Estimation of total suspended solids concentration by hyperspectral remote sensing in Liaodong Bay

文献类型: 外文期刊

第一作者: Wang, Jingjing

作者: Wang, Jingjing;Tian, Qingjiu

作者机构:

关键词: Total suspended solids;Hyperion;Hyperspectral remote sensing;Coastal zone

期刊名称:INDIAN JOURNAL OF GEO-MARINE SCIENCES ( 影响因子:0.496; 五年影响因子:0.605 )

ISSN: 0379-5136

年卷期: 2015 年 44 卷 8 期

页码:

收录情况: SCI

摘要: Present study consists the potential of the satellite hyperspectral data - Hyperion image for mapping total suspended solids (TSS) concentration of coastal water in Liaodong Bay, China. After processing and atmospheric correction, the reflectance of water extracted from Hyperion image can be used to express the spectral characteristics of different TSS concentration. Estimated algorithms of TSS concentration based on water reflective spectra data collected in situ. The results indicated near infrared wavelength had better correlation with TSS concentration. Exponential algorithm was found to have better accuracy in estimate the concentration less than 200mg l(-1) and linear algorithm was suited for the concentration range in 200-500 mg l(-1) and logarithm algorithm can better describe the correlation between the reflectance and concentration range in 500-1000 mg l(-1).

分类号:

  • 相关文献

[1]Estimation of Rice Canopy Nitrogen Concentration by Hyperspectral Remote Sensing. Wang, Jingjing,Sun, Ling,Shi, Chunlin,Tian, Qingjiu. 2013

[2]Evaluating Multispectral and Hyperspectral Satellite Remote Sensing Data for Estimating Winter Wheat Growth Parameters at Regional Scale in the North China Plain. Koppe, Wolfgang,Gnyp, Martin L.,Bareth, Georg,Koppe, Wolfgang,Chen, Xinping,Zhang, Fusuo,Li, Fei,Miao, Yuxin,Miao, Yuxin. 2010

[3]Estimation of Overstory and Understory Leaf Area Index by Combining Hyperion and Panchromatic QuickBird Data Using Neural Network Method. Huang, Jianxi,Su, Wei,Zeng, Yuan,Wu, Wenbin,Mao, Kebiao,Xu, Jingyu.

[4]Hyperspectral Discrimination and Response Characteristics of Stressed Rice Leaves Caused by Rice Leaf Folder. Liu, Zhanyu,Ding, Xiaodong,Zhou, Bin,Liu, Zhanyu,Cheng, Jia-an,Huang, Wenjiang,Li, Cunjun,Xu, Xingang,Shi, Jingjing. 2012

[5]Leaf Area Index Estimation Using Vegetation Indices Derived From Airborne Hyperspectral Images in Winter Wheat. Xie, Qiaoyun,Huang, Wenjiang,Liang, Dong,Huang, Linsheng,Zhang, Dongyan,Chen, Pengfei,Wu, Chaoyang,Yang, Guijun,Zhang, Jingcheng. 2014

[6]Identifying Leaf-Scale Wheat Aphids Using the Near-Ground Hyperspectral Pushbroom Imaging Spectrometer. Zhao, Jinling,Zhang, Dongyan,Luo, Juhua,Wang, Dacheng,Huang, Wenjiang. 2012

[7]Estimation of carotenoid content at the canopy scale using the carotenoid triangle ratio index from in situ and simulated hyperspectral data. Kong, Weiping,Huang, Wenjiang,Zhou, Xianfeng,Kong, Weiping,Zhou, Xianfeng,Song, Xiaoyu,Casa, Raffaele. 2016

[8]Associating new spectral features from visible and near infrared regions with optimal combination principle to monitor leaf nitrogen concentration in barley. Xu Xin-Gang,Zhao Chun-Jiang,Wang Ji-Hua,Li Cun-Jun,Yang Xiao-Dong. 2013

[9]New Vegetation Index Fusing Visible-Infrared and Shortwave Infrared Spectral Feature for Winter Wheat LAI Retrieval. Li Xin-chuan,Xu Xin-gang,Jin Xiu-liang,Zhang Jing-cheng,Song Xiao-yu,Li Xin-chuan,Xu Xin-gang,Jin Xiu-liang,Zhang Jing-cheng,Song Xiao-yu,Li Xin-chuan,Bao Yan-song. 2013

[10]Retrieving Soybean Leaf Area Index from Unmanned Aerial Vehicle Hyperspectral Remote Sensing: Analysis of RF, ANN, and SVM Regression Models. Yuan, Huanhuan,Yang, Guijun,Wang, Yanjie,Liu, Jiangang,Yu, Haiyang,Feng, Haikuan,Xu, Bo,Zhao, Xiaoqing,Yang, Xiaodong,Yuan, Huanhuan,Li, Changchun,Wang, Yanjie,Yuan, Huanhuan,Yang, Guijun,Liu, Jiangang,Feng, Haikuan,Yang, Xiaodong,Yang, Guijun,Yu, Haiyang,Xu, Bo,Zhao, Xiaoqing,Yang, Xiaodong. 2017

[11]A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements. Zhao, Feng,Guo, Yiqing,Verhoef, Wout,Gu, Xingfa,Liu, Liangyun,Yang, Guijun. 2014

[12]Research of Cotton Canopy Characteristic Information by Hyperspectral Remote Sensing Data. Qi Ya-qin,Lv Xin,Duan Zhen-yu. 2013

[13]Band Depth Analysis and Partial Least Square Regression Based Winter Wheat Biomass Estimation Using Hyperspectral Measurements. Fu Yuan-yuan,Wang Ji-hua,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan. 2013

[14]The Study of Winter Wheat Biomass Estimation Model Based on Hyperspectral Remote Sensing. Teng, Xiaowei,Dong, Yansheng,Teng, Xiaowei,Dong, Yansheng,Teng, Xiaowei,Dong, Yansheng,Teng, Xiaowei,Dong, Yansheng,Teng, Xiaowei,Meng, Lumin. 2016

[15]CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MULTI-ANGULAR HYPERSPECTRAL MEASUREMENTS. Zhao, Jinling,Yuan, Lin,Zhang, Dongyan,Zhang, Jingcheng,Gu, Xiaohe,Huang, Linsheng,Zhang, Dongyan. 2013

[16]Estimation of crop LAI using hyperspectral vegetation indices and a hybrid inversion method. Liang, Liang,Zhang, Lianpeng,Lin, Hui,Liang, Liang,Zhao, Shuhe,Liang, Liang,Di, Liping,Deng, Meixia,Qin, Zhihao.

[17]Evaluation of spectral indices and continuous wavelet analysis to quantify aphid infestation in wheat. Luo, Juhua,Huang, Wenjiang,Yuan, Lin,Zhao, Chunjiang,Zhang, Jingcheng,Zhao, Jinling,Du, Shizhou.

[18]Comparison of Four Chemometric Techniques for Estimating Leaf Nitrogen Concentrations in Winter Wheat (Triticum Aestivum) Based on Hyperspectral Features. Li, Zh.,Wei, Ch.,Wang, J.,Li, Zh.,Nie, Ch.,Xu, X.,Song, X.,Li, Zh.,Nie, Ch.,Xu, X.,Song, X.,Wang, J..

[19]Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions. Xie, Qiaoyun,Huang, Wenjiang,Xie, Qiaoyun,Dash, Jadunandan,Song, Xiaoyu,Wang, Renhong,Huang, Linsheng,Zhao, Jinling.

作者其他论文 更多>>