Blob Extraction Algorithm in Detection of Convective Cells for Data Fusion

Authors

  • Piotr Szuster

DOI:

https://doi.org/10.26636/jtit.2019.135319

Keywords:

big data, blob extraction, data fusion, data integration, image processing, radar images

Abstract

Earth’s atmosphere is monitored by a multitude of sensors. It is the troposphere that is of crucial importance for human activity, as it is there that the weather phenomena take place. Weather observations are performed by surface sensors monitoring, inter alia, humidity, temperature and winds. In order to observe the developments taking place in the atmosphere, especially in the clouds, weather radars are commonly used. They monitor severe weather that is associated with storm clouds, cumulonimbuses, which create precipitation visible on radar screens. Therefore, radar images can be utilized to track storm clouds in a data fusion system. In this paper an algorithm is developed for the extraction of blobs (interesting areas in radar imagery) used within data fusion systems to track storm cells. The algorithm has been tested with the use of real data sourced from a weather radar network. 100% of convection cells were detected, with 90% of them being actual thunderstorms.

Downloads

Download data is not yet available.

Downloads

Published

2019-12-30

Issue

Section

ARTICLES FROM THIS ISSUE

How to Cite

[1]
P. Szuster, “Blob Extraction Algorithm in Detection of Convective Cells for Data Fusion”, JTIT, vol. 78, no. 4, pp. 65–73, Dec. 2019, doi: 10.26636/jtit.2019.135319.