多年度同时相“星-地”协同遥感反演鄱阳湖叶绿素a浓度

郑璞, 许新发, 许小华, 陈鑫雨, 张任高

长江科学院院报 ›› 2024, Vol. 41 ›› Issue (7) : 48-56.

PDF(8995 KB)
PDF(8995 KB)
长江科学院院报 ›› 2024, Vol. 41 ›› Issue (7) : 48-56. DOI: 10.11988/ckyyb.20230292
水环境与水生态

多年度同时相“星-地”协同遥感反演鄱阳湖叶绿素a浓度

  • 郑璞1,2, 许新发1,2, 许小华1,2, 陈鑫雨3, 张任高4
作者信息 +

Retrieval of Chlorophyll-a Concentration in Poyang Lake by Using Multi-annual and Simultaneous Satellite-Ground Remote Sensing

  • ZHENG Pu1,2, XU Xin-fa1,2, XU Xiao-hua1,2, CHEN Xin-yu3, ZHANG Ren-gao4
Author information +
文章历史 +

摘要

作为长江最大的通江湖泊,鄱阳湖水生态安全影响着整个长江流域。叶绿素a浓度是水生态富营养化的重要指标,利用遥感技术开展叶绿素a浓度常规监测具有重要意义。以鄱阳湖为试验区,以表征富营养化程度的叶绿素a浓度为反演指标,基于2015—2020年6 a的观测数据以及Landsat系列影像,在规范建模时相以及“星-地”协同匹配的情况下,通过分析对比不同波段与叶绿素a浓度的相关指数,构建了适用于夏季鄱阳湖水体叶绿素a浓度反演模型。经6组独立数据验证后R2均值为0.86,RMSE均值为1.01 μg/L,MAPE均值为17.6%,认为所采用的方法可以较好地适用于鄱阳湖区夏季(丰水期)叶绿素a浓度的的反演,同时也为具备长期观测条件下内陆二类水体叶绿素a浓度监测提供了新的参考方法。

Abstract

Poyang Lake, situated in north-central Jiangxi Province, is the largest freshwater lake in China and connects to the Yangtze River. Given its size and location, the lake’s water ecological security profoundly impacts the entire Yangtze River basin. Chlorophyll-a concentration serves as a crucial indicator of water ecological eutrophication, underscoring the importance of routine remote sensing monitoring. This study focuses on Poyang Lake, using chlorophyll-a as a proxy for eutrophication. By analyzing six years of observation data (2015-2020) and LandSat images, a retrieval model for summer chlorophyll-a concentration in Poyang Lake was developed. This model employs standard modeling techniques and ensures “satellite-ground” coordination to accurately match data. Through correlation analysis between various wavelength bands and chlorophyll-a concentration, the study constructs a robust retrieval model. Verification with six independent datasets yielded a mean R2 value of 0.86, RMSE of 1.01 μg/L, and MAPE of 17.6%. These results validate the efficacy of the method for chlorophyll-a retrieval in Poyang Lake and suggest its potential application as a reference for long-term monitoring of chlorophyll-a in similar inland Class II water bodies.

关键词

遥感反演 / 鄱阳湖 / 叶绿素a / 相关性分析

Key words

remote sensing / Poyang lake / chlorophyll-a / correlation analysis

引用本文

导出引用
郑璞, 许新发, 许小华, 陈鑫雨, 张任高. 多年度同时相“星-地”协同遥感反演鄱阳湖叶绿素a浓度[J]. 长江科学院院报. 2024, 41(7): 48-56 https://doi.org/10.11988/ckyyb.20230292
ZHENG Pu, XU Xin-fa, XU Xiao-hua, CHEN Xin-yu, ZHANG Ren-gao. Retrieval of Chlorophyll-a Concentration in Poyang Lake by Using Multi-annual and Simultaneous Satellite-Ground Remote Sensing[J]. Journal of Changjiang River Scientific Research Institute. 2024, 41(7): 48-56 https://doi.org/10.11988/ckyyb.20230292
中图分类号: TP79   

参考文献

[1] 马荣华,唐军武,段洪涛,等.湖泊水色遥感研究进展[J].湖泊科学,2009,21(2):143-158.(MA Rong-hua,TANG Jun-wu,DUAN Hong-tao,et al.Progress in Lake Water Color Remote Sensing[J]. Journal of Lake Sciences,2009,21(2):143-158.(in Chinese))
[2] 黄诗峰,徐 美,陈德清.GIS支持下的河网密度提取及其在洪水危险性分析中的应用[J].自然灾害学报,2001,10(4):129-132.(HUANG Shi-feng,XU Mei,CHEN De-qing.GIS-based Extraction of Drainage Network Density and It’s Application to Flood Hazard Analysis[J].Journal of Natural Disasters,2001,10(4):129-132.(in Chinese))
[3] 黄诗峰,钟邵南,徐 美.基于GIS的流域土壤侵蚀量估算指标模型方法:以嘉陵江上游西汉水流域为例[J].水土保持学报,2001,15(2):105-107,116.(HUANG Shi-feng,ZHONG Shao-nan,XU Mei.Categorical Model of Estimating Soil Erosion Based on GIS—A Case Study in Xihanshui Watershed[J]. Journal of Soil Water Conservation,2001,15(2):105-107,116.(in Chinese))
[4] YULONG G, HUA C, LI Y, et al. Hyperspectral Reconstruction Method for Optically Complex Inland Waters Based on Bio-optical Model and Sparse Representing[J]. Remote Sensing of Environment, 2022, 276(7): 113045.
[5] NEIL C,SPYRAKOS E,HUNTER P D,et al.A Global Approach for Chlorophyll-a Retrieval across Optically Complex Inland Waters Based on Optical Water Types[J].Remote Sensing of Environment,2019,229:159-178.
[6] MA R H,DAI J F.Investigation of Chlorophyll-a and Total Suspended Matter Concentrations Using Landsat-ETM and Field Spectral Measurement in Taihu Lake, China[J]. International Journal of Remote Sensing. 2007, 26(13): 2779-2795.
[7] 王学军,马 廷.应用遥感技术监测和评价太湖水质状况[J].环境科学,2000,21(6):65-68.(WANG Xue-jun,MA Ting.The Application of Remote Sensing Technology in Monitoring the Water Quality of Taihu Lake[J].Chinese Journal of Enviromental Science,2000,21(6):65-68.(in Chinese))
[8] 肖 潇, 汪朝辉. 丹江口典型库湾富营养化遥感分析及防治措施[J]. 人民长江, 2011, 42(9): 33-37. (XIAO Xiao, WANG Chao-hui. Remote Sense Monitoring and Analysis on Eutrophication in Typical Bays of Danjiangkou Reservoir and Control Measures[J]. Yangtze River, 2011, 42(9): 33-37.(in Chinese))
[9] YU G, YANG W, MATSUSHITA B, et al. Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-red-based Algorithm: Validation in Asian Lakes[J]. Remote Sensing, 2014, 6(4): 3492-3510.
[10]GITELSON A A, SCHALLES J F, HLADIK C M. Remote Chlorophyll-a Retrieval in Turbid, Productive Estuaries: Chesapeake Bay Case Study[J]. Remote Sensing of Environment, 2007, 109(4): 464-472.
[11]黄启会,贺中华,梁 虹,等.基于HJ-1ACCD数据的湖泊叶绿素a浓度反演:以贵阳市百花湖为例[J].人民长江,2019,50(3):66-72.(HUANG Qi-hui,HE Zhong-hua,LIANG Hong,et al. Inversion of Chlorophyll-a Concentration in Baihua Lake in Guiyang City Based on HJ-1A CCD Data[J].Yangtze River,2019,50(3):66-72.(in Chinese))
[12]陈武阳,李骏旻,何庆友,等.南海岛礁周边海域表面叶绿素浓度的时空特征[J].热带海洋学报,2019,38(6):21-28.(CHEN Wu-yang,LI Jun-min,HE Qing-you,et al. Spatial-temporal Variation of Sea Surface Chlorophyll around Islands and Reefs in the South China Sea[J].Journal of Tropical Oceanography,2019,38(6):21-28.(in Chinese))
[13]但雨生, 周忠发, 李韶慧, 等. 基于Sentinel-2的平寨水库叶绿素a浓度反演[J]. 环境工程, 2020, 38(3): 180-185, 127. (DAN Yu-sheng, ZHOU Zhong-fa, LI Shao-hui, et al. Retrieval of chlorophyll-a Concentration in Pingzhai Reservoir Based on SENTINEL-2[J]. Environmental Engineering, 2020, 38(3): 180-185, 127.(in Chinese))
[14]潘 鑫,杨 子,杨英宝,等.基于高分六号卫星遥感影像的太湖叶绿素a质量浓度反演[J].河海大学学报(自然科学版),2021,49(1):50-56.(PAN Xin,YANG Zi,YANG Ying-bao,et al. Mass Concentration Inversion Analysis of Chlorophyll a in Taihu Lake Based on GF-6 Satellite Data[J].Journal of Hohai University (Natural Sciences),2021,49(1):50-56.(in Chinese))
[15]郭云开, 钱 佳, 雷宇斌, 等. 基于GF-1卫星数据的水库叶绿素a浓度联合反演研究[J]. 测绘工程, 2021, 30(4): 14-19. (GUO Yun-kai, QIAN Jia, LEI Yu-bin, et al. Joint Retrieval of Chlorophyll-a Concentration in Reservoir Based on GF-1 Satellite Data[J]. Engineering of Surveying and Mapping, 2021, 30(4): 14-19.(in Chinese))
[16]徐鹏飞, 程 乾, 金平斌. 基于神经网络模型的千岛湖清洁水体叶绿素a遥感反演研究[J]. 长江流域资源与环境, 2021, 30(7): 1670-1679. (XU Peng-fei, CHENG Qian, JIN Ping-bin. Inversion of Chlorophyll-a of Clean Water in Qiandao Lake with Remote Sensing Data Using the Neural Network[J]. Resources and Environment in the Yangtze Basin, 2021, 30(7): 1670-1679.(in Chinese))
[17]祁兰兰,王金亮,农兰萍,等.基于GF-1卫星数据的洱海干季水质时空变化监测[J].人民长江,2021,52(9):24-31.(QI Lan-lan,WANG Jin-liang,NONG Lan-ping,et al.Temporal and Spatial Monitoring on Water Quality of Erhai Lake in Dry Season Based on GF-1 Satellite Data[J]. Yangtze River, 2021, 52(9): 24-31.(in Chinese))
[18]武 爽,冯险峰,陈点点,等.基于光谱特征的闽江干流叶绿素a遥感反演[J].遥感信息,2022,37(3):87-92.(WU Shuang, FENG Xian-feng, CHEN Dian-dian, et al. Remote Sensing Retrieval of Chlorophyll-a in Minjiang River Based on Spectral Characteristics[J]. Remote Sensing Information, 2022, 37(3): 87-92.(in Chinese))
[19]《鄱阳湖研究》编委会. 鄱阳湖研究[M]. 上海: 上海科学技术出版社, 1988. (The Editing Committee. Research on the Poyang Lake[M]. Shanghai: Shanghai Scientific and Technical Publishers, 1998. (in Chinese )
[20]NAZEER M, OLAYINKA ILORI C, BILAI M, et al. Evaluation of Atmospheric Correction Methods for Low to High Resolutions Satellite Remote Sensing Data[J]. Atmospheric Research,2021,249:105308.
[21]刘 阁, 李云梅, 吕 恒, 等. 基于MERIS影像的洪泽湖叶绿素a浓度时空变化规律分析[J]. 环境科学, 2017, 38(9): 3645-3656. (LIU Ge, LI Yun-mei, L Heng, et al. Remote Sensing of Chlorophyll-a Concentrations in Lake Hongze Using Long Time Series MERIS Observations[J]. Environmental Science, 2017, 38(9): 3645-3656.(in Chinese))
[22]毕 顺,李云梅,吕 恒,等.基于OLCI数据的洱海叶绿素a浓度估算[J].湖泊科学,2018,30(3):701-712.(BI Shun,LI Yun-mei,L Heng,et al.Estimation of Chlorophyll-a Concentration in Lake Erhai Based on OLCI Data[J]. Journal of Lake Sciences,2018,30(3):701-712.(in Chinese))
[23]郑著彬, 张润飞, 李建忠, 等. 基于欧比特高光谱影像的滇池叶绿素a浓度遥感反演研究[J]. 遥感学报, 2022, 26(11): 2162-2173. (ZHENG Zhu-bin, ZHANG Run-fei, LI Jian-zhong, et al. Remote Sensing Retrieval of Chlorophyll-a Concentration in Dianchi Lake Based on Orbita Hyperspectral Imagery[J]. National Remote Sensing Bulletin, 2022, 26(11): 2162-2173.(in Chinese))
[24]LEE Z, CARDER K L, DU K. Effects of Molecular and Particle Scattering on the Model Parameter for Remote-Sensing Reflectance[J]. Applied Optics, 2004, 43(25): 4957-4964.
[25]姜玲玲, 王龙霄, 王 林, 等. 基于Sentinel-3 OLCI影像的渤海透明度遥感反演研究[J]. 光谱学与光谱分析, 2022, 42(4): 1209-1216. (JIANG Ling-ling, WANG Long-xiao, WANG Lin, et al. Research on Remote Sensing Retrieval of Bohai Sea Transparency Based on Sentinel-3 OLCI Image[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1209-1216.(in Chinese))
[26]韦安娜, 田礼乔, 陈晓玲, 等. 基于穷举法的鄱阳湖叶绿素a浓度高光谱反演模型与应用研究: 以GF-5卫星AHSI数据为例[J]. 华中师范大学学报(自然科学版), 2020, 54(3): 447-453. (WEI An-na, TIAN Li-qiao, CHEN Xiao-ling, et al. Retrieval and Application of Chlorophyll-a Concentration in the Poyang Lake Based on Exhaustion Method: a Case Study of Chinese Gaofen-5 Satellite AHSI Data[J]. Journal of Central China Normal University (Natural Sciences), 2020, 54(3): 447-453.(in Chinese))
[27]李怡静, 孙晓敏, 郭玉银, 等. 基于梯度提升决策树算法的鄱阳湖水环境参数遥感反演[J]. 航天返回与遥感, 2020, 41(6): 90-102. (LI Yi-jing, SUN Xiao-min, GUO Yu-yin, et al. Remote Sensing Retrieval of Water Quality Parameters in Poyang Lake Based on the Gradient Boosting Decision Tree Algorithm[J]. Spacecraft Recovery & Remote Sensing, 2020, 41(6): 90-102.(in Chinese))
[28]邓实权, 田礼乔, 李 建, 等. 面向GF-5卫星高光谱传感器的浑浊水体叶绿素a浓度反演算法研究: 以鄱阳湖为例[J]. 华中师范大学学报(自然科学版), 2018, 52(3): 409-415. (DENG Shi-quan, TIAN Li-qiao, LI Jian, et al. A Novel Chlorophyll-a Inversion Model in Turbid Water for GF-5 Satellite Hyperspectral Sensor—A Case in Poyang Lake[J]. Journal of Central China Normal University (Natural Sciences), 2018, 52(3): 409-415.(in Chinese))
[29]李亭亭,田礼乔,李 建,等.基于Sentinel卫星的浑浊水体叶绿素反演对比研究:以鄱阳湖为例[J].华中师范大学学报(自然科学版),2017,51(6):858-864.(LI Ting-ting, TIAN Li-qiao, LI Jian, et al. Comparison Study on the Retrieval of Chlorophyll in Turbid Waters Based on Sentinel Satellites—A Case Study of Poyang Lake[J]. Journal of Central China Normal University (Natural Sciences), 2017, 51(6): 858-864.(in Chinese))
[30]封 雷, 封 丽, 方 芳, 等. 基于改进多层卷积神经网络的水体富营养化遥感监测算法研究[J]. 计算机科学, 2022, 49(增刊2): 388-392. (FENG Lei, FENG Li, FANG Fang, et al. Research on Remote Sensing Monitoring Algorithm of Water Eutrophication Based on Improved Multilayer Convolutional Neural Network[J]. Computer Science, 2022, 49(Supp.2): 388-392.(in Chinese))
[31]冯天时, 庞治国, 江 威. 基于珠海一号高光谱卫星的巢湖叶绿素a浓度反演[J]. 光谱学与光谱分析, 2022, 42(8): 2642-2648. (FENG Tian-shi, PANG Zhi-guo, JIANG Wei. Remote Sensing Retrieval of Chlorophyll-a Concentration in Lake Chaohu Based on Zhuhai-1 Hyperspectral Satellite[J]. Spectroscopy and Spectral Analysis, 2022, 42(8): 2642-2648.(in Chinese))

基金

江西省科技厅重大科技研发专项(20213AAG01012);江西省科技厅重点研发计划项目(20212BBG71008)

PDF(8995 KB)

Accesses

Citation

Detail

段落导航
相关文章

/