COURSE SYLLABUS

REMOTE SENSING AND AGRICULTURAL APPLICATIONS

1	Course Title:	REMOTE SENSING AND AGRICULTURAL APPLICATIONS
2	Course Code:	TPR4913-S
3	Type of Course:	Optional
4	Level of Course:	First Cycle
5	Year of Study:	4
6	Semester:	7
7	ECTS Credits Allocated:	3
8	Theoretical (hour/week):	1
9	Practice (hour/week) :	2
10	Laboratory (hour/week) :	0
11	Prerequisites:	none
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. ERTUĞRUL AKSOY
16	Course Lecturers:	Doç. Dr. Gökhan ÖZSOY
17	Contactinformation of the Course Coordinator:	Uludağ Üniversitesi, Ziraat Fakültesi, Toprak Bilimi ve Bitki Besleme Bölümü 16059 Görükle Kampüsü, Nilüfer/Bursa Tel: 0-224-2941534 E-posta: aksoy@uludag.edu.tr
18	Website:
19	Objective of the Course:	To gain knowledge and skills about the principles of Remote Sensing (RS), tools used in RS, software and digital data, RS application areas, RS applications in agriculture and natural resources monitoring.
20	Contribution of the Course to Professional Development	Knows the basic principles of remote sensing and remote sensing techniques. does production and area prediction in agriculture by using remote sensing program and satellite images.

Learning Outcomes:

1	To describe the definition of RS, basic principles and elements of RS, areas of general and agricultural use of RS.;
2	To define the properties of remote sensing hardware and software commonly used in Turkey and in the World.;
3	To define the basic elements of RS, digital data sources and methods of obtaining data.;
4	To apply the basic RS techniques for to monitor and manage natural resources such as soil, water and forest and to product and area estimation in agriculture;
5	To follow the innovations on RS applications for monitoring, protecting and developing natural resources in Turkey and in the World.;

22	Course Content:

Week	Theoretical	Practical
1	-Introduction -Definition of Remote Sensing (RS) and the history of RS.	Introducing remote sensing and GIS laboratory.
2	Physical components of RS	Software and hardware systems used for RS.
3	Electromagnetic Spectrum, color theory and Color composite images.	Computer Application
4	Reflection characteristics of the natural and cultural objects.	Computer Application
5	The satellites and sensors used in RS.	Computer Application
6	Satellite data selection.	Computer Application
7	Features and application areas of satellite images and aerial photographs	Satellite images and Panchromatic and color aerial photographs
8	Basic principles of Photogrametry and maps.	Computer Application
9	Preprocessing in RS data.	Computer Application
10	Generating information from RS data	Computer Application
11	Visual interpretation in RS	Computer Application
12	Multi spectral classification in RS ( product and area prediction)	Computer Application
13	RS applications in agriculture and natural resources management; unmannned aerial vehicle (UVA) and using in agiculture	Computer Application
14	presentation of project assignments and an general overview of the term	Computer Application General evaluation of semestre (home-work reports and result of practice exam. Disclosure of possible errors.)

23	Textbooks, References and/or Other Materials:	Sesören, A., 1999. Uzaktan Algılamada Temel Kavramlar. Mart Matbaacılık, İstanbul. Lillesand, T.M., Kiefer, R.W., 2000. Remote Sensing and Image Intrpretation. Fourth Ed. John. Wiley and Sons, Inc., New York, 710 pp. Aronoff, S. 2005. Remote Sensing for GIS Managers. ESRI press, Redlands, California, USA. 487p. Buiten , H.J., Clevers J.G.P.W., 1993. Land Observation By Remote Sensing Theory and Applications. Wageningen Agricultural Uni. The Netherlands. Gordon and Breach Sience Publishers. Shresta, D.P., 1991. An Introduction to Remote Sensing From Space. ITC, International Institute for Aerospace Survey and Earth Sciences
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	20
Quiz	0	0
Homeworks, Performances	2	20
Final Exam	1	60
Total	4	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Midterm exam, homework, attandes performance to lecture, practice and final exam
Information	For success, it is necessary to attend the course practises, submit homework, get the required grades from the midterm, paractice and final exam.

ECTS / WORK LOAD TABLE

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High