Abstract
Snow cover area is dramatically decreasing across the Los Andes Mountains and the most relevant water reservoir under drought conditions. In this sense, monitoring of snow cover is key to analyzing the hydrologic balance in snowmelt-driven basins. MODIS Snow Cover daily products (MOD10A1 and MYD10A1) allow snow cover to be monitored at regular time intervals and in large areas, although the images often are affected by cloud cover. The main objective of this technical note is to evaluate the application of an algorithm to remove cloud cover in MODIS snow cover imagery in the Chilean Andes mountains. To this end, the northern region of Chile (Pulido river basin) during the period between December 2015 and December 2016 was selected. Results were validated against meteorological data from a ground station. The cloud removal algorithm allowed the overall cloud cover to be reduced from 26.56% to 7.69% in the study area and a snow cover mapping overall accuracy of 86.66% to be obtained. Finally, this work allows new cloud-free snow cover imagery to be produced for long term analysis and hydrologic models, reducing the lack of data and improving the daily regional snow mapping.
Highlights
Snow is an essential component of the climate system on the atmospheric processes, due to its high albedo, low thermal conductivity and considerable latent heat [1]
The cloud removal algorithm decreased the cloud cover in the Pulido river basin from 26.56% to 7.69% in the study area, where snow-covered regions are located over the higher parts of the Andes mountains
The MODIS snow cover product has good agreement with ground observations, with always over 90% accuracy when the sky is clear, mainly analyzed in studies of the Northern Hemisphere [34–38], but in the Chilean Andes, the mapping accuracy is more variable, due to the complex topography of the MODIS 8-day snow cover composites (MOD10A2) used in [23] in six basins of the central-southern region of Chile and achieved an overall accuracy of 81 to 98% with snow-covered area (SCA) compared with ground observations
Summary
Snow is an essential component of the climate system on the atmospheric processes, due to its high albedo, low thermal conductivity and considerable latent heat [1]. The snow is affected by climate change in most regions, decreasing the cover area due to positive feedback with the air temperature, especially during the spring and summer seasons [2,3]. In this sense, semiarid regions are highly sensitive to climate change in terms of the increase in air temperatures and the strong variability in distribution of precipitation, which forces snow to melt and affect the water balance, which in turn affects human activities [4]. Ground-based snow monitoring and its properties can be very problematic in mountainous areas due to the rugged topography and adverse weather conditions [6] For this reason, remote sensing is useful at providing information on snow cover areas in mountainous regions at regular intervals of time [7]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
