Maite Lezama Valdes
Remote Sensing and Spatial Modelling Research Group
Institute of Landscape Ecology
Heisenbergstr. 2, D-48149 Münster
room 546
phone +49(0)251-83 33 679
e-mail maite.lezama [at] uni-muenster.de
office hours on appointment
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Research Areas
- Downscaling
- machine learning
- remote sensing
CV
Education
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- MSc Physical Geography Philipps Universität Marburg
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- MA Soziologie und Sozialforschung Philipps Universität Marburg
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- BSc Geography Philipps University Marburg
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- BA Social Sciences Philipps Universität Marburg
Positions
- since
- Doktorandin am Institut für Landschaftsökologie Münster
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- PhD candidate Institute for Geoinformatics Münster
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Teaching
- Übung: Ü Remote Sensing and Spatial Modelling Forum [146726]
(in cooperation with Prof. Dr. Hanna Meyer)
[ - | | wöchentlich | Mo. | GEO1 513 | Lilian-Maite Lezama Valdes] - Übung: Ü Analyse und Visualisierung ökologischer Daten in R [146725]
[ - | | wöchentlich | Do. | StudLab GEO1 130 | Lilian-Maite Lezama Valdes]
- Praktische Übung: P Remote sensing based analysis of environmental change [144590]
(in cooperation with Prof. Dr. Hanna Meyer)
[ - | | wöchentlich | Di. | StudLab GEO1 125 | Prof. Dr. Hanna Meyer] - Übung: Ü Ecological data analysis and visualization with R [144572]
[ - | | wöchentlich | Do. | Lilian-Maite Lezama Valdes] - Seminar: Ü Acquisition and analysis of UAS-based image data [144644]
(in cooperation with Prof. Dr. Hanna Meyer)
[ - | | wöchentlich | Mo. | GEO1 513 | Lilian-Maite Lezama Valdes]
- Praktikum/Seminar: Environmental Statistics I [142724]
- Praktikum/Seminar: S Landschaftsökologische GIS&Fernerkundungsprojekte [142717]
(in cooperation with Prof. Dr. Hanna Meyer)
- Übung: Ü Remote Sensing and Spatial Modelling Forum [146726]
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Publications
Articles in Journals
- . . ‘Machine learning and multi-sensor based modelling of woody vegetation in the Molopo Area, South Africa.’ Remote Sensing of Environment 222: 195 - 203. doi: https://doi.org/10.1016/j.rse.2018.12.019.
Short Articles (Poster or Abstracts)
- . ‘Downscaling Land Surface Temperature for the Antarctic Dry Valleys using Multi-Sensor Data and Machine Learning.’ contributed to the EGU General Assembly 2019, Wien, Österreich, .