| Summary: | In remote sensing, the application determines the type of platform and scale used during air or space –borne data collection as the pixel size of the collected data varies depending on the sensor or platform used. Applications involving some cryospheric environments require the use of the microwave band of the electromagnetic spectrum, with snow water equivalent (SWE) studies making use of passively emitted microwave radiation.
A key issue in the use of passive microwave remotely sensed data is its spatial resolution, which ranges from 10 to 25 kilometres. The Climate Research Branch division of the Meteorological Service Canada is using passive microwave remote sensing as a means to monitor and obtain SWE values for Canada’s varying land-cover regions for use in climate change studies. Canada’s diverse landscape necessitated the creation of a snow water equivalent retrieval algorithm suite comprised of four different algorithms; all reflecting different vegetative covers. The spatial resolution of small scale remotely sensed data does provide a means for monitoring Canada’s large landmass, but it does, however, result in generalizations of land-cover, and in particular, vegetative structure, which is shown to influence both snow cover and algorithm performance.
The Climate Research Branch is currently developing its SWE algorithm for Canada’s boreal forest region. This thesis presents a means of successfully and easily collecting in situ remotely sensed data in the form of hemispherical photographs for gathering vegetative structure data to ground-truth remotely sensed data. This thesis also demonstrates that the Gap Light Analyzer software suite used for analyzing hemispherical photographs of mainly deciduous environments during the spring-fall months can be successfully applied towards cryospheric studies of predominantly coniferous environments.
|
|---|
