Publications

Laurin, GV; Francini, S; Penna, D; Zuecco, G; Chirici, G; Berman, E; Coops, NC; Castelli, G; Bresci, E; Preti, F; Valentini, R (2022). SnowWarp: An open science and open data tool for daily monitoring of snow dynamics. ENVIRONMENTAL MODELLING & SOFTWARE, 156, 105477.

Abstract
Snow cover is a key hydrological variable, critical to understanding water cycles and informing management decisions around resource extraction and recreational activities. Remote sensing open-access data and cloud -based computing platforms are two innovative tools for snow cover estimation. In this paper, we present SnowWarp, a processing framework that uses Google Earth Engine and the R programming languages to combine Landsat 30 m with MODIS 500 m satellite imagery and produce daily-30-m spatial resolution snow cover data anywhere globally. SnowWarp was applied in an alpine catchment in Northern Italy from 2000-2019 and validated using hy-drometeorological datasets. Strong correlations between snow cover and ground data were found with corre-lations in terms of R up to-0.84 for temperature,-0.17 for precipitation, 0.74 for snow depth, and-0.43 for streamflow. The SnowWarp tool is an open-source framework enabling users to map fine spatial and temporal dynamics of snow cover to the ecosystem and hydrological monitoring.

DOI:
10.1016/j.envsoft.2022.105477

ISSN:
1873-6726