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Reducing Rice Methane Emissions in Vietnam and Indonesia using EO

The GDA Agriculture activity collaborated with the World Bank to develop Earth Observation (EO) based solutions for monitoring methane emissions from rice cultivation, supporting climate-smart agriculture and sustainable mitigation strategies.

Description

Under the GDA Agriculture activity, the implementing partner  company unique collaborated with the World Bank to develop Earth Observation (EO) based products aimed at estimating methane emissions from rice cultivation in Indonesia and then Vietnam. These activities align with the Strategic Irrigation Modernization and Urgent Rehabilitation Project, a World Bank funded initiative that focuses on improving irrigation infrastructure, water resource management, and agricultural productivity. The project also supports the forthcoming Multiphase Programmatic Approach (MPA) for Low-Methane Agricultural Transformation in East Asia, expected by 2025, which aims to reduce methane emissions from farming through innovative practices and climate-smart interventions.

The EO services developed were tailored to provide critical agricultural and environmental indicators such as rice paddy inundation status, irrigation practices, and methane emission estimates using Sentinel-1 and PALSAR-2 radar data.  In Indonesia, backscatter analysis was completed to classify inundation status of rice fields, distinguishing different iirgation schemes that impact methane emissions. Modelled methane emission estimates based on inundation classification was also completed for Indonesia. Similar services were deployed in Vietnam, where backscatter analysis and methane emission calculations were refined to provide region-specific assessments.

The project highlighted EO’s potential in advancing agricultural methane reduction strategies. EO technologies can support the monitoring of alternate wetting and drying (AWD) irrigation methods, ensuring that mitigation interventions are effectively implemented across diverse climatic and agronomic contexts.

 

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