EGU24-1481, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Overcoming Barriers to Sustainable Rice Production: A Remote Sensing-Enabled Approach

Nick Kupfer1, Carsten Montzka1, and Tuan Quoc Vo2
Nick Kupfer et al.
  • 1Research Center Jülich, IBG-3 Agrosphere, Germany
  • 2Department of Land Resources, College of Environment and Natural Resources, Can Tho University, Vietnam

In Vietnam, conventional rice cultivation is under strong economic and ecological pressure. Against this backdrop, there is a rising demand for organic products both domestically and globally. In response, OrganoRice aims to facilitate the transition to organic farming in the model provinces of Vinh Long, Dong Thap, and An Giang in the Mekong Delta through a collaborative effort between German and Vietnamese partners. The initiative encompasses not only addressing physical challenges such as soil and water pollution reduction, optimal fertilization, and ecological plant protection but also delves into critical socio-economic dimensions, including enhancing the income of rice farmers and product marketing. The project acknowledges the intricate task of integrating cultural identity and individual farmers into the social fabric of the village community as a crucial factor for success in the conversion process. Direct communication with the rural population is prioritized, and key local stakeholders and scientific institutions, such as Can Tho University, play pivotal roles in ensuring the project's sustainable success.

The Mekong Delta's agricultural landscape is being explored through advanced tools such as remote sensing and hydrological simulations to map, predict, and optimize crop types, agricultural practices (both conventional and organic), and irrigation water pathways. Leveraging European Copernicus satellites Sentinel-1 and Sentinel-2, alongside PlanetScope equipped with radar and multispectral sensors, allows for monitoring plant growth conditions at a high spatial resolution. The analytical process involves examining remotely sensed data through phenological metrics, quantile mapping, and Fourier transform, complemented by conceptual simulations of irrigation flow paths. The initial phase comprises a comprehensive high-resolution time-series analysis of land use and land cover (LULC) dynamics to identify all potential LULCs influencing organic rice farming. Subsequently, irrigation flow path modeling is employed to estimate complex water dependencies. Ultimately, data fusion of LULC and irrigation analysis, combined with crop-specific pesticide data, results in an opportunity map highlighting suitable areas for organic rice farming. This interdisciplinary approach underscores the importance of integrating technological advancements with socio-economic considerations for a comprehensive and sustainable organic farming transition in the Mekong Delta.

How to cite: Kupfer, N., Montzka, C., and Quoc Vo, T.: Overcoming Barriers to Sustainable Rice Production: A Remote Sensing-Enabled Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1481,, 2024.