Dr. M.T. Marshall | People Pages: Find employees & contact details

I seek to improve our understanding of crop carbon and water exchange from field to global scales. I answer my research questions with models that capture the spatio-temporal dynamics of agricultural production (area × yield) and evapotranspiration. The models are: (i) implemented in a Geographic Information System; (ii) based on principles of light-use efficiency and machine-learning; and (iii) driven by Earth observation, climate reanalysis, and other geospatial information. The work flow reduces uncertainties in crop models and improves agricultural monitoring systems, as well as motivates my teaching and training activities. Ultimately, my work increases agricultural production, enhances resilience of crops to drought and other climate shocks, and reduces CO₂ emissions caused by agricultural expansion into natural ecosystems. Such outcomes help achieve Sustainable Development Goal SDG-2 (“Zero Hunger”), SDG-6 (“Clean Water and Sanitation”), SDG-13 (“Climate Action”), and SDG-15 (“Life on Land”).

Editor of Agricultural and Forest Meteorology

Expertise

Earth and Planetary Sciences
- Model
- Cartography
- Investigation
- Farmland
- Vegetation Index
- Evapotranspiration
- Remote Sensing
- Datum

Organisations

Associate Professor in Crop Resilience and Sustainable Land Use

Research and Innovation Priorities

Better data: Enhance field measurement networks to calibrate and validate AI-driven satellite Earth Observation methods for crop productivity, water use, and carbon fluxes.
Better models: Develop knowledge-based AI model hybrids that integrate multi-scale satellite Earth Observation data to reduce uncertainty in crop yield, evapotranspiration, and carbon cycle predictions.
Better insights: Design AI-powered decision-support systems that translate satellite Earth Observation data on crop productivity, water use, and carbon dynamics into actionable strategies for sustainable agriculture and land management.

Publications

2025

Crop productivity under heat stress: a structural analysis of light use efficiency models (2025)Agricultural and forest meteorology, 362. Article 110376. Lai, P., Marshall, M. T., Darvishzadeh, R. & Nelson, A. D.https://doi.org/10.1016/j.agrformet.2024.110376

2024

The influence of temporal resolution on crop yield estimation with Earth Observation data assimilation (2024)Remote Sensing Applications: Society and Environment, 36. Article 101272. Tilahun, B. S., Marshall, M. T., Mengistu, D. & Nelson, A. D.https://doi.org/10.1016/j.rsase.2024.101272Characterizing crop productivity under heat stress using MODIS data (2024)Agricultural and forest meteorology, 355, 1-15. Article 110116. Lai, P., Marshall, M., Darvishzadeh, R., Tu, K. & Nelson, A.https://doi.org/10.1016/j.agrformet.2024.110116Enhancing regional estimates of evapotranspiration with earth observation data (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). Zhang, L.https://doi.org/10.3990/1.9789036561259Crop growth and yield monitoring in smallholder agricultural systems: a multi-sensor data fusion approach (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). Tilahun, B. S.https://doi.org/10.3990/1.9789036560818CROP GROWTH AND YIELD MONITORING IN SMALLHOLDER AGRICULTURAL SYSTEMS: A MULTI-SENSOR DATA FUSION APPROACH (2024)[Dataset Types › Dataset]. DATA Archiving and Networked Services (DANS). Tilahun, B. S., Marshall, M. T. & Nelson, A.https://doi.org/10.17026/PT/PVCRILEnhanced Detection of Artisanal Small-Scale Mining with Spectral and Textural Segmentation of Landsat Time Series (2024)Remote sensing, 16(10). Article 1749. Fonseca, A., Marshall, M. T. & Salama, S.https://doi.org/10.3390/rs16101749A method for estimating physical and economic food access at high spatial resolution (2024)Food security, 16, 47-64. Campomanes V, F., Marshall, M. & Nelson, A.https://doi.org/10.1007/s12571-023-01404-1Assimilation of Earth Observation data for crop yield estimation in smallholder agricultural systems (2024)IEEE Journal of selected topics in applied earth observations and remote sensing, 17, 557-572. Sisheber, B., Marshall, M., Mengistu, D. & Nelson, A.https://doi.org/10.1109/jstars.2023.3329237Remote sensing of evapotranspiration from croplands (2024)In Remote Sensing Handbook, Volume V (Six Volume Set): Water, Hydrology, Floods, Snow and Ice, Wetlands, and Water Productivity, Second Edition (pp. 313-382). CRC Press. Biggs, T. W., Nagler, P. L., Ruhoff, A., Petsini, T., Marshall, M., Kagone, S., Senay, G. B., Petropoulos, G. P., Abe, C. & Glenn, E. P.https://doi.org/10.1201/9781003541400-15

Research profiles

I grew up in the Mojave Desert where a few spectacular weeks a year a wanderer’s senses are stimulated by the unique smells of thirst-quenched soil and sudden wildflower blooms. These early experiences and my exposure to amazing educators influenced me profoundly. Consequently, I am driven to understand how we impact our environment and to help students discover their own passion in this regard.

Past Webinar

Monitoring Rangeland Carrying Capacity with EO

Noy-Meir Carrying Capacity Calculation

Supplementary Reading

Ungar (2019)

de Leeuw et al. (2019)

Courses academic year 2024/2025

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.