SYSTEMATIC STUDY OF WEATHER VARIABLES FOR RAINFALL DETECTION

被引：0

作者：

Manandhar, Shilpa ^{[1
]}

Dev, Soumyabrata ^{[2
]}

Lee, Yee Hui ^{[1
]}

Winkler, Stefan ^{[3
]}

Meng, Yu Song ^{[4
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore

[2] Trinity Coll Dublin, Sch Comp Sci & Stat, ADAPT Ctr, Dublin, Ireland

[3] Univ Illinois, ADSC, Singapore, Singapore

[4] ASTAR, Natl Metrol Ctr, Singapore, Singapore

来源：

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年

关键词：

Precipitation; weather sensor; remote sensing; PWV; PRECIPITABLE WATER;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Numerous weather parameters affect the occurrence and amount of rainfall. Therefore, it is important to study these parameters and their interdependency. In this paper, different weather and time-related variables -relative humidity, solar radiation, temperature, dew point, day-of-year, and time-ofday are analyzed systematically using Principal Component Analysis (PCA). We found that four principal components explain a cumulative variance of 85%. The first two principal components are applied to distinguish rain and no-rain scenarios as well. We conclude that all 7 variables have similar contribution towards rainfall detection.

引用

页码：3027 / 3030

页数：4

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