The TETIS Joint Research Unit conducts research on the development of innovative methods for the production, analysis, and use of spatial information—particularly based on remote sensing data—to support rural areas in their transitions. Within the unit, the Earth Observation and Spatio-Temporal Indicators Group (GOST) aims to develop approaches based on existing or future multisensor Earth observation data for characterizing land surfaces and developing indicators and thematic products useful to the scientific community and local stakeholders.

One area of application for these developments is the characterization of agricultural systems and their evolution in the Global South, under the combined effects of multiple factors.

Through their methodological, technical, and thematic approaches, the position holder will contribute to the unit’s efforts to generate information on agricultural transitions (including agroecological transitions), the sustainability of food systems, the effects of climate change, and land-use planning.

This work will be conducted by incorporating current trends in remote sensing research (increasing availability of imagery, new open-source software tools, computing power, and new approaches and methods for data processing—including AI, etc.), which offer new opportunities for extracting key variables related to agricultural systems and landscapes.

More specifically, the incumbent’s responsibilities will include:

·        Identifying, creating, and extracting indicators (temporal, spatial, landscape-based; direct or indirect; generic or specific) from satellite imagery to characterize rural agroecosystems in the Global South and their changes

·        Identifying the main determinants (climatic, environmental, and/or socioeconomic) of these indicators and analyzing their trajectories

·        Selecting or adapting relevant “data (remote sensing, field data, surveys) / methods” combinations to address local constraints and challenges

·        Establishing multi-indicator approaches (composite indicators, convergence of evidence) to inform an assessment of farming practices, agricultural landscape structure, and their dynamics

·        Evaluating the scope of validity—particularly geographic and thematic—of the developed indicators, as well as their level of accuracy

The work will be conducted using an integrative approach at the intersection of several disciplines (geography, agronomy, socioeconomics, data science).

It will take into account the specific characteristics of the Global South in order to identify open-source solutions that are tailored to and transferable to partners.

Job Location

France, Montpellier

·        Ph.D. in space-based remote sensing applied to socio-agro-ecosystems

·        Proven experience and/or expertise in the following areas: agronomy, rural economics/geography, particularly related to development in the Global South (agroecology, agricultural transitions, etc.)

·        Solid experience in the processing and analysis of satellite image time series

·        Proficiency in software and programming tools for applying methods of processing, machine learning, and analysis of remote sensing data (QGIS, OTB, R, Python, and dedicated libraries, etc.), knowledge of standards for exploting shared online resources (STAC, Cloud Optimized Geotiff, Cloud Native Formats, etc.), and commitment to open science (Git repositories)

·        Experience in setting up and/or coordinating projects

·        At least 4 years of professional experience following completion of a Ph.D.

·        Proficiency in scientific English (spoken and written)

·        Experience working in interdisciplinary teams, in partnerships, with field actors, and within national and international research networks (e.g., GeoGLAM)

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