18 th Esri India User Conference 2017 Page 1 of 9 Hyperspectral Remote Sensing Data Analysis using Dimensionality Reduction Techniques Ankur Rana 1 , Arnab Saha 2 , Pradeep K. Garg 3 , Sewata Tomar 4 1, 2 Research Fellow, Uttarakhand Technical University, Dehradun, U.K., India 3 Professor, Uttarakhand Technical University, Dehradun, U.K., India 4 Student, Amity Institute of Geoinformatics and Remote Sensing, Amity University, Noida, U.P., India Word Limit of the Paper should not be more than 3000 Words = 7/8 Pages) Abstract: Hyperspectral image processing represents an important mechanism for remote sensing of the Earth. Nowadays, hyper spectral image software’s becomes extensively used. Hyperspectral images provide more information about bands and their high dimensionality. A critical task in hyper spectral data processing is to decrease the redundancy of the spectral and spatial information without losing any valuable details. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) Hyperspectral data consists of 425 bands out of which 425 calibrated/useful bands are available for Hyperspectral applications. This paper analyses the dimensionality reduction techniques and the data processing steps for both atmospheric and topographic correction of hyperspectral data acquired by the AVIRIS over the snow cover of the Patsio glacier in Dhundi region of Himachal Pradesh, India. Bands conserving maximum information are selected based on the maximum value of statistical measures. End members are extracted from the selected bands and their spectral signatures are determined. Preprocessing step which includes fixing bad pixels, local destriping, FLAASH atmospheric correction, principal component analysis (PCA), minimum noise fraction (MNF) smoothing using ENVI 5.3 software and effort polishing provide improved results. PCA and MNF applied to the hyperspectral calibrated bands reduced the dimensionality of the data and all maps have been prepared by using ArcGIS 10.4.3 software. Keywords: PPI, MNF, FLAASH, AVIRIS About the Author: Mr. Ankur Rana Currently, JRF in Uttrakhand Technical University, Dehradun in Snow and Glacier studies project. Completed M.Tech in Geo-informatics and Remote Sensing from Amity University. E mail ID: ranaankur1991@gmail.com Contact: +91 9758692698 Mr. Arnab Saha Currently, JRF in Uttrakhand Technical University Dehradun in Snow and Glacier studies project. Completed M.Tech in Geo-informatics and Remote Sensing from Amity University. Post-Graduation Diploma in Remote Sensing and GIS from IIRS, ISRO Dehradun. Had done B.Tech in Civil Engineering. Area of interest lies in hydrology, climate change and hydrological modelling. Prof. P.K. Garg Professor, Uttarakhand Technical University, Dehradun. Ex- HOD, IIT Roorkee, India Ms. Sewata Tomar Currently completed M.Sc. in Geographical Information System and Remote Sensing from Amity University Sec 125 Noida.