利用哨兵-2 图像对北半球 3702 个湖泊和 1028 个水库的冰层物候进行全球分析

IF 3.8 2区 工程技术 Q1 ENGINEERING, CIVIL
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引用次数: 0

摘要

由于现有的全球湖冰研究主要集中在大中型湖泊,而水库冰研究则局限于区域尺度,很少有冰物候学研究将不同规模的湖泊和水库结合起来。本研究旨在描述北半球 1 至 31,000 平方公里范围内 3702 个湖泊和 1028 个水库的结冰和破冰日期,并分析冰层物候日期与驱动因素之间的空间模式和关系。通过谷歌地球引擎平台,使用冰探测算法从哨兵-2 图像中获取了这些水体在 2019 年至 2023 年期间的冻结和破裂日期。通过将物候学日期与基于被动微波传感器观测数据的独立数据库进行比较,对该算法进行了验证,发现冻结和破裂日期的平均绝对误差为 18 天。这个新建立的冰物候数据库与水体的各种地理、形态和气候特征一起,被用来开发一个预测冰物候日期的随机森林模型。虽然预测模型的性能处于中等水平(冻结和破裂的平均绝对误差均为 12 天),但在某些高海拔地区遇到了挑战,多云和黑冰导致冻结日期推迟。在随机森林模型所包含的变量中,纬度和冰冻度日的累积被认为是冰冻物候期的主要驱动因素。尽管在全球范围内应用一种单一、直接的方法存在挑战,但这项研究建立了一个庞大而全面的湖泊和水库结冰和破冰日期数据库,可供社会各界进一步分析结冰模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A global analysis of ice phenology for 3702 lakes and 1028 reservoirs across the Northern Hemisphere using Sentinel-2 imagery

As existing global lake ice studies have predominantly focused on medium to large lakes, and reservoir ice studies have been limited to regional scales, very few studies of ice phenology have combined both lakes and reservoirs of different sizes. This study aims to characterize the freeze-up and break-up dates of 3702 lakes and 1028 reservoirs from 1 to 31,000 km2 across the Northern Hemisphere, and to analyze spatial patterns and relationships between ice phenological dates and driving factors. The freeze-up and break-up dates of these water bodies were retrieved from Sentinel-2 imagery using an ice detection algorithm through the Google Earth Engine platform from 2019 to 2023. The algorithm was verified by comparing phenology dates with an independent database based on observations from passive microwave sensors, with a mean absolute error of 18 days for both freeze-up and break-up dates. This newly established ice phenology database along with various geographic, morphometric, and climatic characteristics of the water bodies, was used to develop a random forest model for predicting ice phenology dates. While the predictive model performance is at a fair level (mean absolute error of 12 days for both freeze-up and break-up), challenges were encountered in certain high-elevation areas where cloudy conditions as well as black ice resulted in delayed freeze-up dates. Among the variables included in the random forest model, latitude and accumulation of freezing degree days were identified as the main drivers of ice phenology dates. Despite the challenges of applying a single, straightforward method on a global scale, this study has allowed the creation of a vast and comprehensive database of lake and reservoir freeze-up and break-up dates that can be used by the community to further analyze ice patterns.

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来源期刊
Cold Regions Science and Technology
Cold Regions Science and Technology 工程技术-地球科学综合
CiteScore
7.40
自引率
12.20%
发文量
209
审稿时长
4.9 months
期刊介绍: Cold Regions Science and Technology is an international journal dealing with the science and technical problems of cold environments in both the polar regions and more temperate locations. It includes fundamental aspects of cryospheric sciences which have applications for cold regions problems as well as engineering topics which relate to the cryosphere. Emphasis is given to applied science with broad coverage of the physical and mechanical aspects of ice (including glaciers and sea ice), snow and snow avalanches, ice-water systems, ice-bonded soils and permafrost. Relevant aspects of Earth science, materials science, offshore and river ice engineering are also of primary interest. These include icing of ships and structures as well as trafficability in cold environments. Technological advances for cold regions in research, development, and engineering practice are relevant to the journal. Theoretical papers must include a detailed discussion of the potential application of the theory to address cold regions problems. The journal serves a wide range of specialists, providing a medium for interdisciplinary communication and a convenient source of reference.
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