Share Email Print
cover

Proceedings Paper

An improved algorithm for extracting atmospheric motion vectors in cloud-free region from FY-2E thermal infrared imagery
Author(s): Zhenhui Wang; Qing Zhang; Min Tang; Hang Zhao; Lu Yang; Yizhe Zhan
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Atmospheric motion vectors (AMV) in cloud-free region can not be obtained with current operational cloud-motion tracking and water-vapor channel algorithms. The motivation of this study is to introduce a supplementary algorithm in order to work out the low-level AMVs in the clear area with FY-2E long wave, window (10.3~11.5, 11.6~12.8 μm) channel imagery. It has been shown that the weak signals indicating water vapor in “cloud-free region” can be extracted from FY-2E long wave infrared imagery and may be used as tracers for atmospheric motion vectors. The algorithm, named as Second Order difference method, has been raised in order to weaken the surface temperature interference to the weak signals of water vapor in “cloud-free region” by means of split window and temporal difference calculations. The results from theory analysis and cases study show that this method can make up for the wind data in regions lack of cloud but rich of water vapor and comparison between the wind vectors from this method and the NCEP reanalysis data shows a good consistency.

Paper Details

Date Published: 23 October 2014
PDF: 6 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 924416 (23 October 2014); doi: 10.1117/12.2067108
Show Author Affiliations
Zhenhui Wang, Nanjing Univ. of Information Science & Technology (China)
Qing Zhang, Nanjing Univ. of Information Science & Technology (China)
Min Tang, Nanjing Univ. of Information Science & Technology (China)
Hang Zhao, Nanjing Univ. of Information Science & Technology (China)
Lu Yang, Nanjing Univ. of Information Science & Technology (China)
Yizhe Zhan, Nanjing Univ. of Information Science & Technology (China)


Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top