Literature DB >> 15207584

Water quality change in reservoirs of Shenzhen, China: detection using LANDSAT/TM data.

Yunpeng Wang1, Hao Xia, Jiamo Fu, Guoying Sheng.   

Abstract

The objective of this research is to explore a precise and fast way of monitoring water chemical and biochemical quality in the reservoirs of Shenzhen, China. Water quality change in 1988 and 1996 are detected by synthesizing satellite data and ground-based data. One scene Thematic Mapper (TM) image in winter of 1996 was acquired and the simultaneous in situ measurement, sampling and analysis were performed. Main methods include radiometric calibration of TM remote sensor, atmospheric correction to image data and statistical model construction. The results indicate that satellite-based estimates and in situ measured water reflectance have very high correlation, and the root mean square differences between two kinds of indices are close to 0.02-0.03 for each TM band in Visible-Near Infrared (VI-NIR) range. Statistical relationship between calibrated image data (average of 5 x 5 pixels) of TM bands and laboratory analyzed data of water samples indicated reflectance of TM band 1 to band 4 and organic pollution measurements such as TOC, BOD and COD had higher correlation. The same scene TM data in the winter of 1988 was processed in the same procedure. Results indicate that water quality of most reservoirs have become worse. Water of eastern reservoirs near Dongjiang River is characterized with higher TOC and TSS, and water of western reservoirs is characterized with higher BOD and COD. Copyright 2004 Elsevier B.V.

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Year:  2004        PMID: 15207584     DOI: 10.1016/j.scitotenv.2004.02.020

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  21 in total

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8.  Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derived from Landsat 8 OLI data: understanding its driving and restrictive factors.

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Authors:  Murat Kavurmacı; Semih Ekercin; Levent Altaş; Yakup Kurmaç
Journal:  Environ Sci Pollut Res Int       Date:  2013-02-20       Impact factor: 4.223

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