GEOSS: an intelligent methodology for identifying site suitability of air sample collection Online publication date: Mon, 09-Nov-2020
by Kamonasish Mistry; Biplab Biswas; Siwen Zhang; Tao Wu; Liang Zhou; Abdelfettah Benchrif; Srimanta Gupta
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 19, No. 5, 2020
Abstract: Air pollution (AP) types and levels change with changes in land use land cover (LULC) types. However, there is no such attempt to develop any common methodology or model for optimum sampling which can be correlated between LULC types and changes with the AP level types and changes. A pre-planned, well-calculated geospatial method is needed to evaluate the ambient AP level, type and its variation over different LULC types. 'GEOSS' (geospatial estimation of optimum sample site) has been innovated to identify the optimum AP sampling sites so that it can represent the wide spatial coverage over varied LULC types. Classified satellite images and statistical tools are used to optimize sampling locations. Validation approach based on nearest neighbour analysis (NNA) has justified that GEOSS employed sampling points are systematically distributed and fulfilled all the basic assumptions of the present sampling procedure.
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