Geospatial Applications in Air Pollution Modeling - A case study of Tuticorin district in Tamil Nadu
For developing models for monitoring / keeping SPM within sustainable limits, a multispectral image is imported, georeferenced and classified via a supervised classification process, wherein ground truth information is used for creating the training set. The resultant class raster is edited to incorporate tag values representing levels of pollution manifested by the class raster of land cover. A surface raster of sustainability is created with data articulated within limits of air quality standards.

SPM pollution via model
The properties of hexagon grid cells - created via polygon grid process - are extracted from surface raster of sustainable SPM pollution (created via surface modeling process), prevailing air quality raster (created via supervised classification of multispectral image) and actual SPM pollution surface raster. A table with a computed field (with implied one-to-one attachment with polygon ID) for air quality records of hexagon cells is created. A theme map of records of computed field displays the spatial spread of air quality achieved via management formula for keeping the air quality standards. Following table indicates the changes statistically.
Comments
Geospatial applications for modeling air pollution include the following steps: importing, georeferencing, spatial data editing, surface modeling, relief shading, pseudo color editing, creating and using region, extracting and merging vectors, supervised classification, polygon grid sampling, extracting grid cell properties, and theme mapping.
The inputs for study came from Professor N.C. Chandrasekar and Mr. T. Jayasekar of VOCC, Tuticorin and Professor Victor Rajamanickam, of Tamil University, Thanjavur.
The study - for reasons of paucity of funds - is not exhaustive. Yet it vindicates the potential benefits of geospatial modeling of air pollution in rural, urban, and regional planning for activities of dwelling, working and amenities.
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