An improved analytical algorithm for remote estimation of chlorophyll-a in highly turbid waters

被引:18
|
作者
Li, Linhai [1 ]
Li, Lin [1 ]
Song, Kaishan [1 ,2 ]
Li, Yunmei [3 ]
Shi, Kun [1 ,3 ]
Li, Zuchuan [1 ]
机构
[1] Indiana Univ Purdue Univ, Dept Earth Sci, Indianapolis, IN 46202 USA
[2] Chinese Acad Sci, NE Inst Geog & Agr Ecol, Changchun 130012, Jilin, Peoples R China
[3] Nanjing Normal Univ, Coll Geog Sci, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210046, Peoples R China
来源
ENVIRONMENTAL RESEARCH LETTERS | 2011年 / 6卷 / 03期
关键词
chlorophyll-a; remote sensing; turbid waters; MERIS; inherent optical properties; INLAND; COASTAL; CYANOBACTERIA; RETRIEVAL; QUALITY; BLOOMS; MODEL;
D O I
10.1088/1748-9326/6/3/034037
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An analytical three-band algorithm for spectrally estimating chlorophyll-a (Chl-a) has been proposed recently and the model does not need to be trained. However, the model did not consider the effects of the absorption due to colored detritus matter (CDM) and backscattering of the water column, resulting in an overestimation when Chl-a < 50 mg m(-3) and an underestimation when Chl-a >= 50 mg m(-3). In this letter, an improved three-band algorithm is proposed by integrating both backscattering and CDM absorption coefficients into the model. The results demonstrate that the improved three-band model resulted in more accurate estimation of Chl-a than the previously used three-band model when they were applied to water samples collected from five highly turbid water bodies with Chl-a ranging from 2.54 to 285.8 mg m(-3). The best results, after model modification, were observed in three Indiana reservoirs with R-2 = 0.905 and relative root mean square error of 20.7%, respectively.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] Remote sensing retrieval for chlorophyll-a concentration in turbid case II waters(I): The optimal model
    Zhou, Lin
    Ma, Rong-Hua
    Duan, Hong-Tao
    Jiang, Guang-Jia
    Shang, Lin-Lin
    Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves, 2011, 30 (06): : 531 - 536
  • [22] Remote Sensing of Chlorophyll-A in Case II Waters: A Novel Approach With Improved Accuracy Over Widely Implemented Turbid Water Indices
    Menon, Harilal B.
    Adhikari, Arjun
    JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2018, 123 (11) : 8138 - 8158
  • [23] Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes
    Yu, Gongliang
    Yang, Wei
    Matsushita, Bunkei
    Li, Renhui
    Oyama, Yoichi
    Fukushima, Takehiko
    REMOTE SENSING, 2014, 6 (04) : 3492 - 3510
  • [24] Assessment of NIR-red algorithms for observation of chlorophyll-a in highly turbid inland waters in China
    Huang, Changchun
    Zou, Jun
    Li, Yunmei
    Yang, Hao
    Shi, Kun
    Li, Junsheng
    Wang, Yanhua
    Chen, Xia
    Zheng, Fa
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 93 : 29 - 39
  • [25] Validation of a synthetic chlorophyll index for remote estimates of chlorophyll-a in a turbid hypereutrophic lake
    Zhang, Fangfang
    Zhang, Bing
    Li, Junsheng
    Shen, Qian
    Wu, Yuanfeng
    Wang, Ganlin
    Zou, Lei
    Wang, Shenglei
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2014, 35 (01) : 289 - 305
  • [26] Remote sensing retrieval for chlorophyll-a concentration in turbid case II waters (II): application on MERIS image
    Jiang Guang-Jia
    Zhou Lin
    Ma Rong-Hua
    Duan Hong-Tao
    Shang Lin-Lin
    Rao Jia-Wang
    Zhao Chen-Lu
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2013, 32 (04) : 372 - 378
  • [27] Improving Satellite Chlorophyll-a Retrieval in the Turbid Waters of the Bay of Fundy, Canada
    Wilson, Kristen L.
    Hilborn, Andrea
    Clay, Stephanie
    Devred, Emmanuel
    ESTUARIES AND COASTS, 2024, 47 (04) : 1012 - 1031
  • [28] Improving Satellite Chlorophyll-a Retrieval in the Turbid Waters of the Bay of Fundy, Canada
    Kristen L. Wilson
    Andrea Hilborn
    Stephanie Clay
    Emmanuel Devred
    Estuaries and Coasts, 2024, 47 : 1012 - 1031
  • [29] Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results
    Dall'Olmo, Giorgio
    Gitelson, Anatoly A.
    APPLIED OPTICS, 2006, 45 (15) : 3577 - 3592
  • [30] Estimation of Chlorophyll-a Concentrations in a Highly Turbid Eutrophic Lake Using a Classification-Based MODIS Land-Band Algorithm
    Li, Junsheng
    Gao, Min
    Feng, Lian
    Zhao, Hongli
    Shen, Qian
    Zhang, Fangfang
    Wang, Shenglei
    Zhang, Bing
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 12 (10) : 3769 - 3783