and Electronics in Agriculture, 165, 14p.

Crowson, M., Hagensieker, R., & Waske, B., 2019. Mapping land cover change in northern Brazil with limited training data. International Journal of Applied Earth Observation and Geoinformation, 78, 202-214.

Haburaj, V., Krause, J., Pless, S., Waske, B., & Schutt, B., 2019. Evaluating the Potential of Semi-Automated Image Analysis for Delimiting Soil and Sediment Layers. Journal of Field Archaeology, 44(8), 538-549.

Hänel, T., Jarmer, T. & Aschenbruck, N., 2019. Using distributed compressed sensing to derive continuous hyperspectral imaging from a wireless sensor network. Computers and Electronics in Agriculture, 166, 9p.

Marchetti, F., Waske, B., Arbelo, M., Moreno-Ruíz, J. A., & Alonso-Benito, A., 2019. Mapping Chestnut Stands Using Bi-Temporal VHR Data. Remote Sensing, 11(21), 2560.


Baumann, M., Levers, C., Macchi, L., Bluhm, H., Waske, B., Gasparri, N. I., & Kuemmerle, T., 2018. Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data. Remote Sensing of Environment, 216, 201-211.

Hagensieker, R., & Waske, B., 2018. Evaluation of multi-frequency SAR images for tropical land cover mapping. Remote Sensing, 10(2), 1-16.

Kanning, M., Kühling, I., Trautz, D. & Jarmer, T., 2018. High resolution UAV-based hyperspectral imagery for LAI and chlorophyll estimations from wheat for yield prediction. Remote Sensing, 10(12), 2000.

Muro, J., Strauch, A., Heinemann, S., Steinbach, S., Thonfeld, F., Waske, B., & Diekkruger, B., 2018. Land surface temperature trends as indicator of land use changes in wetlands. International Journal of Applied Earth Observation and Geoinformation, 70, 62-71.

Polinova, M., Jarmer, T., Brook, A., 2018. Spectral data source effect on crop state estimation by vegetation indices. Environmental Earth Sciences, 77, 752.

Steinhausen, M. J., Wagner, P. D., Narasimhan, B., & Waske, B., 2018. Combining Sentinel-1 and Sentinel-2 data for improved land use and land cover mapping of monsoon regions. International Journal of Applied Earth Observation and Geoinformation, 73, 595-604.

Zhang, S., Foerster, S., Medeiros, P., de Araújo, J. C., & Waske, B., 2018. Effective water surface mapping in macrophyte-covered reservoirs in NE Brazil based on TerraSAR-X time series. International Journal of Applied Earth Observation and Geoinformation, 69, 41-55.


Hagensieker, R., Roscher, R., Rosentreter, J., Jakimow, B., & Waske, B., 2017. Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data. International Journal of Applied Earth Observation and Geoinformation, 63, 244-256.

Locher-Krause, K. E., Volk, M., Waske, B., Thonfeld, F., & Lautenbach, S., 2017. Expanding temporal resolution in landscape transformations: Insights from a landsat-based case study in Southern Chile. Ecological Indicators, 75, 132-144.

Mack, B., & Waske, B., 2017. In-depth comparisons of MaxEnt, biased SVM and one-class SVM for one-class classification of remote sensing data. Remote Sensing Letters, 8(3), 290-299.

Rosentreter, J., Hagensieker, R., Okujeni, A., Roscher, R., Wagner, P. D., & Waske, B., 2017. Subpixel mapping of urban areas using EnMAP data and Multioutput Support Vector Regression. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5), 1938-1948.


Bauer, J., Siegmann, B., Jarmer, T. & Aschenbruck, N., 2016. On the potential of wireless sensor networks for the in-situ assessment of crop leaf area index. Computers and Electronics in Agriculture, 128, 149-159.

Jarmer, T. & Shoshany, M., 2016. Relationships between soil spectral and chemical properties along a climatic gradient in the Judean Desert. Arid Land Research and Management, 30(2), 123-137.

Joshi, N., Baumann, M., Ehammer, A., Fensholt, R., Grogan, K., Hostert, P., Rudbeck Jepsen, M., Kuemmerle, T., Meyfroidt, P., Mitchard, E.T.A., Reiche, J., Ryan, C.M. & Waske, B., 2016. A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. Remote Sensing, 8(1), 70.

Kanning, M., Siegmann, B. & Jarmer, T., 2016. Regionalization of uncovered agricultural soils based on organic carbon and soil texture estimations. Remote Sensing, 8, 927-943.

Mack, B., Roscher, R., Stenzel, S., Feilhauer, H., Schmidtlein, S., & Waske, B., 2016. Mapping raised bogs with an iterative one-class classification approach. ISPRS Journal of Photogrammetry and Remote Sensing, 120, 53-64.

Roscher, R., & Waske, B., 2016. Shapelet-based sparse representation for landcover classification of hyperspectral images. Geoscience and Remote Sensing, IEEE Transactions on, 54(3), 1623-1634.

Trinder, J., & Waske, B., 2016. Theme section for 36th International Symposium for Remote Sensing of the Environment in Berlin. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 463-463.

Wagner, P. D., & Waske, B., 2016. Importance of spatially distributed hydrologic variables for land use change modeling. Environmental Modelling & Software, 83, 245-254.

Zhang, S. P., Foerster, S., Medeiros, P., de Araujo, J. C., Motagh, M., & Waske, B., 2016. Bathymetric survey of water reservoirs in north-eastern Brazil based on TanDEM-X satellite data. Science of The Total Environment, 571, 575-593.


Beyer, F., Jarmer, T. & Siegmann, B., 2015. Identification of agricultural crop types in Northern Israel using multitemporal RapidEye data. Photogrammetrie-Fernerkundung-Geoinformation, 1/2015, 21-32.

Du, P., Samat, A., Waske, B., Liu, S., & Li, Z., 2015. Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features. ISPRS Journal of Photogrammetry and Remote Sensing, 105(0), 38-53.

Siegmann, B. & Jarmer, T., 2015. Comparison of different regression models and validation techniques for the assessment of wheat leaf area index from hyperspectral data. International Journal of Remote Sensing, 36(18), 4519-4534.

Siegmann, B., Jarmer, T., Beyer, F. & Ehlers, M., 2015. The potential of pan-sharpened EnMAP data for the assessment of wheat LAI. Remote Sensing, 7, 12737-12762.


Mack, B., Roscher, R., & Waske, B., 2014. Can I trust my one-class classification? Remote Sensing, 6(9), 8779-8802.

Stefanski, J., Chaskovskyy, O., & Waske, B., 2014. Mapping and monitoring of land use changes in post-Soviet western Ukraine using remote sensing data. Applied Geography, 55, 155-164.

Stefanski, J., Kuemmerle, T., Chaskovskyy, O., Griffiths, P., Havryluk, V., Knorn, J., Korol, N., Sieber, A. & Waske, B., 2014. Mapping land management regimes in Western Ukraine using optical and SAR data. Remote Sensing, 6(6), 5279-5305.

Suess, S., van der Linden, S., Leitao, P. J., Okujeni, A., Waske, B., & Hostert, P., 2014. Import Vector Machines for quantitative analysis of hyperspectral data. IEEE Geoscience and Remote Sensing Letters, 11(2), 449-453.


Jarmer, T., 2013. Spectroscopy and hyperspectral imagery for monitoring summer barley. International Journal of Remote Sensing, 34(17), 6067-6078.

Stefanski, J., Mack, B., & Waske, B., 2013. Optimization of object-based image analysis with Random Forests for land cover mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(6), 2492-2504.


Klemenjak, S., Waske, B., Valero, S., & Chanussot, J., 2012. Automatic detection of rivers in high-resolution SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(5), 1364-1372.

Roscher, R., Forstner, W., & Waske, B., 2012. (IVM)-V-2: Incremental import vector machines. Image and Vision Computing, 30(4-5), 263-278.

Roscher, R., Waske, B., & Forstner, W., 2012. Incremental Import Vector Machines for classifying hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, 50(9), 3463-3473.

Waske, B., van der Linden, S., Oldenburg, C., Jakimow, B., Rabe, A., & Hostert, P., 2012. imageRF - A user-oriented implementation for remote sensing image analysis with Random Forests. Environmental Modelling & Software, 35, 192-193.


Schwanghart, W. & Jarmer, T., 2011. Linking spatial patterns of soil organic carbon to topography - a case study from south-eastern Spain. Geomorphology, 126, 252-263.

Shoshany, M., Kizel, F., Netanyahu, N.S., Goldshlager, N., Jarmer, T. & Even-Tzur, G., 2011. An iterative search in end-member fraction space for spectral unmixing. Geoscience and Remote Sensing Letters, 99, 706-709.