Spatial Air Temperature Monitoring Using Microwave Links Data

Description in English
This project employs opportunistic sensing to comprehensively monitor air temperature across the Czech Republic, leveraging secondary data from microwave links. Machine learning techniques transform operational temperatures and additional parameters into ambient air temperatures. The primary aims are: i) To augment the existing meteorological network by integrating opportunistic data, thus filling in uncovered areas and enhancing the temperature measurement accuracy without further infrastructure investment. ii) To generate a detailed vertical air temperature profile over the Czech Republic. iii) To actively monitor urban heat islands for more effective climate change adaptation. This innovative methodology provides a rapid, cost-effective, and complex approach of thermal monitoring.

Key words in English
microwave link, temperature measurement, spatio-temporal, LPWAN weather station, machine learning model