Estimation of PM10 Distribution using Landsat 7 ETM+ Remote Sensing Data

Ajay Roy, Anjali Jivani, Bhuvan Parekh, (doi: 10.23953/cloud.ijarsg.284)


Remote sensing imagery is a rich source of information with applications in varied fields. Monitoring of environment pollution is one of them. The work presented in this paper is focused on estimation of the ambient concentration of pollutant using remote sensing. Particulate Matter with particle sizes less than 10 microns (PM10) is estimated for the study area Vadodara. Landsat 7 ETM+ data of different wavelength has been processed and analyzed for the relationship with coincident ground station PM10 data. The radiance values observed by the satellite and its difference with the radiance calculated after atmospheric correction for the same pixel is considered as a measure to estimate PM10. This difference, called path radiance is calculated and correlated with the ground station PM10 values. Using regression analysis on the calculated data and the ground station PM10 data, the algorithm for PM10 estimation is generated and PM10 map is generated for the study area. The algorithm shows good results for the test data. Pollution estimation through remote sensing is an efficient technique as it can be carried out in less time. Estimation and analysis for larger area is possible using remote sensing approach. The 30 meter resolution of Landsat satellite makes it more suitable for local and regional study.


Landsat ETM+; PM10; Remote Sensing

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