By Office of Communications and Public Affairs
Two recent studies from the Water Engineering and Management (WEM) Program at the Faculty of Civil and Environmental Engineering (FCEE) at Asian Institute of Technology (AIT) highlight how digital tools are helping address pressing challenges in agriculture and environmental management across Southeast Asia.
The first study, “Digital Agriculture Adoption and Pathways Across ASEAN Food Value Chains,” examines how digital technologies are being adopted across agricultural production and food value chains in ASEAN. It forms part of a regional assessment conducted with the Economic Research Institute for ASEAN and East Asia (ERIA) on digitalization in agriculture and food systems across ASEAN countries.
The second study, “Satellite Data Fusion and Machine Learning for Water Quality Monitoring in the Lower Chao Phraya River,” introduces a satellite-based approach for monitoring water quality in Thailand’s Lower Chao Phraya River. The study was led by doctoral researcher Aye Khaing Mon under the supervision of Dr. Mohana Sundaram Shanmugam, with contributions from Prof. Sangam Shrestha, Dr. Natthachet Tangdamrongsub, and Dr. Sushil Kumar Himanshu, all from AIT.
Together, these studies highlight the growing potential of data-driven solutions to strengthen food systems and improve natural resource management across the region.
The first study, conducted across eight ASEAN countries, finds that digital agriculture is gaining traction, particularly through practical and accessible tools such as advisory applications, digital payments, and online marketplaces. However, adoption of more advanced technologies, including artificial intelligence, automation, and precision agriculture, remains limited, especially among smallholder farmers. Stakeholders across the region are primarily seeking digital solutions that reduce production costs, improve productivity, and address labor shortages. At the same time, adoption continues to be constrained by high investment costs, limited digital skills, inadequate rural infrastructure, and fragmented policy support. The findings highlight the need for stronger financing mechanisms, targeted capacity building, and closer collaboration between governments, agricultural support systems, and technology providers.
The second study focuses on the Lower Chao Phraya River and presents a satellite data fusion framework combined with a machine learning model to improve water quality monitoring. By integrating data from multiple satellite missions, the approach enhances both spatial detail and temporal frequency, significantly increasing the availability of usable monitoring data. The proposed model demonstrates improved accuracy and reduced prediction bias, particularly in complex urban river environments where conventional methods often face limitations. This enables more reliable monitoring of key indicators such as water extent, sediment dynamics, and chlorophyll-related water quality conditions. While wet-season observation remains challenging due to cloud cover, the framework offers a scalable and transferable solution for river monitoring in Thailand and across the region, particularly where ground-based data are limited.
Dr. Mohana Shanmugam, Assistant Professor, WEM, said, “Across Southeast Asia, the gap between the potential of digital tools and their actual accessibility for communities remains significant. Our study on digital agriculture, conducted with ERIA, shows that while practical tools such as advisory applications and digital payments are gaining traction, the adoption of more advanced technologies remains limited among smallholder farmers, constrained by high costs, limited digital skills, and inadequate rural infrastructure.
He added, “Our river monitoring research addresses a parallel challenge. By fusing Landsat and Sentinel-2 satellite data with machine learning, we increased usable water quality observations by up to 63 percent in a single year compared with Sentinel-2 alone. Both studies deliver concrete, actionable evidence that governments, development agencies, and agricultural support systems can translate directly into policy and practice. This reflects how AIT’s WEM Program is advancing practical, scalable solutions for food security and environmental resilience across the region.”
