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  • Cartography and geographic base data  (1)
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  • Cartography and geographic base data  (1)
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    Online Resource
    Online Resource
    Walter de Gruyter GmbH ; 2015
    In:  Geodesy and Cartography Vol. 64, No. 1 ( 2015-06-1), p. 29-42
    In: Geodesy and Cartography, Walter de Gruyter GmbH, Vol. 64, No. 1 ( 2015-06-1), p. 29-42
    Abstract: The coastal zone and estuaries of Quang Ninh and Hai Phong have great potential not only for economic development but also for protection and conservation of biodiversity and ecosystem. Nowadays, due to industrial, agricultural and anthropogenic activities signs of water pollution in the region have been found. The level of surface water pollution can be determined by traditional methods through observatory stations. However, a traditional approach to determine water contamination is discontinuous, and thereby makes pollution assessment of the entire estuary very difficult. Nowadays, remote sensing technology has been developed and widely applied in many fields, for instance, in monitoring water environments. Remote sensing data combined with information from in-situ observations allow for extraction of polluted components in water and accurate measurements of pollution level in the large regions ensuring objectivity. According to results obtained from Spot-5 imagery of Quang Ninh and Hai Phong, the extracted pollution components, like BOD, COD and TSS can be determined with the root mean square error, the absolute mean error and the absolute mean percentage error (%): ±4.37 (mg/l) 3.86 (mg/l), 27%; ±55.32 (mg/l), 48.30 (mg/l), 14%; and ±32.90 (mg/l), 23.38 (mg/l), 28%; respectively. Obtained outcomes guarantee objectivity in assessing water contaminant levels in the investigated regions and show the advantages of remote sensing applications in Resource and Environmental Monitoring in relation to Water – Air – Land.
    Type of Medium: Online Resource
    ISSN: 2300-2581
    Language: Unknown
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2015
    detail.hit.zdb_id: 2802019-4
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