Disaster Observation System
 

Using Earth Observation Satellite technology, Big Data, Artificial Intelligence, Machine Learning, Data Analytics, and Geographic Information system (GIS) to inspect disasters in each area such as village, sub-district, district and provincial levels together with Conventional surveys (Officers visit the area to inspect the damage), This will help to detect the disaster accurately, quickly, covering the actual damaged area and also use less budget. In addition, display of disaster-prone areas such as repeated floods or repeated droughts, this will help people to plan or deal with disasters effectively.   

 
Flood Detection System
 
Inspection of flooded areas by using SAR (Synthetic Aperture Radar) satellite images to process and showing information on flood-affected areas
Example: analysis of flood affected areas. Nakhon Sawan Province, November 4, 2022
It was found that there were 221,884 rai of flooded areas


District
Flood (Rai)
Chum Saeng
118,460.07
Tha Tako
48,467.50
Mueang Nakhon Sawan
21,098.38
Krok Phra
13,581.96
Phayuha Khiri
10,147.80
Kao Liao
6,374.33
Banphot Phisai
1,748.39
Lat Yao
734.52
Nong Bua
571.94
Mae Poen491.40
Phaisali
107.44
Chum Ta Bong53.66
Mae Wong46.69
 Total221,884.07

Drought Detection System

 

 Inspect the drought affected areas by using satellite data together with Artificial Intelligence (AI) and Machine Learning (ML)

Examples of drought-affected areas Nong Bua Sa-at Subdistrict, Bua Yai District, Nakhon Ratchasima Province
Drought analytics comparing 2019 and 2020

 

* Department of Disaster Prevention and Mitigation announced the condition of "drought" on August 5, 2019.

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