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一个具有数据标准的用于北极后退解冻滑坡的协作式可扩展地理空间数据集。

A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards.

作者信息

Yang Yili, Rodenhizer Heidi, Rogers Brendan M, Dean Jacqueline, Singh Ridhima, Windholz Tiffany, Poston Amanda, Potter Stefano, Zolkos Scott, Fiske Greg, Watts Jennifer, Huang Lingcao, Witharana Chandi, Nitze Ingmar, Nesterova Nina, Barth Sophia, Grosse Guido, Lantz Trevor, Runge Alexandra, Lombardo Luigi, Nicu Ionut Cristi, Rubensdotter Lena, Makopoulou Eirini, Natali Susan

机构信息

Woodwell Climate Research Center, 149 Woods Hole Road, Falmouth, MA, 02540-1644, USA.

Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China.

出版信息

Sci Data. 2025 Jan 6;12(1):18. doi: 10.1038/s41597-025-04372-7.

Abstract

Arctic permafrost is undergoing rapid changes due to climate warming in high latitudes. Retrogressive thaw slumps (RTS) are one of the most abrupt and impactful thermal-denudation events that change Arctic landscapes and accelerate carbon feedbacks. Their spatial distribution remains poorly characterised due to time-intensive conventional mapping methods. While numerous RTS studies have published standalone digitisation datasets, the lack of a centralised, unified database has limited their utilisation, affecting the scale of RTS studies and the generalisation ability of deep learning models. To address this, we established the Arctic Retrogressive Thaw Slumps (ARTS) dataset containing 23,529 RTS-present and 20,434 RTS-absent digitisations from 20 standalone datasets. We also proposed a Data Curation Framework as a working standard for RTS digitisations. This dataset is designed to be comprehensive, accessible, contributable, and adaptable for various RTS-related studies. This dataset and its accompanying curation framework establish a foundation for enhanced collaboration in RTS research, facilitating standardised data sharing and comprehensive analyses across the Arctic permafrost research community.

摘要

由于高纬度地区的气候变暖,北极永久冻土正在经历快速变化。溯源解冻滑坡(RTS)是最突然且影响最大的热剥蚀事件之一,它改变了北极地貌并加速了碳反馈。由于传统测绘方法耗时,其空间分布特征仍不明确。虽然众多RTS研究已发表独立的数字化数据集,但缺乏集中统一的数据库限制了这些数据集的利用,影响了RTS研究的规模以及深度学习模型的泛化能力。为解决这一问题,我们建立了北极溯源解冻滑坡(ARTS)数据集,该数据集包含来自20个独立数据集的23529个存在RTS的数字化数据和20434个不存在RTS的数字化数据。我们还提出了一个数据管理框架,作为RTS数字化的工作标准。该数据集旨在全面、可访问、可贡献且适用于各种与RTS相关的研究。这个数据集及其配套的管理框架为加强RTS研究中的合作奠定了基础,促进了北极永久冻土研究社区内的标准化数据共享和全面分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af5f/11704310/73b61d637952/41597_2025_4372_Fig1_HTML.jpg

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