Ordu University Lifelong Learning Programme

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
TOB615	REMOTE SENSING IN AGRICULTURE	Compulsory	1	2	6

Level of Course Unit

Second Cycle

Objectives of the Course

resentation of remote sensing techniques, image processing and classification, using of Remote Sensing in natural resources.

Name of Lecturer(s)

Assist. Prof. Ferhat TÜRKMEN

Learning Outcomes

1	Students are learned Basic concepts of Remote Sensing
2	Satellites, sensors, data processing knows
3	Knows to use remote sensing for natural resources
4
5

Mode of Delivery

Formal Education

Prerequisites and co-requisities

None

Recommended Optional Programme Components

None

Course Contents

A brief description of the basic concepts and principles of remote sensing, The history of remote sensing, Information systems in Remote sensing, Projections systems, different satellite data sources and their characteristics, Digital geographic data integration with the of satellite data and uses, global positioning systems uses in remote sensing, Cameras and aerial photographs, geometric distortions Image processing, Image enhancement, Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis, Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis, Classification and interpretation of image data

Weekly Detailed Course Contents

Week	Theoretical	Practice	Laboratory
1	A brief description of the basic concepts and principles of remote sensing,	Display data in Imagine Viewer
2	The history of remote sensing	Import data
3	Information systems in Remote sensing ,	Images compare
4	Projections systems	From image to image rectification
5	different satellite data sources and their characteristics,	Change the band combination
6	Digital geographic data integration with the of satellite data and uses	Shape files to produce and update
7	global positioning systems uses in remote sensing,	Produce images of the slope
8	Mid-term exam	Mid-term exam
9	Cameras and aerial photographs,	Produce images of Aspect
10	geometric distortions	Produce shaded relief images
11	Image processing,	Visibility analysis
12	Image enhancement,	Digital elevation model produce from the Line coverage data type
13	Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis,	Raster images produce from the contour lines
14	Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis,	Supervised classification
15	Classification and interpretation of image data	Unsupervised classification
16	Final Exam	Final Exam

Recommended or Required Reading

Levin, N. 1999. Fundamentals of Remote Sensing. Hydrographic Data Management course, IMO - International Maritime Academy, Trieste, Italy Natural Resources Canada. Fundamentals of Remote Sensing. Erdas imagine basic. İşlem Companies Group Publications. 2002

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
SUM		0
End Of Term (or Year) Learning Activities	Quantity	Weight
SUM		0
Yarıyıl (Yıl) İçi Etkinlikleri		40
Yarıyıl (Yıl) Sonu Etkinlikleri		60
SUM		100

Language of Instruction

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	2	2
Final Examination	1	2	2
Attending Lectures	14	4	56
Report Preparation	5	8	40
Individual Study for Homework Problems	7	5	35
Individual Study for Mid term Examination	1	20	20
Individual Study for Final Examination	1	25	25
TOTAL WORKLOAD (hours)			180

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6	PO 7	PO 8	PO 9	PO 10
LO1	2		3	2
LO2	2	2					3
LO3			4	4	4	3
LO4
LO5

* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High