Publications - peer reviewed

Tsai, Y.-L.; Dietz, A.; Oppelt, N.; Kuenzer, C. (2019):

Remote Sensing of Snow Cover Using Spaceborne SAR: A Review. Remote Sens. 11/2019,

Tsai, Y.-L.; Dietz, A.; Oppelt, N.; Kuenzer, C. (2019):

Wet and dry snow detection using Sentinel-1 SAR data for mountaneous areas with a machine learning technique. Remote Sens. 11/2019,

Taravat, A.; Wagner, M.; Oppelt, N. (2019):

Automatic grassland cutting date detection in the context of spatiotemporal SAR imagery analysis and artificial neural networks. Remote Sens. 26,

Addae, B.; Oppelt, N. (2019):

Land-use/Land-cover Change Analysis and Urban Growth Modelling in the Greater Accra Metropolitan Area (GAMA), Ghana. Urban Sci. (3(1), 26,

König, M.; Hieronymi, M.; Oppelt, N. (2019):

Application of Sentinel-2 MSI in Arctic research: evaluating the performance of atmospheric correction approaches over Arctic sea ice. Frontiers in Earth Science - Cryosphere;

Fritz, C.; Kuhwald, K.; Schneider, T.; Geist, J.; Oppelt, N. (2019):

Sentinel-2 for mapping the spatio-temporal development of submerged aquatic vegetation at Lake Starnberg (Germany). Journal of Limnology, DOI: 10.4081/jlimnol.2019.1824

Baschek, B.; Dörnhöfer, K.; Fricke, K.; Oppelt, N. (2018):

Grundlagen und Möglichkeiten der passiven Fernerkundung von Binnengewässern. In: Handbuch Angewandte Limnologie 34.Erg.Lfg. 1/18  III-1.1.7: 28 Seiten.

Kuhwald, M.; Dörnhöfer, K.; Oppelt, N.; Duttmann, R. (2018):

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model. Sustainability. 2018.

Dörnhöfer, K.; Scholze, J.;  Stelzer, K.; Oppelt, N. (2018):

Water Colour Analysis of Lake Kummerow Using Time Series of Remote Sensing and In Situ Data. Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 2018.

Da Ponte, E.; Mack, B.; Wohlfahrt, C.; Rodas, O.; Fleckenstein, M.; Oppelt, N.; Dech, S.; Kuenzer, C. (2017):

Assessing forest cover dynamics and forest perception in the Atlantic forest of Paraguay, combining remote sensing and household level data. Forests 8(389), doi:10.3390/f8100389.

Dörnhöfer, K.; Klinger, P.; Heege, T.; Oppelt, N. (2017):

Multi-sensor astellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake. Science of the Total Environment, 612: 1200-1214.

Fritz, C.; Doernhoefer, K.; Schneider, T.; Geist, J.; Oppelt, N. (2017):

Mapping submerged aquatic vegetation using RapidEye satellite data: the example Lake Kummerow (Germany). Water 9(510), special issue "Water quality monitoring and modeling in lakes", doi:10.3390/w9070510.

DaPonte, E.; Kuenzer, C.; Parker, A.; Rodas, O.; Oppelt, N.; Fleckenstein, M. (2017):

Forest cover loss in Paraguay and perception of ecosystem services: a case study in the Upper Parana Forest. Ecosystem Services 24: 200-2012. 

Dörnhöfer, K.; Göritz, A.; Gege, P.; Pflug, B.; Oppelt, N. (2016):

Water constituents and water depth retrieval from Setinel-2A – a first evaluation in an oligotrophic lake. Remote Sensing 2016/7/941, doi:10.3390/rs8110941.

Peronaci, S.; Taravat, A.; del Frate, F.; Oppelt, N. (2016):

Use of NARX neural networks for Meteosat Second Generation SEVIRI very short-term cloud mask forecasting. International Journal of Remote Sensing 37/24: 6205-6215,

Uhl, F.; Bartsch, I.; Oppelt, N. (2016):

Submerged kelp detection with hyperspectral data. Remote Sensing, special issue on coastal remote sensing 8/487; doi:10.3390/rs8060487.

Oppelt, N. (2016):

Fernerkundung in der Hydrologie. In: Hydrologie (Eds. Fohrer, N. et al.), UTB. 

Dörnhöfer, K.; Oppelt, N. (2016)

Remote sensing for lake research and monitoring - recent advances. Ecological Indicators 64, pp. 105-122.

Oppelt, N.; Scheiber, R.; Wegmann, M.; Taubenboeck, H.; Gege, P.; Berger, M. (2015)
Fundamentals of remote sensing for terrestrial applications: evolution, current state-of-art, and future possibilities. In: Thenkabail, P.S. (Ed.). Remote Sensing Handbook, Vol I/Data Characterisation, Classification, and Accuracies. Chapter 2, pp. 61-83. Taylor and Francis, ISBN 9781482217865.

Vo, T.; Kuenzer, C.; Oppelt, N. (2015)

How remote sensing supports mangrove ecosystem service valuation: A case study in Ca Mau Province, Vietnam. Ecosystem Services 14, pp.67-75.

Da Ponte, E.; Leinenkugel, P.; Fleckenstein, M.; Parker, A.; Oppelt, N.; Kuenzer, C. (2015)

Tropical Forest Cover Dynamics for Latin America using Earth Observation Data: A Review Covering the Continental, Regional, and Local Scale. International Journal of Remote Sensing 36(12), pp. 3196-3242.

Leinenkugel, P.; Wolters, M.L.; Oppelt, N.; Kuenzer, C. (2015)
Tree cover and forest cover dynamics in the Mekong Basin from 2001 to 2011. Remote Sensing of Environment 158(1), pp. 376–392.

Taravat, A.; Proud, D.; Peronaci, S.; del Frate, F.; Oppelt, N. (2015)
Multilayer percetron neural networks model for Meteosat Second Generation SEVIRI daytime cloud masking. Remote Sensing 7(2), pp. 1529-1539,

Rathjens, H.; Oppelt, N.; Bosch, D.D.; Arnold, J.; Volk, M. (2014)
Development of a grid-based version of the SWAT landscape model. Hydrological Processes 29(6), pp. 900-914,

Rathjens, H.; Doernhofer, K.; Oppelt, N. (2014)
An interpolation and improvement approach for remotely sensed land cover data. International Journal of Applied Earth Observation and Geoinformation 31, pp. 1-12.

Kandziora, M.; Dörnhöfer, K.; Oppelt, N.; Müller, F. (2014)
Detecting land use and land cover changes in northern German agricultural landscapes to assess ecosystem service dynamics. Landscape Online 35, pp. 1-24,

Leinenkugel, P.; Oppelt, N.; Kuenzer, C. (2014)
A new land cover map for the Mekong: Southeast Asia´s largest transboundary river basin. Pacific Geographies 41, pp. 10-14.

Leinenkugel, P.; Wolters, M.; Kuenzer, C.; Oppelt, N.; Dech, S. (2014)
Sensitivity analysis for predicting continuous fields of tree-cover and fractional land-cover distributions in cloud-prone areas. International Journal of Remote Sensing 35(8), pp. 2799-2821.

Taravat, A.; Oppelt, N. (2014)
Weilbull multiplicative model and multilayer perceptron neural networks for dark-spot detection from SAR imagery. Sensors 14(12), Special issue on Modern Technologies for Sensing Pollution in Air, Water, and Soils, pp. 22798-22810,

Uhl, F.; Oppelt, N.; Bartsch, I. (2013)
Spectral mixture of intertidal marine macroalgae around the island of Helgoland (Germany, North Sea). Aquatic Botany 111, pp. 112-124,

Vo, T.Q.; Oppelt, N.; Kuenzer, C.; Leinenkugel, P. (2013)
Remote sensing in mapping ecosystem services - an object-based approach. Remote Sensing 5(1), pp.183-201,

Leinenkugel, P.; Kuenzer, C.; Oppelt, N.; Dech, S. (2013)
Characterisation of land surface phenology and land cover based on moderate resolution satellite data in cloud prone areas – a novel product for the complete Mekong Basin. Remote Sensing of Environment 136, pp. 180-198.

Oppelt, N. (2012)
Remote Sensing of Photosynthetic Parameters. In: Najafpour, M.M. (Ed.). Applied Photosynthesis. InTech Publisher, Rijeka (CRO), pp. 141-164, ISBN: 978-953-51-0061-4.

Vo, Q.T.; Kuenzer, C.; Vo, Q,M.; Moder, F.; Oppelt, N. (2012)
Review of valuation methods of mangrove ecosystem services. Ecological Indicators 23(1), pp. 431-446,

Rathjens, H.; Oppelt, N. (2012)
SWAT model calibration of a grid-based setup. Advances in Geosciences 32, pp. 55-61,

Oppelt, N.; Schulze, F.; Bartsch, I.; Doernhoefer, K.; Eisenhardt, I. (2012)
Hyperspectral Classification Approaches for Intertidal Macroalgae Habitat Mapping: a Case Study in Heligoland. Optical Engineering 51(11), 111703,

Rathjens, H.; Oppelt, N. (2011)
SWATgrid: An interface for setting up SWAT in a grid-based discretization scheme. Computers & Geosciences 45, pp. 161-167,

Oppelt, N. (2010)
The use of remote sensing data to assist crop modelling under climate change conditions. Journal of Applied Remote Sensing 4(1), 041896,

Oppelt, N. (2010)
Monitoring of the biophysical status of vegetation using multi-angular, hyperspectral remote sensing for the optimization of a physically-based SVAT model. Kieler Geographische Schriften 121, CAU Kiel (Germany), ISBN 978-3-923887-63-7.

Oppelt, N.; Hank, T. (2009)
Improved modeling of maize growth by combining a biophysical model of photosynthesis with hyperspectral remote sensing. In: Henten, E.J.; Goense, D.; Lokhorst, C. (Eds.). Precision Agriculture '09. Wageningen Academic Publishers, pp. 133-140,

Oppelt, N. (2008)
Vertical profiling of vegetation canopies using multi-angular remote sensing data. Canadian Journal of Remote Sensing 34(2), pp. 314-325,

Oppelt, N.; Hank, T.; Mauser, W. (2007)
Assessment of vertical variation of chlorophyll using hyperspectral, multiangular imagery. In: Stafford, J. (Ed.). Precision Agriculture '07. Wageningen Academic Publishers, pp. 181-188, ISBN: 978-90-8686-024-1 (reviewed).

Hank, T.; Oppelt, N.; Mauser, W. (2007)
Physically based modelling of photosynthetic processes. In: Stafford, J. (Ed.). Precision Agriculture '07. Wageningen Academic Publishers, pp. 165-172, ISBN: 978-90-8686-024-1 (reviewed).

Oppelt, N.; Mauser, W. (2007)
Airborne Visible /Infrared Imaging Spectrometer AVIS: Design, Characterization and Calibration. Sensors 7(9), pp. 1934-1953,

Oppelt, N.; Mauser, W. (2004)
Hyperspectral Monitoring of Physiological Parameters of Wheat during a Vegetation Period Using AVIS Data. International Journal of Remote Sensing 25(1), pp. 145-160.

Oppelt, N.; Mauser, W. (2003)
Hyperspectral Remote Sensing - a Tool for the Derivation of Plant Nitrogen and its Spatial Variability. In: Stafford, J.; Werner, A. (Eds.). Precision Agriculture '03. Wageningen Academic Publishers, pp. 493-498 (reviewed).

Oppelt, N. (2002)
Monitoring of Plant Chlorophyll and Nitrogen Status Using the Airborne Imaging Spectrometer AVIS. PhD thesis. Ludwig-Maximilians Universität München.