...
首页> 外文期刊>Geomorphology >InletTracker: An open-source Python toolkit for historic and near real-time monitoring of coastal inlets from Landsat and Sentinel-2
【24h】

InletTracker: An open-source Python toolkit for historic and near real-time monitoring of coastal inlets from Landsat and Sentinel-2

机译:InletTracker:用于历史悠久的Python工具包,用于来自Landsat和Sentinel-2的沿海入口的历史悠久和近实时监控

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker (https://github. com/VHeimhuber/InletTracker), a new tool that reconstructs the time-evolving state of dynamic coastal inlets over the last 30+ years from publicly available Landsat 5, 7 and 8 and Sentinel-2 satellite imagery. InletTracker is a Google Earth Engine enabled python toolkit that uses a novel least-cost pathfinding approach to trace inlets along and across the berm (i.e., barrier, bar), and then analyses the resulting transects to infer whether an inlet is open or closed. To evaluate the performance of InletTracker, we applied the tool at 12 intermittent coastal inlets with different maximum inlet widths (= 30-200 m), geomorphological setting and opening frequency located across Southeastern and Southwestern Australia. This exercise involved 6363 unique binary inlet state predictions (i.e., open vs. closed) that were validated against visually inferred inlet states (from the satellite imagery itself), on-ground observational records, and in-situ water levels from inside the inlets. InletTracker reproduced the visually inferred inlet states with an average accuracy across all sites of 89% for the combined Landsat and Sentinel-2 record (15-30 m resolution) and 94% for the Sentinel-2 record only (10 m resolution). Overall, we found good agreement between the predictions of the tool and the three independent validation datasets for all but the smallest sites. Our results demonstrate that InletTracker will enable coastal engineers, managers, and researchers to gain new insights into the dynamics and drivers of coastal inlets or similar shallow water land forms such as river mouths, tidal flats, floodplains, wetlands or delta channel networks. Further, the high spatial (i.e., 10 m) and temporal (i.e., 5-daily) resolution provided by Sentinel-2 makes InletTracker a viable option for near real-time monitoring of even relatively small inlets with a minimum channel width of around 10 m and frequent, short-duration, openings. (c) 2021 Elsevier B.V. All rights reserved.
机译:尽管其全球丰富和高生态和社会经济的意义,但沿海入口的动态往往在多层时间尺度上量化量很差。在这里,我们介绍了InletTracker(HTTPS:// Github。COM / VHEIMHUBER / INLETTRICKER),一个新工具,该工具在公共可用LANDSAT 5,7和8和Sentinel中重建了过去30多年的动态沿海入口的时间不断发展状态-2卫星图像。 InletTracker是一个Google地球发动机,使能Python Toolkit的Python Toolkit,它使用一种新颖的最小成本路径方法来沿着Berm(即,屏障,杆)沿着和跨越散列入口,然后分析所得到的横切来推断入口是否打开或关闭。为了评估InletTracker的性能,我们将工具应用于12个间歇沿海入口,其中包含不同的最大入口宽度(& = 30-200米),位于澳大利亚东南部和西南部的地貌设定和开放频率。该练习涉及6363个独特的二进制入口状态预测(即,开放与闭合),其针对视觉推断的入口状态(来自卫星图像本身),地面观测记录和原位水平从入口内部验证。 InletTracker在综合Landsat和Sentinel-2记录(15-30米分辨率)的所有站点(15-30米分辨率)和94%仅为94%(分辨率)时,在所有站点(15-30米分辨率)和94%)(10米的分辨率)的所有站点中的平均精度再现了视觉推断的入口状态。总体而言,我们在工具的预测和所有除可其所有网站上的三个独立验证数据集之间找到了良好的一致性。我们的结果表明,InletTracker将使沿海工程师,经理和研究人员能够获得新的洞察沿海入口或类似浅水土地形式的动态和司机,如河口,潮汐公寓,洪水平板,湿地或三角洲通道网络。此外,由Sentinel-2提供的高空间(即,10米)和时间(即,5-每日)分辨率使InletTracker成为近乎实时监控甚至相对较小的入口的可行选项,最小通道宽度约为10 M和频繁,短期,开口。 (c)2021 elestvier b.v.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号