Retrieval of total suspended matter concentrations from high resolution WorldView-2 imagery: a case study of inland rivers

International Conference on Energy Engineering and Environmental Protection 2017

能源学;生态环境科学

Shi, Liangliang^1,2 ; Mao, Zhihua^1,2 ; Wang, Zheng^2,3

Zhejiang University, Hangzhou

310028, China^1

State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou

310012, China^2

School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing

210023, China^3

关键词: Akaike information criterion;    High resolution satellite imagery;    High resolution satellites;    Monitoring water quality;    Multiple regression model;    Multivariable regression;    Radiometric corrections;    Spatial distribution map;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/121/3/032036/pdf
DOI  :  10.1088/1755-1315/121/3/032036

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Satellite imagery has played an important role in monitoring water quality of lakes or coastal waters presently, but scarcely been applied in inland rivers. This paper presents an attempt of feasibility to apply regression model to quantify and map the concentrations of total suspended matter (CTSM) in inland rivers which have a large scale of spatial and a high CTSM dynamic range by using high resolution satellite remote sensing data, WorldView-2. An empirical approach to quantify CTSM by integrated use of high resolution WorldView-2 multispectral data and 21 in situ CTSM measurements. Radiometric correction, geometric and atmospheric correction involved in image processing procedure is carried out for deriving the surface reflectance to correlate the CTSM and satellite data by using single-variable and multivariable regression technique. Results of regression model show that the single near-infrared (NIR) band 8 of WorldView-2 have a relative strong relationship (R2=0.93) with CTSM. Different prediction models were developed on various combinations of WorldView-2 bands, the Akaike Information Criteria approach was used to choose the best model. The model involving band 1, 3, 5, and 8 of WorldView-2 had a best performance, whose R2 reach to 0.92, with SEE of 53.30 g/m3. The spatial distribution maps were produced by using the best multiple regression model. The results of this paper indicated that it is feasible to apply the empirical model by using high resolution satellite imagery to retrieve CTSM of inland rivers in routine monitoring of water quality.