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SnowWarp: An open science and open data tool for daily monitoring of snow dynamics
Environmental Modelling & Software ( IF 4.9 ) Pub Date : 2022-08-04 , DOI: 10.1016/j.envsoft.2022.105477
Gaia Vaglio Laurin, Saverio Francini, Daniele Penna, Giulia Zuecco, Gherardo Chirici, Ethan Berman, Nicholas C. Coops, Giulio Castelli, Elena Bresci, Federico Preti, Riccardo Valentini

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.



中文翻译:

SnowWarp:用于日常监测雪动态的开放科学和开放数据工具

积雪是一个关键的水文变量,对于了解水循环和为资源开采和娱乐活动的管理决策提供信息至关重要。遥感开放获取数据和基于云的计算平台是积雪估计的两个创新工具。在本文中,我们介绍了 SnowWarp,这是一个处理框架,它使用 Google Earth Engine 和 R 编程语言将 Landsat 30 m 与 MODIS 500 m 卫星图像相结合,并在全球任何地方生成每日 30 米空间分辨率的积雪数据。

SnowWarp 从 2000 年到 2019 年在意大利北部的一个高山流域应用,并使用水文气象数据集进行了验证。发现积雪和地面数据之间存在很强的相关性,温度的相关性 R 高达 -0.84,降水量为 -0.17,积雪深度为 0.74,流量为 -0.43。SnowWarp 工具是一个开源框架,使用户能够将积雪的精细时空动态映射到生态系统和水文监测。

更新日期:2022-08-08
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