Microsoft Word remote sensing-booklet doc

Course Outline: Data Sources and Procurement, Data Formats (BSQ, BIL, 
BIP, etc.) Image Subsetting & Enhancement, Image Cleaning, Atmosphere 
Path Correction,, Image Mosiacing and Color Balancing, Image 
Rectification, Registration and Re-sampling, Band Ratios, Vegetation 
Indices, Image Filtering, Difference Images, Principal Component Analysis, 
Classification Schemes, Types, Algorithms, Field data collection, 
Qualitative and quantitative techniques, sampling techniques, Error 
matrices, Ground-Verification (Field Verification). Project (from third week 
students will be advised to commence their project work in a teamwork 
environment. Project work will be based on real life data sets obtained from 
resource monitoring agencies such as SUPARCO, SOP). 
Lab Outline: Intro to lab and software, Image Management (Import/Export 
& Display), Enhancement Techniques, Spectral and spatial digitizing 

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HEC — RS&GIS Curricula 2005
 
 
 22  
(image masking), Mosaicing and color balancing, Rectification and 
Registration and Re-sampling, Band Ratio, Vegetation Indices, Difference 
images, Image filters, Signature selection, Supervised, Unsupervised and 
Hybrid classification, ISODATA, MDM, MLC, and Baysian classification, 
Error Matrix Generation, Classification validation, field work