利用Sentinel-1图像和卫星测高数据监测洞里萨湖水量的月变化

IF 2.4 Q2 GEOSCIENCES, MULTIDISCIPLINARY VIETNAM JOURNAL OF EARTH SCIENCES Pub Date : 2023-09-13 DOI:10.15625/2615-9783/18897
Binh Pham-Duc, Quan Tran Anh, Son Tong Si
{"title":"利用Sentinel-1图像和卫星测高数据监测洞里萨湖水量的月变化","authors":"Binh Pham-Duc, Quan Tran Anh, Son Tong Si","doi":"10.15625/2615-9783/18897","DOIUrl":null,"url":null,"abstract":"This work estimates the surface water volume variation of the Cambodian Tonle Sap Lake at a monthly scale from 2015-2022. To achieve this, radar Sentinel-1 imagery was processed using the Google Earth Engine platform to generate backscatter coefficient maps. The Otsu method was utilized to identify the optimal threshold to classify each backscatter coefficient map into water or non-water clusters. Additionally, altimetry data from three satellites (i.e., Sentinel-3, Jason-3, and Jason-CS/Sentinel-6) was processed to estimate Tonle Sap Lake’s water level variation using the AlTiS software. Surface water maps of the lake, derived from MODIS and clear-sky Sentinel-2 imagery, were used to validate the lake’s surface water extent time series, while in situ water level data collected at Prek Kdam station was used to validate the variation of the lake’s water height. Our results estimated that the lake’s open water area varies from 2200 to 6000 km2, while its water level ranges from 3.1 to 10.9 m. Combining the two time series, we estimated that Tonle Sap Lake’s water volume varies between approximately -7.2 and 9.4 km3 month-1, which shows high correlation with the variation of the water volume flowing through Chau Doc and Tan Chau stations (R = 0.9528 after removing the time lag). This study highlights the ability of satellite data for lake monitoring, which is very useful in remote areas where gauge stations are limited or unavailable. Future work aims to test the accuracy of the proposed methodology in other types of environments, particularly in mountainous regions of North Vietnam, where the terrain is very steep.","PeriodicalId":23639,"journal":{"name":"VIETNAM JOURNAL OF EARTH SCIENCES","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Monitoring monthly variation of Tonle Sap Lake water volume using Sentinel-1 imagery and satellite altimetry data\",\"authors\":\"Binh Pham-Duc, Quan Tran Anh, Son Tong Si\",\"doi\":\"10.15625/2615-9783/18897\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work estimates the surface water volume variation of the Cambodian Tonle Sap Lake at a monthly scale from 2015-2022. To achieve this, radar Sentinel-1 imagery was processed using the Google Earth Engine platform to generate backscatter coefficient maps. The Otsu method was utilized to identify the optimal threshold to classify each backscatter coefficient map into water or non-water clusters. Additionally, altimetry data from three satellites (i.e., Sentinel-3, Jason-3, and Jason-CS/Sentinel-6) was processed to estimate Tonle Sap Lake’s water level variation using the AlTiS software. Surface water maps of the lake, derived from MODIS and clear-sky Sentinel-2 imagery, were used to validate the lake’s surface water extent time series, while in situ water level data collected at Prek Kdam station was used to validate the variation of the lake’s water height. Our results estimated that the lake’s open water area varies from 2200 to 6000 km2, while its water level ranges from 3.1 to 10.9 m. Combining the two time series, we estimated that Tonle Sap Lake’s water volume varies between approximately -7.2 and 9.4 km3 month-1, which shows high correlation with the variation of the water volume flowing through Chau Doc and Tan Chau stations (R = 0.9528 after removing the time lag). This study highlights the ability of satellite data for lake monitoring, which is very useful in remote areas where gauge stations are limited or unavailable. Future work aims to test the accuracy of the proposed methodology in other types of environments, particularly in mountainous regions of North Vietnam, where the terrain is very steep.\",\"PeriodicalId\":23639,\"journal\":{\"name\":\"VIETNAM JOURNAL OF EARTH SCIENCES\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VIETNAM JOURNAL OF EARTH SCIENCES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15625/2615-9783/18897\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VIETNAM JOURNAL OF EARTH SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15625/2615-9783/18897","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

本研究估算了2015-2022年柬埔寨洞里萨湖地表水的月尺度变化。为了实现这一目标,雷达Sentinel-1图像使用谷歌地球引擎平台进行处理,生成后向散射系数图。利用Otsu方法确定最佳阈值,将每个后向散射系数图划分为水或非水簇。此外,利用AlTiS软件对三颗卫星(即Sentinel-3、Jason-3和Jason-CS/Sentinel-6)的测高数据进行处理,估算洞里萨湖的水位变化。利用MODIS和晴空Sentinel-2影像获取的湖泊地表水图,验证了湖泊的地表水范围时间序列,同时利用Prek Kdam站收集的原位水位数据验证了湖泊水位高度的变化。结果表明,湖泊开放水域面积在2200 ~ 6000 km2之间,水位在3.1 ~ 10.9 m之间。结合这两个时间序列,我们估计洞里沙湖的水量在-7.2 ~ 9.4 km3之间变化,这与通过Chau Doc和Tan Chau站的水量变化具有高度的相关性(去除滞后后R = 0.9528)。这项研究突出了卫星数据监测湖泊的能力,这在测量站有限或没有测量站的偏远地区非常有用。未来的工作旨在测试所提出的方法在其他类型环境中的准确性,特别是在地形非常陡峭的越南北部山区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Monitoring monthly variation of Tonle Sap Lake water volume using Sentinel-1 imagery and satellite altimetry data
This work estimates the surface water volume variation of the Cambodian Tonle Sap Lake at a monthly scale from 2015-2022. To achieve this, radar Sentinel-1 imagery was processed using the Google Earth Engine platform to generate backscatter coefficient maps. The Otsu method was utilized to identify the optimal threshold to classify each backscatter coefficient map into water or non-water clusters. Additionally, altimetry data from three satellites (i.e., Sentinel-3, Jason-3, and Jason-CS/Sentinel-6) was processed to estimate Tonle Sap Lake’s water level variation using the AlTiS software. Surface water maps of the lake, derived from MODIS and clear-sky Sentinel-2 imagery, were used to validate the lake’s surface water extent time series, while in situ water level data collected at Prek Kdam station was used to validate the variation of the lake’s water height. Our results estimated that the lake’s open water area varies from 2200 to 6000 km2, while its water level ranges from 3.1 to 10.9 m. Combining the two time series, we estimated that Tonle Sap Lake’s water volume varies between approximately -7.2 and 9.4 km3 month-1, which shows high correlation with the variation of the water volume flowing through Chau Doc and Tan Chau stations (R = 0.9528 after removing the time lag). This study highlights the ability of satellite data for lake monitoring, which is very useful in remote areas where gauge stations are limited or unavailable. Future work aims to test the accuracy of the proposed methodology in other types of environments, particularly in mountainous regions of North Vietnam, where the terrain is very steep.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
VIETNAM JOURNAL OF EARTH SCIENCES
VIETNAM JOURNAL OF EARTH SCIENCES GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
3.60
自引率
20.00%
发文量
0
期刊最新文献
Hybrid approach for permeability prediction in porous media: combining FFT simulations with machine learning Identification of the active faults and seismotectonic zonation of Laos territory Multi-step-ahead prediction of water levels using machine learning: A comparative analysis in the Vietnamese Mekong Delta Temporal and spatial variation in water quality in the Son La hydropower Reservoir, Northwestern Vietnam Application of hybrid modeling to predict California bearing ratio of soil
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1