Authors: Gernot Paulus*, School of Geoinformation, Carinthia University of Applied Sciences, Thomas Winkler, Spatial Information Management, Carinthia University of Applied Sciences, Robert V. Rohli, Department of Oceanography & Coastal Sciences, Louisiana State University
Topics: Environmental Science, Remote Sensing, Spatial Analysis & Modeling
Keywords: Unmmanned Aerial Systems, 3D weather phenomena, meteorology
Session Type: Paper
Start / End Time: 1:10 PM / 2:50 PM
Room: Harding, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Ongoing trends of mature Unmanned Aerial Systems (UAS) and increasingly miniaturized platforms and environmental sensors nowadays promote many new areas of application in the context of atmospheric boundary layer (ABL) research. One of the main goals of this research is to develop a prototype application of a flight planner for 3D meteorological data capture missions that offers UAS operators and scientists an easy and efficient way to design sophisticated and repeatable flight plans. We will present a concept for spatio-temporal sampling schemes for the UAS-based data capture of weather data within the boundary layer using a new, light weight meteorological sensor named “weather frog”. This new sensor has been integrated into a fixed wing UAS system. To demonstrate the feasibility of the newly developed prototype, several UAS-based meteorological missions were planned and executed. During the course of these missions, atmospheric properties such as absolute temperature, humidity, estimated wind speed, and estimated wind direction were recorded. Furthermore, a first proof-of-concept implementation of a conceptual workflow for three-dimensional spatio-temporal change detection demonstrates its practicability by visualizing changes in the atmosphere, occurring between different flights over the same area at different times. Finally, a first evaluation of the observations collected by the UAS provides a first assessment of the expected accuracy of the UAS-based sampling approach for dynamic weather phenomena. UAS-based weather data have been compared and evaluated based on SODAR/RASS reference data.