Near real time monitoring of snow cover using webcam imagery

Environmental camera networks are growing in usage in different parts of the globe. Time series of webcam imagery from the camera networks are used in estimating snow cover properties. Fractional snow cover (FSC) and snow depth (SD) are two important parameters which can be estimated from the webcam imagery using image processing algorithms. Monitoring of snow cover from webcam imagery has the potential to be used in gap filling and validation of satellite derived products. It can also be used as a data source for snow monitoring in remote areas where manual measurements and in-situ sensor installation and maintenance are costly, especially under forest canopy which retrieval of signal from ground by satellites is a challenge. In this paper, we have used multiple webcams from MONIMET Camera Network in Finland and Finnish Meteorological Institute Image Processing Toolbox (FMIPROT) on the cloud to establish an automated processing chain which reports FSC and SD estimations in near real time, available in FMIPROT website. Image processing algorithms are implemented in the toolbox, the images from last year are also processed and the results are compared with ultrasonic in-situ measurements and values generated by visual inspections on images. In the website, estimations from the day-time images of the latest one month are visualized on interactive plots, along with time-lapse animations of images, with a latency of 3 hours.