Badan Pusat Statistik (BPS-Statistics Indonesia) and the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP) along with the Food and Agriculture Organization (FAO) held an Innovative Workshop on the utilization of Earth Observation (EO) in the Mixed Method project to monitor rice crop growth. The event took place for five days from March 4-8, 2024, at the offices of the BPS and the Polytechnic STIS in Jakarta. Currently, the BPS calculates rice production data using two surveys, namely the Area Sampling Frame Survey (ASF) to identify the rice growth phases to predict harvest time, and the Crop-Cutting Survey to measure rice productivity. Data from the results of both surveys are used to calculate rice production. The opportunity of EO technology to capture surface information without visiting the field can be utilized to identify harvest times, optimizing data collection costs.

This workshop was attended by technical staff from BPS and STIS working on rice production estimates, the use of EO data, and machine learning as part of the One Rice Data project. In addition, meetings were also conducted with technical staff from other relevant ministries and agencies (such as the Ministry of National Development Planning (Bappenas), the National Research and Innovation Agency (BRIN), and the Ministry of Agriculture).

This workshop aims to support the development of a methodology development plan to facilitate the integration of Earth Observation and ASF data for producing official statistics on rice in Indonesia. Aligned with the focus goals of the Roadmap Mixed Method for the year 2024, the specific objectives of the technical support from UNESCAP and FAO include discussions on Phenology and Crop Area with a Remote Sensing-Based Approach. This involves conducting an in-depth study on data sources, methods, and processes for rice estimation in Indonesia, evaluating recent developments in rice estimation using Earth observation data in the country, reviewing data sources and model outputs, providing detailed insights into the latest global developments in crop estimation methods, reviewing the work, and developing a research plan outlining the steps for the development, testing, and improvement of the mixed-methods approach. This includes model development, benchmarking, ground truth data, data analysis, quality assurance, and strategic guidelines on infrastructure and field implementation.

Imam Machdi, Deputy of Methodology and Statistical Information at the BPS, stated that the utilization of earth observation data for the modernization of agricultural statistics provides significant opportunities to optimize cost-effective data collection. Collaborating with ESCAP and relevant stakeholders to build models utilizing Earth Observation is expected to uphold quality standards, ensuring rice production data as fast and accurate official statistics. However, it is crucial to emphasize that the implementation of new methods cannot happen instantly; assurance of the accuracy of these methods is required," said Imam Machdi.

UNESCAP and FAO, as partners in this event, highlight the importance of regional cooperation in addressing common challenges related to agricultural development and statistical approaches, including the application of modern algorithms such as Machine Learning for sustainable rice phenology classification.

This workshop not only provides in-depth insights into the mixed-method but also offers participants the opportunity to discuss and develop joint recommendations that can be implemented at the national and regional levels.