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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-1/W1-2023
https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
05 Dec 2023
| 05 Dec 2023
A PRELIMINARY COMPARISON OF TWO EXCLUSION MAPS FOR LARGE-SCALE FLOOD MAPPING USING SENTINEL-1 DATA
Chair of Data Science in Earth Observation, Technical University of Munich, Arcisstraße 21, Munich 80333, Germany
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr 8, Vienna A-1040, Austria
B. Bauer-Marschallinger
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr 8, Vienna A-1040, Austria
W. Wagner
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr 8, Vienna A-1040, Austria
M. Chini
Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, 5 Avenue des Hauts-Fourneaux, Esch-sur-Alzette 4362, Luxembourg
X. X. Zhu
Chair of Data Science in Earth Observation, Technical University of Munich, Arcisstraße 21, Munich 80333, Germany
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We propose a methodology to calibrate the bankfull channel depth and roughness parameters in a 2-D hydraulic model using an archive of medium-resolution SAR satellite-derived flood extent maps. We used an identifiability methodology to locate the parameters and suggest the SAR images which could be optimally used for model calibration. We found that SAR images acquired around the flood peak provide best calibration potential for the depth parameter, improving when SAR images are combined.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
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Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
M. K. van der Molen, R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, T. C. Maximov, A. V. Kononov, T. Ohta, A. Kotani, M. C. Krol, and W. Peters
Hydrol. Earth Syst. Sci., 20, 605–624, https://doi.org/10.5194/hess-20-605-2016, https://doi.org/10.5194/hess-20-605-2016, 2016
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Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle. Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
G. Blöschl, A. P. Blaschke, M. Broer, C. Bucher, G. Carr, X. Chen, A. Eder, M. Exner-Kittridge, A. Farnleitner, A. Flores-Orozco, P. Haas, P. Hogan, A. Kazemi Amiri, M. Oismüller, J. Parajka, R. Silasari, P. Stadler, P. Strauss, M. Vreugdenhil, W. Wagner, and M. Zessner
Hydrol. Earth Syst. Sci., 20, 227–255, https://doi.org/10.5194/hess-20-227-2016, https://doi.org/10.5194/hess-20-227-2016, 2016
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This paper illustrates the experimental and monitoring set-up of the 66 ha Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Lower Austria, which allows meaningful hypothesis testing. The HOAL catchment features a range of different runoff generation processes (surface runoff, springs, tile drains, wetlands), and is convenient from a logistic point of view as all instruments can be connected to the power grid and a high-speed glassfibre local area network.
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
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We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
A. Piscini, M. Picchiani, M. Chini, S. Corradini, L. Merucci, F. Del Frate, and S. Stramondo
Atmos. Meas. Tech., 7, 4023–4047, https://doi.org/10.5194/amt-7-4023-2014, https://doi.org/10.5194/amt-7-4023-2014, 2014
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