Prof. Dr. Anette Eltner
© M. Kretzschmar
Professor apl.
NameMs Prof. Dr. Anette Eltner
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Scientific Resume
- 2021 Junior Professor for Geosensor Systems, TU Dresden
- 2020-2021 Guest lecturer UAV photogrammetry in Geography, University Heidelberg
- 2020 TUD Young Investigator (TU Dresden status for excellent, independent junior research group leaders ...)
- 2016 PhD thesis (awarded by the german working group for geomorphology, AK Geomorphologie) "Photogrammetric techniques for across-scale soil erosion assessment - Developing methods to integrate multi-temporal high resolution topography data at field plots" (Qucosa)
- 2010 Diploma in Geography at the TU Dresden with minors in Photogrammetry/Remote Sensing, Soil Science and Hydrology
Research focus
- UAV photogrammetry and remote sensing
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Developing methods for geomorphological and hydrological monitoring
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Application of artificial intelligence in environmental sciences (Plattform lernende Systeme)
- Erosion processes in fragile landscapes
- Spatio-temporal high resolution topography (laserscanning, structure-from-motion, time-lapse)
- Image processing in geographic applications (automatic feature detection and tracking)
- Low-cost geosensors systems
Administration
- Head of the Examination Board for BSc Environmental Informatics
- Degree Program Coordinator for MSc Geoinformatics
Editorial Board Member
- Chief editor Geoscientific Instrumentation, Methods and Data Systems
- Photogrammetric Record
Publications
138 Entries
2025
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Low-cost instrumentation for monitoring wadi discharge: A Raspberry Shake and time-lapse camera system, 15 Mar 2025Electronic (full-text) versionResearch output: Contribution to conferences > Poster
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An empirical approach to separate camera-based elevation change measurements due to sediment yield from other soil erosion masking processes , 20 Jan 2025Electronic (full-text) versionResearch output: Contribution to conferences > Abstract
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Impact of burn severity of the July 2022 forest fire on soil hydrophobicity in the Elbe Sandstone temperate forest, 20 Jan 2025Electronic (full-text) versionResearch output: Contribution to conferences > Abstract
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Do we need to label large datasets for river water segmentation? Benchmark and stage estimation with minimum to non-labeled image time series, 2025, In: International journal of remote sensing. 46, 7, p. 2719-2747, 29 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Subpixel Automatic Detection of GCP Coordinates in Time-Lapse Images Using a Deep Learning Keypoint Network, 2025, In: IEEE Transactions on Geoscience and Remote Sensing. 63, 14 p., 5601714Electronic (full-text) versionResearch output: Contribution to journal > Research article
2024
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Low-Cost sensors for measuring wadi discharge - a Raspberry Pi based seismometer and time-lapse camera setup, 14 Dec 2024, In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLVIII-2/W8-2024, p. 243-250, 8 p.Electronic (full-text) versionResearch output: Contribution to journal > Conference article
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Synergistic image and point cloud processing of UAV data for urban flood modeling: point cloud smart thinning and curb mapping, 14 Dec 2024, 8th International ISPRS Workshop LowCost 3D - Sensors, Algorithms, Applications, 12–13 December 2024, Brescia, Italy. 2/W8-2024 ed., Vol. 48. p. 483–490, 8 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
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Decoding rainfall effects on soil surface changes: Empirical separation of sediment yield in time-lapse SfM photogrammetry measurements, 5 Dec 2024, In: Soil and Tillage Research. 248 (2025), 20 p., 106384Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Editorial for Special Issue: Virtual Geoscience, Dec 2024, In: PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 92, 6, p. 655, 1 p.Electronic (full-text) versionResearch output: Contribution to journal > Editorial (Lead article)
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Mapping indicator species of segetal flora for result-based payments in arable land using UAV imagery and deep learning, Dec 2024, In: Ecological indicators. 169, 112780Electronic (full-text) versionResearch output: Contribution to journal > Research article