Dr. Tobias Rentschler

Address:
Eberhard Karls University Tübingen
Digital Humanities Center
Keplerstr. 2
D-72070 Tübingen

Office: Keplerstr. 2, Room 139

Contact:
+49(0)7071-29-73621
t.rentschlerspam prevention@uni-tuebingen.de

Consulting hours:
By arrangement

Web of Science: ORCID:

Functions:

2021-today SFB 1070: Representative for Postdocs of the Executive Board
2020-2021 Faculty of Science: Member of the Board of Representatives of the Postgraduate Convention
2017-2021 SFB 1070: Deputy Representative for PhD Candidates of the Executive Board

Research Topics:

Research data management
Spatial humanities
Geoinformatics and spatial statistics
Environmental modelling with machine learning

Project:

SFB 1070 ResourceCultures, Project S: Service Project Research data management

CV:

*14^th August 1989 in Calw

Work experience

Since 2021

Senior Researcher

SFB 1070 ResourceCultures project S: Research data management, Eberhard Karls Universität Tübingen

2017-2021

Research Associate

SFB 1070 ResourceCultures project S: Geoscientific and geoarchaeological consulting, Eberhard Karls Universität Tübingen

2017

Trainee

Swiss Soil Monitoring Network, modelling section, Agroscope, Federal Department of Economic Affairs, Education and Research, Switzerland

2013-2017

Research assistant in different third-party funding projects

Chair of Physical Geography, Eberhard Karls Universität Tübingen • Chair of Soil Science and Geomorphology, Eberhard Karls Universität Tübingen • BEF China (FOR 891): The role of tree and shrub diversity for production, erosion control, element cycling, and species conservation in Chinese subtropical forest ecosystems, Eberhard Karls Universität Tübingen • SFB 1070 ResourceCultures. B03 Exploitation of Resources and Ruling Areas in the Middle Ages, Eberhard Karls Universität Tübingen • SNF-Project: Region, Nation and Beyond. An Interdisciplinary and Transcultural Reconceptualization of Ukraine, Universität St. GallenSoil

Education

11/2020

Doctoral degree: Explainable machine learning in soil mapping (Dr. rer. nat.)

Eberhard Karls University of Tübingen

2017 to 2020

Doctoral student

Doctoral student at the Faculty of Science, Eberhard Karls University of Tübingen

2014 to 2017

Study of physical Geography (M.Sc.)

Landscape System Sciences (M.Sc.), Eberhard Karls Universität Tübingen

2010 to 2014

Study of physical Geography (B.Sc.)

Study of Geography (B.Sc.), Eberhard Karls Universität Tübingen

Teaching

Several bachelor and master modules in geography since 2013: GEO 31, GEO 34, GEO 44, GEO 76, GEO 77, GEO 96:

Geoinformatics, Geographical Information Systems, and remote sensing
Soil-Landscape Modelling, machine learning in enviromental sciences
Soil, Geomorphology, and Geophysics
Spatial Statistics

Peer reviewed publications

2022	Rentschler, T., Bartelheim, M., Behrens, T., Díaz-Zorita Bonilla, M., Teuber, S., Scholten, T., Schmidt, K. (2022): Contextual spatial modelling in the horizontal and vertical domains. Scientific reports, 12, 1, 9496. doi: 10.1038/s41598-022-13514-5 Rentschler, T., Schmidt, K., Nitschke, R., Scholten, T., Teuber, S., (2021): Soil spectroscopy data from 130 soil profiles in Lora del Rio, Andalusia, Spain. PANGAEA. doi.pangaea.de/10.1594/PANGAEA.938522 Rentschler, T., Schmidt, K., Behrens, T., Scholten, T., (2021): Soil quality and soil property data and terrain data for 3D multi-scale contextual spatial modelling in Lora del Rio, Andalusia, Spain. PANGAEA. doi.pangaea.de/10.1594/PANGAEA.938774
2020	Rentschler, T., Werban, U., Ahner, M., Behrens, T., Gries, P., Scholten, T., Teuber, S., Schmidt, K. (2020): 3D mapping of soil organic carbon content and soil moisture with multiple geophysical sensors and machine learning. Vadose Zone Journal 19, 1. doi: 10.1002/vzj2.20062
	Stumpf, F., Schneider, M.K., Keller, A., Mayr, A., Rentschler, T., Meuli, R.G., Schaepman, M., Liebisch, F. (2020): Spatial monitoring of grassland management using multi-temporal satellite imagery. Ecological Indicators 113, 106201. doi: 10.1016/j.ecolind.2020.106201
	Taghizadeh-Mehrjardi, R., Schmidt, K., Amirian-Chakan, A., Rentschler, T., Zeraatpisheh, M., Sarmadian, F., Valavi, R., Davatgar, N., Behrens, T., Scholten, T. (2020): Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space. Remote Sensing 12 1095. doi: 10.3390/rs12071095
2019	Rentschler, T., Gries, P., Behrens, T., Bruelheide, H., Kühn, P., Seitz, S., Shi, X., Trogisch, S., Scholten, T., Schmidt, K. (2019): Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China. PLoS ONE 14(8): e0220881. doi: 10.1371/journal.pone.0220881
2017	Schmaltz, E.M., Rosner, H.-J., Rentschler, T., Märker, M. (2017): Assessment of groundwater response and soil moisture fluctuations in the Mugello Basin (central Italy). Geography, Environment, Sustainability (GES Journal) 10/2, 15-27. doi: 10.24057/2071-9388-2017-10-2-15-27

Conference Contributions

24	Rentschler, T., Scholten, T., Schmidt, K.: Notes on explainable machine learning in spatial modelling. Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2023, Halle (Saale). [talk]
23	Bellat, M., Glissmann, B., Taghizadeh, R., Rentschler, T., Sconzo, P., Pfälzner, P., Scholten, T.: From site observation to regional interpretation, the influence of multi-scalar approach on soil properties and their archaeological implication: Kurdistan (Iraq). XXI INQUA Congress 2023, Rome. [talk]
22	Bellat, M., Glissmann, B., Taghizadeh, R., Rentschler, T., Sconzo, P., Pfälzner, P., Scholten, T.: Can soil information add value for the archaeological predictive model? ICAANE 2023, Copenhagen. [talk]
21	Bellat, M., Glissmann, B., Taghizadeh, R., Rentschler, T., Sconzo, P., Pfälzner, P., Scholten, T. (2023): Spatial soil information as a proxy for archaeological predictive modelling in arid regions: the Selevani plain example (Kurdistan, Iraq). CAA 2023, Amsterdam. [poster]
20	Rentschler, T., Bartelheim, M., Behrens, T., Díaz-Zorita Bonilla, M., Scholten, T., Schmidt, K.: Tiefenbezogene und skalenabhängige Modellierung der Bodenqualität in Andalusien, Spanien. Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2022, Trier. [talk]
19	Taghizadeh-Mehrjardi, R., Rentschler, T., Schmidt, K., Cheshmberah, F., Scholten, T.: Improving the spatial prediction of soil texture fractions using semisupervised machine learning in Germany. Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2022, Trier. [talk]
18	Rentschler, T., Bartelheim, M., Behrens, T., Díaz-Zorita Bonilla, M., Scholten, T., Schmidt, K.: The relevant range of scales for 3D multi-scale contextual spatial modelling. 22nd World Congress of Soil Science, Glasgow, United Kingdom. [talk]
17	Bellat, M., Glissmann, B., Rentschler, T., Schmidt, K., Sconzo, P., Pfälzner, P., Scholten, T.: Unraveling archaeological settlement, landscape, and resource use patterns with machine learning in Kurdistan (Iraq). EGU General Assembly 2022, Vienna. [talk]
16	Rau, K., Gläßle, T., Rentschler, T., Hennig, P., Scholten, T.: Spatial prediction of soil thickness with Gaussian Process Regression using pedological knowledge described by partial differential equations. EGU General Assembly 2021, Vienna. [online PICO]
15	Rentschler, T., Bartelheim, M., Díaz-Zorita Bonilla, M., Gries, P., Scholten, T., Schmidt, K.: Volumetric soil quality modelling with machine learning in a diverse agricultural landscape in Andalusia, Spain. EGU General Assembly 2020, Vienna. [online talk]
14	Bindereif, L., Rentschler, T., Batelheim, M., Díaz-Zorita Bonilla, M., Gries, P., Scholten, T., Schmidt, K.: Synthetic sampling for spatio-temporal land cover mapping with machine learning and the Google Earth Engine in Andalusia, Spain. EGU General Assembly 2020, Vienna. [online talk]
13	Scholten, T., Rentschler, T., Taghizadeh-Mehrjardi, R., Schmidt, K.: Prediction of Drought Risk and Soil Quality using FTIR and ML - Examples from Prehistoric Andalusia, Spain. Interdisciplinary and International Workshop 2019 Linares, Spain. [talk]
12	Rentschler, T., Bartelheim, M., Díaz-Zorita Bonilla, M., Scholten, T., Schmidt, K.: Convolutional neural networks und Nahinfrarotspektroskopie für die Prognose von Bodenqualitätsindikatoren. Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2019, Bern, Schweiz. [talk]
11	Rentschler, T., Ahner, M., Behrens, T., Gries, P., Kühn., P., Werban, U., Scholten, T., Schmidt, K.: Volumetric mapping of soil organic carbon and soil water content with electrical conductivity data. Pedometrics 2019, Guelph, Ontario, Canada. [talk]
10	Rentschler, T., Ahner, M., Behrens, T., Gries, P., Kühn, P., Werban, U., Scholten, T., Schmidt, K.: Three-dimensional mapping of soil organic carbon and soil water content with proximal soil sensing data. EGU General Assembly 2019, Vienna. [PICO]
9	Bindereif, L., Rentschler, T., Bartelheim, M., Díaz-Zorita Bonilla, M., Gries, P., Scholten, T., Schmidt, K.: Analysis and mapping of spatio-temporal land use dynamics in Andalusia, Spain using the Google Earth Engine cloud computing platform and the Landsat archive. EGU General Assembly 2019, Vienna. [poster]
8	Rentschler, T., Ahner, M., Behrens, T., Gries, P., Kühn, P., Werban, U., Scholten, T., Schmidt, K.: Dreidimensionale Kartierung des organischen Bodenkohlenstoffs und des Bodenwassergehalts mit geophysikalischen Methoden. 7th Digital Soil Mapping Workshop, Deutsche Bodenkundliche Gesellschaft (DBG), AG DSM 2019, Tübingen. [talk]
7	Rentschler, T., Gries, P., Behrens, T., Bruelheide, H., Kühn, P., Seitz, S., Trogisch, S., Scholten, T., Schmidt, K.: Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China. 2nd ISMC Conference: New Perspectives on Soil Models 2018, Wageningen, Netherlands. [poster]
6	Stumpf, F., Keller, A., Mayr, A., Rentschler, T., Schneider, M., Meuli, R., Schaepman, M., Liebisch, F.: Spatial monitoring of grassland management and plant diversity in Switzerland. SUSALPS Conference 2018, Garmisch-Partenkirchen, Germany. [talk]
5	Taghizadeh-Mehrjardi, R., Schmidt, K., Eftekhari K., Rentschler, T., Scholten, T.: Updating the categorical soil map of Iran using limited soil legacy data. 21st World Congress of Soil Science 2018, Rio de Janeiro, Brazil. [poster]
4	Rentschler, T., Schmidt, K.: Learning QGIS - Getting started with geospatial analysis and mapping. In Poseidons Reich XXIII, Jahrestagung der DEGUWA e.V. 2018, Tübingen. [workshop]
3	Rentschler, T., Kühn, P., Scholten, T., Schmidt, K.: Dreidimensionale Kartierung von SOC basierend auf maschinellem Lernen in Jiangxi, VR China. Deutscher Kongress für Geographie, Tübingen, Germany. [talk]
2	Rentschler, T., Kühn, P., Behrens, T., Scholten, T., Schmidt, K.: Dreidimensionale Modellierung von organischem Kohlenstoff im Boden basierend auf multi-skaliger Reliefanalyse und Methoden des Data Minings in Jiangxi, VR China. Deutsche Bodenkundliche Gesellschaft (DBG) Jahrestagung 2017, Göttingen, Germany. [talk]
1	Rentschler, T., Kühn, P., Scholten, T., Schmidt, K.: Three-dimensional mapping of soil organic carbon (SOC) based on multi-scale digital terrain analysis and data mining in Jiangxi Province, PR China. Pedometrics 2017, Wageningen, Netherlands. [poster]