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Center of Agricultural Information (CAI) by Division of Geo-Informatics set a practical training in the topic “Interpret and Classify Agricultural Areas by using Geo-Informatics in 2024
Center of Agricultural Information (CAI) by Division of Geo-Informatics set a practical training in the topic “Interpret and Classify Agricultural Areas by using Geo-Informatics in 2024 between CAI and Regional Office of Agricultural Economics”. Director of CAI is honored for opening this practical training during 25-27 March 2024 at Sri Sappakrit Training Room, Vision Building, Office of Agricultural Economics, Bangkok. The number of participants was 23 people. Finally, the director of Division of Geo-Informatics declares on the practical training.
The main objectives of this practical training are enhancing the knowledge on Ge0-Informatics technology, which are advantages on the agricultural interpretation. Consequently, participants can utilize this knowledge on any Geo-Informatics applications, especially processing agricultural data in the provincial level and adapt to the importance and role of areas. The subject of this practical training is consisted of theory of Geo-Informatics and trends, processing of satellite data downloading (involved the pre-processing), agricultural classification, overall accuracy, procedures on agricultural classification, geo-spatial metadata, and artificial intelligence (AI).
In addition, this practical training gains the assistance from Geography and Geo-Informatic, Thammasart University to propose Dr. Sitthisak Moukomla for a lecturer in topic “Adopting Google Earth Engine (GEE) for agricultural”. The GEE provides important data for analysis such as precipitation, soil moisture, satellite imagery, vegetation index (VI), crop stresses, and AI (with the example of Random Forest (RF). This section is enhancing the opportunities for plenty of data especially in the Google Earth Engine platform. At the end, the hosts and participants have a discussion on the problems/obstacles on our workings in the previous year and solve these problems together. This practical training was a success and achieve our objectives.
The main objectives of this practical training are enhancing the knowledge on Ge0-Informatics technology, which are advantages on the agricultural interpretation. Consequently, participants can utilize this knowledge on any Geo-Informatics applications, especially processing agricultural data in the provincial level and adapt to the importance and role of areas. The subject of this practical training is consisted of theory of Geo-Informatics and trends, processing of satellite data downloading (involved the pre-processing), agricultural classification, overall accuracy, procedures on agricultural classification, geo-spatial metadata, and artificial intelligence (AI).
In addition, this practical training gains the assistance from Geography and Geo-Informatic, Thammasart University to propose Dr. Sitthisak Moukomla for a lecturer in topic “Adopting Google Earth Engine (GEE) for agricultural”. The GEE provides important data for analysis such as precipitation, soil moisture, satellite imagery, vegetation index (VI), crop stresses, and AI (with the example of Random Forest (RF). This section is enhancing the opportunities for plenty of data especially in the Google Earth Engine platform. At the end, the hosts and participants have a discussion on the problems/obstacles on our workings in the previous year and solve these problems together. This practical training was a success and achieve our objectives.
