Visual Analytics of Multi-sensorWeather Information. Georeferenciation of Doppler Weather Radar and Weather Stations
Abstract
This work presents a geovisual tool which integrates and georeferences data coming from some of the weather instruments installed in the Basque Country: a Doppler weather radar and the weather station network composed of around 100 multi-sensors stations (temperature, precipitation, wind...). The visualization of the raw data coming from the weather radar is based on the generation of a set of 3D textured concentric cones (one per elevation scan). The resulting 3D model is then integrated in the 3D digital terrain of the Basque Country. For the weather stations, we have provided a Kriging based interpolation method to produce textures from the scalar data measured at the weather stations. These textures are then mapped in the same 3D digital terrain as before. The integrated visualization of the weather information enhances the understanding of the data. To illustrate the proposed methods a use case is provided: matching the precipitation measured at ground level with the radar scans.
BIB_text
author = {Aitor Moreno, Andoni Galdós, Andoni Mujika, Álvaro Segura},
title = {Visual Analytics of Multi-sensorWeather Information. Georeferenciation of Doppler Weather Radar and Weather Stations},
pages = {329-336},
volume = {1},
keywds = {
Weather Stations, Geovisual Analytics, Doppler Weather Radar, Scalar Fields
}
abstract = {
This work presents a geovisual tool which integrates and georeferences data coming from some of the weather instruments installed in the Basque Country: a Doppler weather radar and the weather station network composed of around 100 multi-sensors stations (temperature, precipitation, wind...). The visualization of the raw data coming from the weather radar is based on the generation of a set of 3D textured concentric cones (one per elevation scan). The resulting 3D model is then integrated in the 3D digital terrain of the Basque Country. For the weather stations, we have provided a Kriging based interpolation method to produce textures from the scalar data measured at the weather stations. These textures are then mapped in the same 3D digital terrain as before. The integrated visualization of the weather information enhances the understanding of the data. To illustrate the proposed methods a use case is provided: matching the precipitation measured at ground level with the radar scans.
}
isbn = {978-989-758-005-5},
isi = {1},
date = {2014-01-08},
year = {2014},
}
