Digital Numbers, Reflectance, and Atmospheric Correction in Remote Sensing

Abstract

This study focuses on the radiometric transformation of two Landsat images (the first is an ETM+ image acquired on September 23, 2001 and the second is a TM image from June 17, 2003) covering portions of the foothills and mountains west of Calgary, Alberta. A total of four radiometric transformation techniques; viz.converting raw DNs to radiance, converting radiance to TOA reflectance, absolute atmospheric correction using PCI‟s atmospheric correction package and atmospheric normalization via relative atmospheric correction using the liner transformation method, were used on the images.The accuracy assessment suggests that for our study site, atmospheric normalization via relative atmospheric correction using the linear transformation method is the most effective with the RMSE value of 9.5955 and absolute atmospheric correction using PCI‟s atmospheric correction package is the least effective with the RMSE value of 15.0371.

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Download and Integration of Earth Observing System (EOS) data

Introduction

The Earth Observing System (EOS) instruments are designed to collect data to provide a comprehensive overview of the dynamic components of the Earth’s atmosphere, land and water surfaces (Campbell 2007). ‘The EOS is one of the primary components of a NASA-initiated concept which includes numerous platforms and sensors, including the Terra and Aqua spacecrafts. There are five sensors included on Terra and MODIS (Moderate Resolution Imaging Spectro-Radiometer) is one of them. MODIS is a sensor that is intended to provide comprehensive data about land, ocean, and atmospheric processes simultaneously’ (Lillesandet al.2004). In this study,MODIS Terra vegetation indices are used to create a NDVI map for Alberta province in Canada. The main objectives of the study are to become familiar with the variety of remote sensing data sources accessible through the internet; gain experience in accessing, obtaining and integrating data from disparate online sources; enhance knowledge about different file formats and appropriate conversion and re-projection process; and finally to develop cartographic skills to display the appropriate map message. 

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Report on Multiband Images,Colour Compositing, and Contrast Enhancement

Introduction

Image analysis by photo-interpretation is often facilitated when the radiometric nature of the image is enhanced to improve its visual impact. Specific differences in vegetation and soil types, for example, may be brought out by increasing the contrast of an image. Similarly the differences in brightness value can be highlighted either by contrast modification or by assigning quite different colors to those levels (Richards, 1989). This study presents a variety of image enhancement procedures often used with remote sensing image data. 

Objectives of study
i) To explore the basic capabilities of PCI Geomatica software,
ii)To introduce colour composites, histograms, and scatterplots as tools for exploring image data stored in database channels, and
iii)To learn about contrast enhancements, and the impact of the different enhancement types on raw imagery.

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