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OAE uses drones & satellites for precise rainy season rice yield forecasts

OAE uses drones & satellites for precise rainy season rice yield forecasts

Prachachat•Economy•20d ago

Reader Briefing

The Office of Agricultural Economics is enhancing agricultural big data by integrating field surveys with drone and satellite imagery for more accurate rainy season rice yield predictions.

  • •The Office of Agricultural Economics (OAE) is using drones and Sentinel-1/Sentinel-2 satellite data to monitor rainy season rice across five growth stages.
  • •This initiative aims to improve the accuracy of its yield prediction models from an initial estimate of 70% to over 80% through collaboration with FAO and AIR CAS.
  • •The project, piloted in Phichit province with 40 sample plots, is an extension of work done in Suphan Buri, Ang Thong, Chai Nat, and Sing Buri.
  • •This multi-source data approach, combining field, drone, and satellite data, is expected to enhance the precision of crop monitoring and economic product yield assessment.

Overview

  • •In the 2025/2027 season, the OAE is implementing a project to enhance agricultural information and big data management.
  • •The OAE is using drone and satellite imagery (Sentinel-1, Sentinel-2) to monitor rainy season rice in 5 growth stages.
  • •A preliminary yield prediction accuracy of approximately 70% is expected, with a goal to exceed 80% through further integration.
  • •This initiative builds upon previous data collection efforts in the lower central regions of Thailand.
  • •The OAE conducted field surveys in Phichit province from April 20-30, 2026, collecting data from 40 sample plots.
  • •The OAE is collaborating with FAO and AIR CAS to jointly develop enhanced remote sensing-based yield prediction models.
  • •The OAE plans to extend this methodology to other key economic crops such as oil palm and cassava.
  • •OAE states that accurate and timely data is crucial for effective government planning and agricultural management.

Full article content is available on the original source.

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Source: Prachachat (Original)

Key Quotes

Peeraphan Korthong
"The key to modern yield forecasting is using multi-dimensional data to see the most realistic production picture in the field."
หัวใจสำคัญของการพยากรณ์ผลผลิตในยุคใหม่ คือการใช้ข้อมูลหลายมิติ เพื่อให้เห็นภาพการผลิตจริงในพื้นที่มากที่สุด
Peeraphan Korthong
"Accurate, precise, and timely data will enable the government to monitor production, assess yields, and plan agricultural management more effectively going forward."
ข้อมูลที่ถูกต้อง แม่นยำ และทันต่อสถานการณ์ จะช่วยให้ภาครัฐสามารถติดตามสถานการณ์การผลิต ประเมินผลผลิต และวางแผนบริหารจัดการสินค้าเกษตรได้อย่างมีประสิทธิภาพมากขึ้นในระยะต่อไป

Key Entities

Organization

Office of Agricultural Economics (OAE)(สศก.)ℹ️
The organization implementing advanced data technology for agricultural prediction.
Sentinel-1ℹ️
A satellite system providing Synthetic Aperture Radar (SAR) data used for crop monitoring.
Sentinel-2ℹ️
A satellite system providing Optical Sensor data used for vegetation analysis.
Food and Agriculture Organization of the United Nations (FAO)(FAO)ℹ️
An international organization collaborating with OAE on agricultural yield prediction models.
AIR CASℹ️
Aerospace Information Research Institute of the Chinese Academy of Sciences, collaborating with OAE.

Person

Peeraphan Korthong(นายพีรพันธ์ คอทอง)
Secretary-General of the Office of Agricultural Economics, discussing the integration of technology in agriculture.

Place

Phichit Province(จังหวัดพิจิตร)ℹ️
A province where the drone and satellite monitoring initiative for rainy season rice is being piloted.
Suphan Buri(สุพรรณบุรี)ℹ️
A province that served as a representative area for previous agricultural data collection efforts.
Ang Thong(อ่างทอง)ℹ️
A province that served as a representative area for previous agricultural data collection efforts.
Chai Nat(ชัยนาท)ℹ️
A province that served as a representative area for previous agricultural data collection efforts.
Sing Buri(สิงห์บุรี)ℹ️
A province that served as a representative area for previous agricultural data collection efforts.