Mapping Rice Water Management and Methane Emissions in Ghana

An extensive rice field stretching into the distance with flooded paddies, ready for cultivation
Ryo Yoshitake, Unsplash

PI and co-PIs: Sherrie Wang (MIT); Soren Vines (Aya Data); Freddie Monk (Aya Data); Benjamin Adevu (Demeter Ghana); William Hunt (Demeter Ghana)

Funding amount: $350,000

Project overview: Rice cultivation, while essential for agriculture, comes with methane emissions that are often poorly quantified in global climate analyses. This project aims to better understand and quantify methane emissions from rice cultivation in Ghana, by using satellite imagery and machine learning alongside field surveys to assess rice flooding, a key factor influencing methane generation. The team will generate 10 meter-resolution maps of rice flooding and methane emissions for the entirety of Ghana, designed to inform methane models as well as interventions towards high-emissions hotspots.

Full abstract:

Click to expand

Rice cultivation is one of the most important agricultural sources of methane (CH4), but rice CH4 emissions remain poorly quantified on a global scale due to a scarcity of ground data. At the same time, rice consumption and production are increasing throughout Africa as the population grows, and efforts to increase rice yield while mitigating rice CH4 have been prioritized by governments throughout the continent. In this proposed study, we aim to fill data gaps in rice CH4 emissions by using satellite imagery and machine learning to map rice flooding in Ghana, as flooding is the main cultivation practice that influences CH4 generation during the rice growing season. To address the lack of ground labels on flooding that has previously prevented such research, we will conduct field surveys in four rice-growing regions throughout Ghana to gather geolocated data on the timing, duration, and intensity of flooding events. Our deliverables include all survey data, a high-resolution rice flooding map, and a proxy rice CH4 map, which will be released publicly upon project completion.

Agriculture & Food Computer Vision & Remote Sensing