高分辨率融化季节反照率的检索及其对喀喇昆仑异常的影响

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2024-09-22 DOI:10.1016/j.rse.2024.114438
Fuming Xie , Shiyin Liu , Yu Zhu , Xinyi Qing , Shucheng Tan , Yongpeng Gao , Miaomiao Qi , Ying Yi , Hui Ye , Muhammad Mannan Afzal , Xianhe Zhang , Jun Zhou
{"title":"高分辨率融化季节反照率的检索及其对喀喇昆仑异常的影响","authors":"Fuming Xie ,&nbsp;Shiyin Liu ,&nbsp;Yu Zhu ,&nbsp;Xinyi Qing ,&nbsp;Shucheng Tan ,&nbsp;Yongpeng Gao ,&nbsp;Miaomiao Qi ,&nbsp;Ying Yi ,&nbsp;Hui Ye ,&nbsp;Muhammad Mannan Afzal ,&nbsp;Xianhe Zhang ,&nbsp;Jun Zhou","doi":"10.1016/j.rse.2024.114438","DOIUrl":null,"url":null,"abstract":"<div><div>Glacial responses to climate change exhibit considerable heterogeneity. Although global glaciers are generally thinning and retreat, glaciers in the Karakoram region are distinct in their surging or advancing, exhibiting nearly zero or positive mass balance—a phenomenon known as the Karakoram Anomaly. This anomaly has sparked significant scientific interest, prompting extensive research into glacier anomalies. However, the dynamics of the Karakoram anomaly, particularly its evolution and persistence, remain insufficiently explored. In this study, we employed Landsat reflectance data and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 albedo products to developed high-resolution albedo retrieval models using two machine learning (ML) regressions––random forest regression (RFR) and back-propagation neural network regression (BPNNR). The optimal BPNNR model (Pearson correlation coefficient [<em>r</em>] = 0.77–0.97, unbiased root mean squared error [<em>ubRMSE</em>] = 0.056–0.077, <em>RMSE</em> = 0.055–0.168, <em>Bias =</em> −0.149 ∼ −0.001) was implemented on the Google Earth Engine cloud-based platform to estimate summer albedo at a 30-m resolution for the Karakoram region from 1990 to 2021. Validation against in-situ albedo measurements on three glaciers (Batura, Mulungutti and Yala Glacier) demonstrated that the model achieved an average <em>ubRMSE</em> of 0.069 (<em>p</em> &lt; 0.001), with <em>RMSE</em> and <em>ubRMSE</em> improvements of 0.027 compared to MODIS albedo products. The high-resolution data was then used to identify firn/snow extents using a 0.37 threshold, facilitating the extraction of long-term firn-line altitudes (FLA) to indicate the glacier dynamics. Our findings revealed that a consistent decline in summer albedo across the Karakoram over the past three decades, signifying a darkening of glacier surfaces that increased solar radiation absorption and intensified melting. The reduction in albedo showed spatial heterogeneity, with slower reductions in the western and central Karakoram (−0.0005–0.0005 yr<sup>−1</sup>) compared to the eastern Karakoram (−0.006 ∼ −0.01 yr<sup>−1</sup>). Notably, surge- or advance-type glaciers, avalanche-fed glaciers and debris-covered glaciers exhibited slower albedo reduction rates, which decreased further with increasing glacier size. Additionally, albedo reduction accelerated with altitude, peaking near the equilibrium-line altitude. Fluctuations in the albedo-derived FLAs suggest a transition in the dynamics of Karakoram glaciers from anomalous behavior to retreat. Most glaciers exhibited anomalous behavior from 1995 to 2010, peaking in 2003, but they have shown signs of retreat since the 2010s, marking the end of the Karakoram anomaly. These insights deepen our understanding of the Karakoram anomaly and provide a theoretical basis for assessing the effect of glacier anomaly to retreat dynamics on the water resources and adaptation strategies for the Indus and Tarim Rivers.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"315 ","pages":"Article 114438"},"PeriodicalIF":11.1000,"publicationDate":"2024-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Retrieval of high-resolution melting-season albedo and its implications for the Karakoram Anomaly\",\"authors\":\"Fuming Xie ,&nbsp;Shiyin Liu ,&nbsp;Yu Zhu ,&nbsp;Xinyi Qing ,&nbsp;Shucheng Tan ,&nbsp;Yongpeng Gao ,&nbsp;Miaomiao Qi ,&nbsp;Ying Yi ,&nbsp;Hui Ye ,&nbsp;Muhammad Mannan Afzal ,&nbsp;Xianhe Zhang ,&nbsp;Jun Zhou\",\"doi\":\"10.1016/j.rse.2024.114438\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Glacial responses to climate change exhibit considerable heterogeneity. Although global glaciers are generally thinning and retreat, glaciers in the Karakoram region are distinct in their surging or advancing, exhibiting nearly zero or positive mass balance—a phenomenon known as the Karakoram Anomaly. This anomaly has sparked significant scientific interest, prompting extensive research into glacier anomalies. However, the dynamics of the Karakoram anomaly, particularly its evolution and persistence, remain insufficiently explored. In this study, we employed Landsat reflectance data and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 albedo products to developed high-resolution albedo retrieval models using two machine learning (ML) regressions––random forest regression (RFR) and back-propagation neural network regression (BPNNR). The optimal BPNNR model (Pearson correlation coefficient [<em>r</em>] = 0.77–0.97, unbiased root mean squared error [<em>ubRMSE</em>] = 0.056–0.077, <em>RMSE</em> = 0.055–0.168, <em>Bias =</em> −0.149 ∼ −0.001) was implemented on the Google Earth Engine cloud-based platform to estimate summer albedo at a 30-m resolution for the Karakoram region from 1990 to 2021. Validation against in-situ albedo measurements on three glaciers (Batura, Mulungutti and Yala Glacier) demonstrated that the model achieved an average <em>ubRMSE</em> of 0.069 (<em>p</em> &lt; 0.001), with <em>RMSE</em> and <em>ubRMSE</em> improvements of 0.027 compared to MODIS albedo products. The high-resolution data was then used to identify firn/snow extents using a 0.37 threshold, facilitating the extraction of long-term firn-line altitudes (FLA) to indicate the glacier dynamics. Our findings revealed that a consistent decline in summer albedo across the Karakoram over the past three decades, signifying a darkening of glacier surfaces that increased solar radiation absorption and intensified melting. The reduction in albedo showed spatial heterogeneity, with slower reductions in the western and central Karakoram (−0.0005–0.0005 yr<sup>−1</sup>) compared to the eastern Karakoram (−0.006 ∼ −0.01 yr<sup>−1</sup>). Notably, surge- or advance-type glaciers, avalanche-fed glaciers and debris-covered glaciers exhibited slower albedo reduction rates, which decreased further with increasing glacier size. Additionally, albedo reduction accelerated with altitude, peaking near the equilibrium-line altitude. Fluctuations in the albedo-derived FLAs suggest a transition in the dynamics of Karakoram glaciers from anomalous behavior to retreat. Most glaciers exhibited anomalous behavior from 1995 to 2010, peaking in 2003, but they have shown signs of retreat since the 2010s, marking the end of the Karakoram anomaly. These insights deepen our understanding of the Karakoram anomaly and provide a theoretical basis for assessing the effect of glacier anomaly to retreat dynamics on the water resources and adaptation strategies for the Indus and Tarim Rivers.</div></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"315 \",\"pages\":\"Article 114438\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2024-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425724004644\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425724004644","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

冰川对气候变化的反应表现出相当大的差异性。虽然全球冰川一般都在变薄和后退,但喀喇昆仑地区的冰川却表现出与众不同的涌动或前进,其质量平衡几乎为零或正值--这种现象被称为喀喇昆仑异常现象(Karakoram Anomaly)。这种异常现象引发了科学界的极大兴趣,促使人们对冰川异常现象进行广泛研究。然而,对喀喇昆仑异常现象的动态变化,特别是其演变和持续性的研究仍然不足。在这项研究中,我们利用大地遥感卫星(Landsat)反射率数据和中分辨率成像分光仪(MODIS)MCD43A3反照率产品,采用随机森林回归(RFR)和反向传播神经网络回归(BPNNR)两种机器学习(ML)回归方法建立了高分辨率反照率检索模型。最佳BPNNR模型(皮尔逊相关系数[r] = 0.77-0.97, 无偏均方根误差[ubRMSE] = 0.056-0.077, RMSE = 0.055-0.168, 偏差 = -0.149 ∼ -0.001)在谷歌地球引擎云平台上实现,以30米分辨率估算1990年至2021年喀喇昆仑地区的夏季反照率。根据对三座冰川(巴图拉冰川、穆隆古提冰川和雅拉冰川)的原地反照率测量结果进行的验证表明,与 MODIS 反照率产品相比,该模型实现了 0.069 (p < 0.001)的平均 ubRMSE 值,RMSE 值和 ubRMSE 值提高了 0.027。然后,利用高分辨率数据,以 0.37 为阈值识别杉林/积雪范围,从而便于提取长期杉林线高度(FLA)来显示冰川动态。我们的研究结果表明,在过去的三十年里,整个喀喇昆仑山的夏季反照率持续下降,这表明冰川表面变暗,增加了对太阳辐射的吸收,加剧了冰川融化。反照率的降低表现出空间异质性,与喀喇昆仑山东部(-0.006 ∼ -0.01年-1)相比,喀喇昆仑山西部和中部的反照率降低速度较慢(-0.0005-0.0005年-1)。值得注意的是,涌升型或前进型冰川、雪崩作用冰川和碎屑覆盖冰川的反照率降低速度较慢,随着冰川面积的增加,反照率进一步降低。此外,反照率降低速度随着海拔高度的增加而加快,在平衡线海拔高度附近达到顶峰。反照率推导出的FLA的波动表明,喀喇昆仑冰川的动态变化正从异常行为向后退过渡。大多数冰川在 1995 年至 2010 年期间表现出异常行为,并在 2003 年达到顶峰,但自 2010 年代以来出现了后退迹象,标志着喀喇昆仑异常现象的结束。这些见解加深了我们对喀喇昆仑异常现象的理解,为评估冰川异常退缩动态对印度河和塔里木河水资源的影响以及适应战略提供了理论依据。
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
Retrieval of high-resolution melting-season albedo and its implications for the Karakoram Anomaly
Glacial responses to climate change exhibit considerable heterogeneity. Although global glaciers are generally thinning and retreat, glaciers in the Karakoram region are distinct in their surging or advancing, exhibiting nearly zero or positive mass balance—a phenomenon known as the Karakoram Anomaly. This anomaly has sparked significant scientific interest, prompting extensive research into glacier anomalies. However, the dynamics of the Karakoram anomaly, particularly its evolution and persistence, remain insufficiently explored. In this study, we employed Landsat reflectance data and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 albedo products to developed high-resolution albedo retrieval models using two machine learning (ML) regressions––random forest regression (RFR) and back-propagation neural network regression (BPNNR). The optimal BPNNR model (Pearson correlation coefficient [r] = 0.77–0.97, unbiased root mean squared error [ubRMSE] = 0.056–0.077, RMSE = 0.055–0.168, Bias = −0.149 ∼ −0.001) was implemented on the Google Earth Engine cloud-based platform to estimate summer albedo at a 30-m resolution for the Karakoram region from 1990 to 2021. Validation against in-situ albedo measurements on three glaciers (Batura, Mulungutti and Yala Glacier) demonstrated that the model achieved an average ubRMSE of 0.069 (p < 0.001), with RMSE and ubRMSE improvements of 0.027 compared to MODIS albedo products. The high-resolution data was then used to identify firn/snow extents using a 0.37 threshold, facilitating the extraction of long-term firn-line altitudes (FLA) to indicate the glacier dynamics. Our findings revealed that a consistent decline in summer albedo across the Karakoram over the past three decades, signifying a darkening of glacier surfaces that increased solar radiation absorption and intensified melting. The reduction in albedo showed spatial heterogeneity, with slower reductions in the western and central Karakoram (−0.0005–0.0005 yr−1) compared to the eastern Karakoram (−0.006 ∼ −0.01 yr−1). Notably, surge- or advance-type glaciers, avalanche-fed glaciers and debris-covered glaciers exhibited slower albedo reduction rates, which decreased further with increasing glacier size. Additionally, albedo reduction accelerated with altitude, peaking near the equilibrium-line altitude. Fluctuations in the albedo-derived FLAs suggest a transition in the dynamics of Karakoram glaciers from anomalous behavior to retreat. Most glaciers exhibited anomalous behavior from 1995 to 2010, peaking in 2003, but they have shown signs of retreat since the 2010s, marking the end of the Karakoram anomaly. These insights deepen our understanding of the Karakoram anomaly and provide a theoretical basis for assessing the effect of glacier anomaly to retreat dynamics on the water resources and adaptation strategies for the Indus and Tarim Rivers.
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
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
期刊最新文献
Two-decade surface ozone (O3) pollution in China: Enhanced fine-scale estimations and environmental health implications Assessing lead fraction derived from passive microwave images and improving estimates at pixel-wise level Estimating anthropogenic CO2 emissions from China's Yangtze River Delta using OCO-2 observations and WRF-Chem simulations A dual-branch network for crop-type mapping of scattered small agricultural fields in time series remote sensing images From theory to hydrological practice: Leveraging CYGNSS data over seven years for advanced soil moisture monitoring
×
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