Abstract
Remote sensing (RS) and geographic information systems (GIS) techniques have become very important these days as they aid planners and decision makers to make effective and correct decisions and designs. Principal component analysis (PCA) involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. It reduces the dimensionality of the data set and identifies a new meaningful underlying variable (Gajbhiye and Sharma 2015a, b; Gajbhiye 2014; Gajbhiye 2015a, b). Morphometric analysis and prioritization of the sub-watersheds of Mohgaon River Catchment, Mandla district in Madhya Pradesh State, India, are carried out using RS and GIS techniques using satellite imageries and topographic maps. In this study, we apply PCA technique for redundancy of morphometric parameters and find the more effective parameters for prioritization of the watershed. The PCA produced more effective parameter form factor (R f), drainage texture (T) and length of overland flow (L o). Finally, the results of PCA reflect a good look on the prioritization of watershed.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call