SnowWarp: An open science and open data tool for daily monitoring of snow dynamics. (October 2022)

• Record Type: Journal Article
• Authors: Laurin, Gaia Vaglio; Francini, Saverio; Penna, Daniele; Zuecco, Giulia; Chirici, Gherardo; Berman, Ethan; Coops, Nicholas C.; Castelli, Giulio; Bresci, Elena; Preti, Federico; Valentini, Riccardo
• Is Part Of: Environmental modelling & software. Volume 156(2022)
• Publication Date: 2022-10
• Subjects: Snow cover -- Landsat -- MODIS -- Google earth engine -- JavaScript -- R; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105477
• Languages: English
• ISSNs: 1364-8152

Abstract

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 hydrometeorological datasets. Strong correlations between snow cover and ground data were found with correlations 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. Highlights: The new open-source SnowWarp tool, utilizing Google Earth Engine and R is presented. Daily snow cover data at 30 m spatial resolution can be calculated globally. SnowWarp exploits MODIS and Landsat remote sensing data and implements a dynamic time warping algorithm. SnowWarp products were generated and tested in an Alpine area in Northern Italy. Snow cover dynamics were related to different hydro-meteorological variables.