Simulation of the Hyperspectral Data from Multispectral Data Using Open Source Programming Environment

Abstract

Multispectral remote sensing (MSS) sensors have been generally utilized for acquiring and extracting information of Land Use Land (LULC) Cover features in the past few decades. MSS sensor generally acquires data in the small window of spectral bands hence, it is not capable of distinguishing spectrally similar features. On the other hand, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of earth surface. But HRS sensors are very few in number because of the requirement of sensitive detectors, large storage capacities which make the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MSS data for detailed LULCstudies. One of the technique is by Simulation of HRS data using available MSS data. In the present study spectral reconstruction approach is used for the simulation of hyperspectral data using EO-1 ALI multispectral data in open source programming. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

Varun Tiwari

PhD Candidate

I am a Ph.D. student with the Center for Geospatial Analytics at North Carolina State University.