Zhigang Cao , Chuanmin Hu , Ronghua Ma , Hongtao Duan , Miao Liu , Steven Loiselle , Kaishan Song , Ming Shen , Dong Liu , Kun Xue
{"title":"MODIS观测显示,近20年来中国湖泊悬浮颗粒物呈下降趋势","authors":"Zhigang Cao , Chuanmin Hu , Ronghua Ma , Hongtao Duan , Miao Liu , Steven Loiselle , Kaishan Song , Ming Shen , Dong Liu , Kun Xue","doi":"10.1016/j.rse.2023.113724","DOIUrl":null,"url":null,"abstract":"<div><p>Variations in the concentrations and distribution of suspended particulate matter (SPM) of lakes can be used to show the responses of lake environment to climate and landscape change. However, the shifts and trends of SPM and potential drivers have not been well investigated across large spatial and temporal dimensions. This study developed a robust machine learning model to generate SPM time series in 269 lakes across China larger than 30 km<sup>2</sup> from 2002 to 2021 using MODIS/Aqua imagery. The support vector regression model showed satisfactory performance on SPM retrievals over four orders of magnitude (0.1–1000 mg L<sup>−1</sup>) (mean absolute percentage error = 26%). The model performance was shown to be insensitive to changes in environmental and observing conditions (e.g., aerosol type and thickness, viewing geometry), based on a radiative transfer simulation model. The long-term MODIS record showed a spatial pattern of lower SPM in the western lakes compared to the shallow lakes of east China. Importantly, the SPM showed a significant decrease in the 21st century (average rate of change of −0.2 mg L<sup>−1</sup>/decade). The interannual variations in SPM were aggregated into five categories, ranging from lakes with continuous changing patterns to those with reversed changing patterns. The driving factors behind the changing patterns vary between different climate zones and ecoregions. A warmer and wetter climate was associated with decreasing SPM in western lakes, while the decrease in wind speed and reduced possibility of soil erosion were the primary drivers of progressively lower SPM in the eastern shallow lakes. These results not only show a comprehensive picture of the SPM dynamics of lakes in China but also provide new insights into the complex mechanisms that drive SPM spatiotemporal dynamics.</p></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"295 ","pages":"Article 113724"},"PeriodicalIF":11.1000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MODIS observations reveal decrease in lake suspended particulate matter across China over the past two decades\",\"authors\":\"Zhigang Cao , Chuanmin Hu , Ronghua Ma , Hongtao Duan , Miao Liu , Steven Loiselle , Kaishan Song , Ming Shen , Dong Liu , Kun Xue\",\"doi\":\"10.1016/j.rse.2023.113724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Variations in the concentrations and distribution of suspended particulate matter (SPM) of lakes can be used to show the responses of lake environment to climate and landscape change. However, the shifts and trends of SPM and potential drivers have not been well investigated across large spatial and temporal dimensions. This study developed a robust machine learning model to generate SPM time series in 269 lakes across China larger than 30 km<sup>2</sup> from 2002 to 2021 using MODIS/Aqua imagery. The support vector regression model showed satisfactory performance on SPM retrievals over four orders of magnitude (0.1–1000 mg L<sup>−1</sup>) (mean absolute percentage error = 26%). The model performance was shown to be insensitive to changes in environmental and observing conditions (e.g., aerosol type and thickness, viewing geometry), based on a radiative transfer simulation model. The long-term MODIS record showed a spatial pattern of lower SPM in the western lakes compared to the shallow lakes of east China. Importantly, the SPM showed a significant decrease in the 21st century (average rate of change of −0.2 mg L<sup>−1</sup>/decade). The interannual variations in SPM were aggregated into five categories, ranging from lakes with continuous changing patterns to those with reversed changing patterns. The driving factors behind the changing patterns vary between different climate zones and ecoregions. A warmer and wetter climate was associated with decreasing SPM in western lakes, while the decrease in wind speed and reduced possibility of soil erosion were the primary drivers of progressively lower SPM in the eastern shallow lakes. These results not only show a comprehensive picture of the SPM dynamics of lakes in China but also provide new insights into the complex mechanisms that drive SPM spatiotemporal dynamics.</p></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"295 \",\"pages\":\"Article 113724\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425723002754\",\"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/S0034425723002754","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}
MODIS observations reveal decrease in lake suspended particulate matter across China over the past two decades
Variations in the concentrations and distribution of suspended particulate matter (SPM) of lakes can be used to show the responses of lake environment to climate and landscape change. However, the shifts and trends of SPM and potential drivers have not been well investigated across large spatial and temporal dimensions. This study developed a robust machine learning model to generate SPM time series in 269 lakes across China larger than 30 km2 from 2002 to 2021 using MODIS/Aqua imagery. The support vector regression model showed satisfactory performance on SPM retrievals over four orders of magnitude (0.1–1000 mg L−1) (mean absolute percentage error = 26%). The model performance was shown to be insensitive to changes in environmental and observing conditions (e.g., aerosol type and thickness, viewing geometry), based on a radiative transfer simulation model. The long-term MODIS record showed a spatial pattern of lower SPM in the western lakes compared to the shallow lakes of east China. Importantly, the SPM showed a significant decrease in the 21st century (average rate of change of −0.2 mg L−1/decade). The interannual variations in SPM were aggregated into five categories, ranging from lakes with continuous changing patterns to those with reversed changing patterns. The driving factors behind the changing patterns vary between different climate zones and ecoregions. A warmer and wetter climate was associated with decreasing SPM in western lakes, while the decrease in wind speed and reduced possibility of soil erosion were the primary drivers of progressively lower SPM in the eastern shallow lakes. These results not only show a comprehensive picture of the SPM dynamics of lakes in China but also provide new insights into the complex mechanisms that drive SPM spatiotemporal dynamics.
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.