Experimental Study on Spectral Retrieval of Dustfall in Iron Ore Areas Under Multi-background Conditions

doi:10.12068/j.issn.1005-3026.2022.11.012

Abstract

Abstract: Dust pollution is serious in some mining areas. Remote sensing could monitor dustfall comprehensively and rapidly. Four kinds of typical backgrounds were selected to carry out iron dustfall spectroscopy measurement to study the accuracy difference of dustfall retrieval. The results show that the retrieval accuracy of plant background was the highest(error is 4.92g/m²) based on 900nm spectral absorption index(SAI)in the hyperspectral model(350~2500nm). By retrieving from the dominant band obtained by the statistical method， the retrieval accuracy on the plant and linoleum roof was relatively high(error is 6.02 and 7.35g/m²， respectively). For the multi-spectral model(according to Landsat-8 OLI bands)， the retrieving accuracy on the plant and linoleum roof was also high in the 7th band(error is 6.19 and 7.93g/m²， respectively). In summary， the dustfall retrieval accuracy under the plants background is the highest， which can be used as the first choice for dust fall remote sensing monitoring; if it is limited by the growing season， the background of linoleum roof can be the first choice. If there is no hyperspectral data， the 7th band of multispectral should be the first choice.

Key words: iron ore area; dustfall; inversion accuracy; multi-background; spectra

CLC Number:

P237

MA Bao-dong， YANG Xiang-ru， LIU Quan， CHE De-fu. Experimental Study on Spectral Retrieval of Dustfall in Iron Ore Areas Under Multi-background Conditions[J]. Journal of Northeastern University(Natural Science), 2022, 43(11): 1607-1612.

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