A Study of Relative Radiometric Normalization for Dynamic Monitoring of Environment Impacts of Mining Activities

doi:10.6046/gtzyyg.2010.03.10

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Abstract

In the dynamic monitoring based on RS image data，the Pseudo Invariant Features (PIF) method is often chosen by domestic researchers. However，when the RS image data are lack of temporally invariant features，they would make interference errors because of temporally variant features. Some mining environments contain large areas of vegetation and less areas for inhabitants. In such cases，the PIF method doesn’t work when it is used for relative radiometric normalization in the mining environment. The Temporally Invariant Cluster (TIC) method is thus introduced in this paper. TIC is a simple and effective method which creates a regression function thorough the high density of the temporally invariant features, so it wouldn’t be interrupted by the temporally variant features and is suitable for mining environment dynamic monitoring. The study area is a polymetallic ore deposit in southeast Hubei Province. The image is based on TM data. The TIC method was used in the NDVI. It is proved that this means can effectively reduce the radiometric difference, and that further analysis can be carried out based on the results obtained.

Keywords Satellite remote sensing Image processing Coastal evolution

TP 75

Issue Date: 20 September 2010

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ZHU Yan, ZHANG Zhi, ZHANG Qin, LIU Feng-Mei, LIU Wen-Ting. A Study of Relative Radiometric Normalization for Dynamic Monitoring of Environment Impacts of Mining Activities[J]. REMOTE SENSING FOR LAND & RESOURCES,2010, 22(3): 47-50.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.03.10 OR https://www.gtzyyg.com/EN/Y2010/V22/I3/47

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