Markus Möller

Environmental Science · Physical Sciences

25h-index2.8kcitations110works3.72yr avg
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Research Topics

Remote Sensing in Agriculture(23), Soil erosion and sediment transport(16), Soil Geostatistics and Mapping(14), Remote Sensing and LiDAR Applications(13), Land Use and Ecosystem Services(12)

Publications110 total

Are remote sensing-based crop type classifications suitable for calculating a landscape heterogeneity metric? A data-fitness-for-purpose assessment
Ecological Informatics·2026Open Access
Conceptual design of an application-specific data quality matrix for agrosystem data
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
Conceptual design of an application-specific data quality matrix for agrosystem data
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
Big Geodata and Spatial Data Infrastructures: a Perspective of a German Authority
PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science·2025· 1 citedOpen Access
Soil-erosion events on arable land are nowcast by machine learning
CATENA·2025· 3 cited
Enhancing environmental indicator trustworthiness: A framework for user-specific quality assessment of spatial input data using data-fitness-for-purpose principles
2025Open Access
DynAWI Extreme Weather Toolbox: an online platform for agricultural risk assessment and decision support
2025Open Access
Management und FAIRe Bereitstellung von multidimensionalen analysefertigen Rasterdaten mittels dynamischer Webdienste
OpenAgrar·2025
DynAWI-Extremwetter-Toolbox: Ein innovativer Ansatz zur Bewältigung von Klimaherausforderungen in derLandwirtschaft
OpenAgrar·2025
Wie genau und plausibel sind Machine Learning-Produkte zur Abschätzung des Oberboden-Kohlenstoffgehaltes landwirtschaftlicher Böden?
OpenAgrar·2025Open Access
Climate change induced heat and drought stress hamper climate change mitigation in German cereal production
Field Crops Research·2024· 9 citedOpen Access
Towards Optimising the Derivation of Phenological Phases of Different Crop Types over Germany Using Satellite Image Time Series
Remote Sensing·2024· 9 citedOpen Access
Soil-erosion events on arable land are nowcast by machine learning
2024Open Access
High resolution 3D images of sediment cores as powerful tool for exploring foraminiferal microhabitats
Marine Micropaleontology·2024· 1 citedOpen Access
Ensemble learning-based crop yield estimation: a scalable approach for supporting agricultural statistics
GIScience & Remote Sensing·2024· 24 citedOpen Access
A novel remote sensing-based approach to determine loss of agricultural soils due to soil sealing — a case study in Germany
Environmental Monitoring and Assessment·2024· 4 citedOpen Access
Site conditions determine heat and drought induced yield losses in wheat and rye in Germany
Environmental Research Letters·2024· 11 citedOpen Access
Regret‐free truth‐telling in school choice with consent
Theoretical Economics·2024· 8 citedOpen Access
Déchiffrer l’imagerie des monnaies celtiques à l’aide de la reconnaissance automatique des images, l’exemple des quinaires au rameau
SPIRE - Sciences Po Institutional REpository·2024Open Access
Towards optimising the derivation of phenological phases of different crop types over Germany using optical high resolution image time series
2023
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Frequent Co-authors

Cornelia Gläßer(7), Martin Völk(6), Heike Gerighausen(6), Henning Gerstmann(6), S. Cohen(5), Til Feike(5), S. Assouline(4), Josef Tanny(4), Burkhard Golla(4), Pasquale Borrelli(3), Christine Alewell(3), Jamil Alexandre Ayach Anache(3), Jantiene Baartman(3), Cristiano Ballabio(3), Nejc Bezak(3), Marcella Biddoccu(3), Artemi Cerdà(3), Devraj Chalise(3), Songchao Chen(3), Walter Chen(3)