Dr. Patrick Knöfel
Employment at the department:
07/2009 - 02/2017
Research projects at the departement:
Scientist at the "Phenological structure of high temporal resolution Sentinel-2 data sets" (PhenoS)
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Kumar, N., Khamzina, A., Tischbein, B., Knöfel, P., Conrad, C., und Lamers, J. P. A. (2019) Spatio-temporal supply–demand of surface water for agroforestry planning in saline landscape of the lower Amudarya Basin, Journal of Arid Environments 162, 53-61.
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Löw, F., Knöfel, P., und Conrad, C. (2015) Analysis of uncertainty in multi-temporal object-based classification, ISPRS - Journal of Photogrammetry and Remote Sensing 105, 91-106.
- Gläßer, C., Gerstmann, H., Conrad, C., and Knöfel, P. (2017) Optimization of multi-temporal Land Use Classification by Integration of Phenological time frames. In 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), pp 1-3, Belgium-Brugge.
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Knöfel, P., Dahms, T., Borg, E., and Conrad, C. (2017) Classification of agricultural land use and derivation of biophysical parameter using SAR and optical data. In Digitale Transformation – Wege in eine zukunftsfähige Landwirtschaft, Lecture Notes in Informatics (LNI), Dresden.
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Conrad, C., Schönbrodt-Stitt, S., Abdullaev, I., Dimo, D., Ibrakhimov, M., Knöfel, P., Leinich, M., Morper-Busch, L., Schorcht, G., Solodoky, G., Sorokin, A., Sorokin, D., Stulina, G., Toshpulatov, R., Unger-Shayesteh, K., Zaitov, S., and Dukhovny, V. (2016) Remote Sensing and GIS for Supporting the Agricultural Use of Land and Water Resources in the Aral Sea Basin. In Water Resources of Central Asia and their Use - Materials to the International Scientific-Practical Conference devoted to the summing-up of the "Water for Life" decade declared by the United Nations, Almaty, Kazakhstan.
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Knöfel, P., Uslar, J. von, and Conrad, C. (2016) Einfluss stratifizierter Probennahme auf die Genauigkeit multitemporaler objektbasierter Landnutzungsklassifikation. In 8. RESA Workshop, Bonn.
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Knöfel, P., Spengler, D., and Conrad, C. (2016) Phänologische Strukturierung von zeitlich hochauflösenden Sentinel-2-Datensätzen zur Optimierung von Landnutzungsklassifikationen. In Kickoff-Veranstaltung "EO4GEOSS", Bonn.
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Knöfel, P., Spengler, D., Conrad, C., and Borg, E. (2016) GLAM.DE - Global Agricultural Monitoring – The German Contribution, Joint workshop for JECAM/Sen2Agri/Sigma projects, Kiew, Urkaine.
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Knöfel, P., Dimov, D., Schönbrodt-Stitt, S., and Conrad, C. (2016) Estimation of actual evapotranspiration to derive irrigation efficiency indicators in the Aral Sea Basin, Central Asia. In AK Fernerkundung, Bonn.
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Gerstmann, H., Knöfel, P., Xu, X., Doktor, D., Möller, M., Thürkow, D., Conrad, C., and Gläßer, C. (2015) Phänologische Strukturierung von zeitlich hochauflösenden Sentinel-2-Datensätzen zur Optimierung von Landnutzungsklassifikationen. In Workshop: "Nutzung der Sentinels und nationalen Erdbeobachtungs-Missionen", Bonn.
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Knöfel, P., Gerstmann, H., Xu, X., and Conrad, C. (2015) Phänologische Strukturierung von zeitlich hochauflösenden Sentinel-2-Datensätzen zur Optimierung von Landnutzungsklassifikationen. In 7. RESA Workshop, Bonn.
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Knöfel, P., Löw, F., and Conrad, C. (2015) Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany. In European Geosciences Union General Assembly 2015, Wien, Austria.
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Knöfel, P., and Conrad, C. (2015) Evaluation of a Modified SEBAL Algorithm to Estimate Actual Evapotranspiration in Cotton Ecosystems of Central Asia using Microwave and Optical Remote Sensing Data. In European Geosciences Union General Assembly 2015, Wien, Austria.
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Knöfel, P., Löw, F., Möller, M., and Conrad, C. (2015) Evaluation of Uncertainty and Accuracy in Multi-Temporal Object-Based Land Use Classification, 36th International Symposium on Remote Sensing of Environment, Berlin.
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Knöfel, P., and Conrad, C. (2015) Introduction of a modified soil heat flux approach and its potential for improving remote sensing based surface energy balance. In Third Space for Hydrology Workshop, Frascati, Italy.
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Knöfel, P., Löw, F., Gerstmann, H., Möller, M., Xu, X., and Conrad, C. (2015) Introduction of a multifunctional tool for the evaluation of uncertainty and accuracy in multitemporal object-based land use classification. In SPIE Remote Sensing Conference, Toulouse, France.
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Knöfel, P., Conrad, C., Falk, U., and Bauer-Marschallinger, B. (2014) Validation of an improved energy balance model to estimate actual evapotranspiration in irrigated cotton ecosystems of Central Asia, Geophysical Research Abstracts Vol.16, EGU2014-10521 , EGU General Assembly, 27. April - 02. May 2014, Vienna, Austria.
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Knöfel, P. (2014) Entwicklung eines Analysetools zur Detektion optimaler Klassifikationszeitschnitte. In 6. RESA Workshop, Bonn.
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Knöfel, P., Conrad, C., and Dech, S. (2013) Potential of Remote Sensing Derived Soil Moisture for the Estimation of Actual Evapotranspiration in Cotton Ecosytems in Middle Asia. In Abstract Book, p 1.
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Knöfel, P., Conrad, C., and Dech, D. (2013) Potential of Remote Sensing Derived Soil Moisture for the Estimation of Actual Evapotranspiration in Cotton Ecosystems of Middle Asia.
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Knöfel, P., Conrad, C., and Dech, S. (2012) Validierung und Optimierung der fernerkundungsbasierten Bestimmung der tatsächlichen Evapotranspiration. In "1. Gemeinsames Arbeitskreis-Treffen AK „Fernerkundung“ der DGfG und AK „Interpretation von Fernerkundungsdaten“ der DGPF".
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Knoefel, P., Conrad, C., Falk, U., and Dech, S. (2012) Validation of remotely sensed estimation of actual evapotranspiration in cotton ecosystems of Middle Asia.
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Knoefel, P., Conrad, C., Falk, U., and Dech, S. (2012) Comparative analysis and validation of remotely sensed estimation of actual evapotranspiration in cotton ecosystems of Middle Asia. In Geophysical Research Abstracts, p 9251, EGU General Assembly, 22 - 27 April 2012. Vienna, Austria.
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Knoefel, P., Falk, U., Conrad, C., and Dech, S. (2011) Modellierung der tatsächlichen Evapotranspiration in der Bewässerungsregion Khorezm, Usbekistan, AK Fernerkundung, 29-30 September, Würzburg, Germany.