Abstract: Data retrieval method based on physical meaning is proposed together with its application for prediction of linear precipitation zone with remote sensing satellite data and open data. The linear precipitation zone causes extremely severe storm and flood damage, landslide, and so on. Linear precipitation zone is formed in the case that the warm, moist air must continuously flow in, the force to lift this air up and it is often in collisions with mountain slopes or cold fronts, the atmospheric conditions are unstable, and there is a certain direction of wind above the sky. These conditions can be monitored by remote sensing satellite data. The proposed method is intended to attempt for prediction of the linear precipitation zone for disaster mitigation. There are water vapor data, cloud liquid data, cloud fraction data, and upper atmospheric wind data derived from the remote sensing satellite-based mission instruments. Through experiment in the case of the linear precipitation zone which was occurred in northern Kyushu, Japan in the begging of July 2020, a possibility to detect the linear precipitation zone was confirmed. Also, flooding damages and other disasters occurred in the northern Kyushu, in same time period caused by the detected linear precipitation zone is detected with Sentinel-1 of SAR data.

Kohei Arai, “Data Retrieval Method based on Physical Meaning and its Application for Prediction of Linear Precipitation Zone with Remote Sensing Satellite Data and Open Data” International Journal of Advanced Computer Science and Applications(IJACSA), 11(10), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111008

@article{Arai2020,
title = {Data Retrieval Method based on Physical Meaning and its Application for Prediction of Linear Precipitation Zone with Remote Sensing Satellite Data and Open Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111008},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111008},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {10},
author = {Kohei Arai}
}