Lrm 111 assignment 2 (case study-2) 12.12.2016

1. SOKOINE UNIVERSITY OF AGRICULTURE
COLLEGE OF AGRICULTURE
DEPARTMENT OF ENGINEERING SCIENCES AND TECHNOLOGY
REMOTE SENSING AND GIS LABORATORY
Course LRM 111: Introduction to Remote Sensing
Assignment-2 (Case Study-2)
1st
SEMESTER B.Sc. Irrigation and Water Resources Engineering (B.Sc. IWRE)
Instructor(s): Prof. D.N. Kimaro
Dr. Proches Hieronimo
Date: 13 December 2016
Remotely sensed data are received from imaging sensors mounted on satellite/aerial platforms generally
containing flaws or deficiencies. The correction of deficiencies and the removal of flaws present in the remote
sensing data are termed pre-processing (sometimes referred to as image restoration or image correction or
image rectification).
Likewise image enhancement can be carried out after pre-processing in order to convert the image quality to a
better and more understandable level for feature extraction or image interpretation. Image enhancement Improve
the appearance of the imagery to assist in visual interpretation and analysis. It is important to emphasise here
that after pre-processing, the image needs to be enhanced i.e. enhancement of image characteristics
(radiometric, spectral and spatial) for visual interpretation. In other words enhancement improves the visual
identification of the information of greatest interest to the user. Various image enhancement techniques are
available to improve visual interpretation
The purpose of this assignment is to study and write notes on pre-processing operations that are used to prepare
data for subsequent analysis after attempting to correct or compensate for the errors. Also to write notes on
various enhancement techniques available to improve interpretation of remotely sensed data.
For each practical group write notes on the tasks given in the Table below:
Practical Group No Task
1 Image enhancement
i. Contrast enhancement
ii. Spatial filtering
iii. Image reduction
2 Image enhancement
i. Image magnification
ii. Indices and ratioing
iii. Colour compositing
3 Geometric correction of remotely sensed data
i. Systematic corrections
ii. Non-systematic corrections
iii. Miscellaneous pre-processing
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2. 4 Radiometric corrections
1. Detector response calibration: (i) De-striping, (ii) (iii) Removal of
missing scan line, (iv) Random noise removal, (v) Vignetting
removal
5 Radiometric corrections
i. Sun angle and topographic corrections
ii. Atmospheric corrections
Prepare a Group assignment/Case Study report. Submit your Group report (hard and soft copy) by 16 January
2016 before 12:30 pm. Submit your soft copy by e-mail.
Note that the all group reports should be shared among all students just after the group report is submitted.
Expect questions in the semester examination from this assignment.
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