基于GF1_WFV的千岛湖水体叶绿素a浓度时空变化

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Abstract We established a simulating model based on the GF-1spectral reflectance features and field survey results. The model was then applied to estimate the concentration and distribution of chlorophyll-a in Qiandao lake from 2013~2019. Our model could effectively estimate the chlorophyll-a concentration in clean water (R²=0.8976). Pixel level analysis revealed that over 94% of water pixels contained less than 3.65μg/L of chlorophyll-a, indicating that the chlorophyll-a concentration of Qiandao lake was quite low during the study period. Moreover, the spatial-temporal analysis showed that the chlorophyll-a concentration in most water pixels experienced a small variation. More than 67% water regions had a slight increase.

Key words： Qiandao Lake chlorophyll-a GF-1 satellite spatial-temporal variation

Received: 12 February 2020

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X524

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	Articles by authors
	XU Peng-fei
	MAO Feng
	JIN Ping-bin
	CHENG Qian

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XU Peng-fei,MAO Feng,JIN Ping-bin等. Spatial-temporal variations of chlorophyll-a in Qiandao lake using GF1_WFV data[J]. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(10): 4580-4588.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2020/V40/I10/4580

[1]	朱利,李云梅,赵少华,等.基于GF-1号卫星WFV数据的太湖水质遥感监测[J]. 国土资源遥感, 2015,27(1):113-120. Zhu L, Li Y M, Zhao S H, et al. Remote sensing monitoring of Taihu Lake water quality by using GF-1satellite WFV data[J]. Remote Sensing for Land and Resources, 2015,27(1):113-120.
[2]	Agboola J I, Uchimiya M, Kudo I, et al. Seasonality and environmental drivers of biological productivity on the western Hokkaido coast, Ishikari Bay, Japan[J]. Estuarine, Coastal and Shelf Science, 2013,127:12-23.
[3]	Li Y, Zhang Y, Shi K, et al. Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derived from Landsat 8OLI data:understanding its driving and restrictive factors[J]. Environmental Science and Pollution Research, 2017,25(2):1-16.
[4]	Chen J, Zhang X, Quan W. Retrieval chlorophyll-a concentration from coastal waters:three-band semi-analytical algorithms comparison and development[J]. Optics Express, 2013,21(7):9024-9042.
[5]	马荣华,孔维娟,段洪涛,等.基于MODIS影像估测太湖蓝藻爆发期蓝藻素含量[J]. 中国环境科学, 2009,29(3):254-260. Ma R H, Kong W J, Duan H T, et al. Quantitative estimation of phycocyanin concentration using MODIS imagery during the period of cyanobacterial blooming in Taihu Lake[J]. China Environmental Science, 2009,29(3):254-260.
[6]	Moses W J, Gitelson A A, Berdnikov S, et al. Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data-Successes and challenges[J]. Environmental Research Letters, 2009,4:1-8.
[7]	Satish P, Ridhi S, Garg J K. Assessing the efficacy of Landsat-8OLI imagery derived models for remotely estimating chlorophyll-a concentration in the Upper Ganga River, India[J]. International Journal of Remote Sensing, 2019,41(7):2439-2456.
[8]	王莹,刘其根,冯权泷,等.基于ETM+影像的千岛湖叶绿素a浓度卫星遥感反演研究[J]. 激光生物学报, 2015,24(5):441-447. Wang Y, Liu Q G, Feng Q L, et al. Inversion of chlorophyll-a concentration based on satellite remote sensing in Qiandao Lake[J]. Acta Laser Biology Sinica, 2015,24(5):441-447.
[9]	刘波,程乾,曾焕建,等.基于GOCI数据的杭州湾跨海大桥两侧水域悬浮泥沙浓度空间分异规律研究[J]. 杭州师范大学学报(自然科学版), 2016,82(1):105-110. Liu B, Cheng Q, Zeng H J, et al. On the suspended sediment concentration distribution and diversity of the waters on both sides of Hangzhou Bay Sea-crossing bridge based on GOCI data[J]. Journal of Hangzhou Normal University (Natural Science Edition), 2016,82(1):105-110.
[10]	高晨,徐健,高丹,等.基于GF-1与实测光谱数据鄱阳湖丰水期总悬浮物浓度反演[J]. 国土资源遥感, 2019,31(1):101-109. Gao C, Xu J, Gao D, et al. Retrieval of concentration of total suspended matter from GF-1satellite and field measures spectral data during flood in Poyang Lake[J]. Remote Sensing for Land and Resources, 2019,31(1):101-109.
[11]	潘梅娥,杨昆,洪亮.基于环境一号卫星影像的内陆水体叶绿素a浓度遥感定量反演模型研究[J]. 科学技术与工程, 2013,13(15):4228-4233. Pan M E, Yang K, Hong L. Remote sensing quantitative retrieval models research of inland chlorophyll-a concentration based on HJ-1satellite images[J]. Science Technology and Engineering, 2013, 13(15):4228-4233.
[12]	佘红英,李家国,陈云嵩,等.基于GF-1号卫星的龙江水库水环境遥感监测适宜性[J]. 四川环境, 2017,36:95-102. She H Y, Li J G, Chen Y S, et al. Suitability assessment of water environment remote sensing monitoring of Longjiang reservior by using GF-1satellite[J]. Sichuan Environment, 2017,36:95-102.
[13]	温爽,王桥,李云梅,等.基于高分影像的城市黑臭水体遥感识别:以南京为例[J]. 环境科学, 2018,39(1):57-67. Wen S, Wang Q, Li Y M, et al. Remote sensing identification of Urban Black-Odor Water Bodies based on high-resolution images:A case study in Nanjing[J]. Environmental Science, 2018,39(1):57-67.
[14]	程乾,刘波,李婷,等.基于高分1号杭州湾河口悬浮泥沙浓度遥感反演模型构建及应用[J]. 海洋环境科学学报, 2015,34(4):558-563,577. Cheng Q, Liu B, Li T, et al. Research on remote sensing retrieval of suspended sediment concentration in Hangzhou Bay by GF-1satellite[J]. Marine Environmental Science, 2015,34(4):558-563,577
[15]	程春梅,李渊,丁奕,等.基于GF-1/WFV的钱塘江叶绿素a和总悬浮物浓度遥感估算[J]. 长江科学院院报, 2019,36(1):25-32. Cheng C M, Li Y, Ding Y, et al. Remote sensing estimation of Chlorophyll-a and total suspended matter concentration in Qiantang river based on GF-1/WFV data[J]. Journal of Yangtze River Scientific Research Institute, 2019,36(1):25-32.
[16]	唐军武,田国良,汪小勇,等.水体光谱测量与分析Ⅰ:水面以上测量法[J]. 遥感学报, 2004,8(1):37-44. Tang J W, Tian G L, Wang X Y, et al. The methods of water spectra measurement and analysis I:Above-water method[J]. Journal of Remote Sensing. 2004,8(1):37-44.
[17]	Koponen S, Pulliainen J, Kallio K, et al. Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data[J]. Remote Sensing of Environment, 2002,79(1):51-59.
[18]	Milich L, Weiss E. GAC NDVI interannual coefficient of variation (CoV) images:Ground truth sampling of the Sahel along north-south transects[J]. International Journal of Remote Sensing, 2000,21(2):235-260.
[19]	Theil H. A rank-invariant method of linear and polynomial regression analysis[J]. Mathematics, 1992,12(2):345-381.
[20]	Mann H B. Non-parametric tests against trend[J]. Econometrics, 1945,2(13):245-259.
[21]	Hamed K H R R. A modified Mann-Kendall trend test for auto correlated data[J]. Journal of Hydrology, 1998,204:182-196.
[22]	Marengo J A. Interdecadal variability and trends of rainfall across the Amazon basin[J]. Theoretical and Applied Climatology, 2004, 78(1):79-96.
[23]	Fensholt R, Langanke T, Rasmussen K, et al. Greenness in semi-arid areas across the globe 1981-2007-an Earth Observing Satellite based analysis of trends and drivers[J]. Remote Sensing of Environment, 2012,121:144-158.
[24]	Motiee H, Mcbean E. An assessment of long-term trends in hydrologic components and implications for water levels in Lake Superior[J]. Hydrology Research, 2009,40(6):564-579.
[25]	Jin J, Wang Q. Assessing ecological vulnerability in western China based on Time-Integrated NDVI data[J]. Journal of Arid Land, 2016,8(4):533-545.
[26]	Yin G, Hu Z, Chen X, et al. Vegetation dynamics and its response to climate change in Central Asia[J]. Journal of Arid Land, 2016,8(3):375-388.