Information
Code | UA502 |
Name | Remote Sensing and Applications in Agriculture |
Term | 2022-2023 Academic Year |
Semester | . Semester |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 6 ECTS |
National Credit | 3 National Credit |
Teaching Language | Türkçe |
Level | Yüksek Lisans Dersi |
Type | Normal |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Prof. Dr. MEHMET EREN ÖZTEKİN |
Course Goal / Objective
What kind of information can be obtained in agriculture by using satellite imagery. The use of this information in the development of agriculture
Course Content
How to use remote sensing in agriculture
Course Precondition
none
Resources
Lecture Notes
Notes
Lecture Notes of ITU
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | has learn the concept of remote sensing |
LO02 | Has knowledge on the use and applications of Remote Sensing in Agriculture |
LO03 | Has basic knowledge on monitoring and mapping of the soils using Remote Sensing |
LO04 | Developes the understanding of monitoring temporal changes and presents land use |
LO05 | Has basic knowledge on monitoring and mapping of the vegetation using Remote Sensing |
LO06 | Has learn to interpretation of satellite images |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory | 3 |
PLO02 | Bilgi - Kuramsal, Olgusal | The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data | 4 |
PLO03 | Bilgi - Kuramsal, Olgusal | The students generate information using remotely sensed data and GIS together with database management skills. | 4 |
PLO04 | Bilgi - Kuramsal, Olgusal | The students develop the necessary skills for selecting and using appropriate techniques and tools for engineering practices, using information technologies effectively, and collecting, analysing and interpreting data. | |
PLO05 | Bilgi - Kuramsal, Olgusal | The students gain knowledge to use current data and methods for multi-disciplinary research | |
PLO06 | Bilgi - Kuramsal, Olgusal | The students gain technical competence and skills in using recent GIS and remote sensing software | 3 |
PLO07 | Bilgi - Kuramsal, Olgusal | The students acquire knowledge on potential practical fields of use of remotely sensed data, and use their theoretical and practical knowledge for problem solution in the related professional disciplines. | |
PLO08 | Yetkinlikler - Öğrenme Yetkinliği | Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data. | 3 |
PLO09 | Yetkinlikler - Öğrenme Yetkinliği | Students can generate data for GIS projects using Remote Sensing techniques. | 3 |
PLO10 | Bilgi - Kuramsal, Olgusal | Gains the ability to analyze and interpret geographic data with GIS techniques | |
PLO11 | Bilgi - Kuramsal, Olgusal | Gains the ability of problem solving, solving, solution oriented application development | |
PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Acquires the ability to acquire, evaluate, record and apply information from satellite data |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Applications Of Remote Sensing in different dicipline | Lecturing | Öğretim Yöntemleri: Anlatım |
2 | Reflactance and elektro magnetic spectrum | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
3 | Sensors and their properties. | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
4 | Soil reflection characteristics and factors affecting reflection 1 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
5 | Soil reflection characteristics and factors affecting reflection 2 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
6 | Vegetation reflection characteristics and factors affecting reflection 1 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
7 | Vegetation reflection characteristics and factors affecting reflection 2 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
8 | Mid-Term Exam | Ölçme Yöntemleri: Sözlü Sınav |
|
9 | Detection of land use by using satellite image 1 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
10 | Detection of land use by using satellite image 2 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
11 | Use of different satellite images in agriculture 1 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
12 | Use of different satellite images in agriculture 2 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
13 | Identification of disease in plants using remote sensing techniques 1 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
14 | Identification of disease in plants using remote sensing techniques 2 | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
15 | Mapping of soils using remote sensing techniques | Lecturing and practice | Öğretim Yöntemleri: Anlatım |
16 | Term Exams | Ölçme Yöntemleri: Sözlü Sınav |
|
17 | Term Exams | Ölçme Yöntemleri: Sözlü Sınav |
Student Workload - ECTS
Works | Number | Time (Hour) | Workload (Hour) |
---|---|---|---|
Course Related Works | |||
Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
Final Exam | 1 | 30 | 30 |
Total Workload (Hour) | 157 | ||
Total Workload / 25 (h) | 6,28 | ||
ECTS | 6 ECTS |