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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| LANDSCAPE ARCHITECTURE (PhD) | |
| Code | PM558 |
| Name | Land Classification Techniques in Remote Sensing |
| Term | 2024-2025 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SÜHA BERBEROĞLU |
| Course Instructor |
Prof. Dr. SÜHA BERBEROĞLU
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
It aims to use the methods, software and algorithms used in the applications of Geographic Information Systems (GIS) for land classification techniques. Image processing techniques, GIS environment and terminologies are among the other objectives of the course.
Course Content
Definition of land use and cover, importance and uses of this information, remote sensing and land classification and its advantages, classification techniques used, algorithms and the basic elements of remote sensing (reflection, spatial resolution and time) are among the subjects of optimum use of land classification.
Course Precondition
There is no precondition
Resources
Lecture Notes, Books, Papers
Notes
All publications on the subject
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | To be able to develop and deepen their knowledge at the level of expertise in the same or a different field based on their master level qualifications. |
| LO02 | To be able to comprehend the interdisciplinary interaction related to the field. |
| LO03 | Analyzes advanced knowledge and develops an understanding based on competencies acquired at the graduate level, providing the foundation necessary for original studies in landscape planning and landscape design. |
| LO04 | Critical awareness of the problems of the nature, sources, knowledge production and testing of information in the interface between landscape planning and other fields related to the field of landscape design. |
| LO05 | To be able to use the theoretical and practical knowledge in the field of expertise. |
| LO06 | To be able to create new information by integrating the information in the field with the information from different disciplines; analyze the problems that require expertise by using scientific research methods. |
| LO07 | Gains the necessary cognitive and practical skills for the professional practice in graduate education. |
| LO08 | Apply gained knowledge, comprehension and problem solving skills in new and non-conventional environments, in a wider, interdisciplinary, multidisciplinary and disciplined context. |
| LO09 | To be able to construct a problem, to develop a solution method, to be able to solve the problem. |
| LO10 | To be able to develop new strategic approaches for solving problems and to be able to produce solutions by taking responsibility. |
| LO11 | To be able to critically evaluate the information related to the field, to direct learning and to carry out advanced studies independently. |
| LO12 | To be able to transfer the current developments and their studies to the groups in the field and outside the field in written, oral and visual form. |
| LO13 | To be able to examine social relations and the norms that direct these relations from a critical point of view, to develop them and to change them when necessary. |
| LO14 | To be able to use information and communication technologies at an advanced level with computer software. |
| LO15 | To be able to develop strategy, policy and implementation plans related to landscape planning and landscape design and to evaluate the obtained results within the framework of quality processes. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explains his/her knowledge at an expert level in the same or a different field, based on Master's level qualifications. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Uses the knowledge of the principles, processes and tools of Landscape Architecture together with solutions in the professional field. | |
| PLO03 | Beceriler - Bilişsel, Uygulamalı | Acquires the ability to work effectively in multi-disciplinary teams and the self-confidence to take responsibility and performs individual or multi-disciplinary work. | |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Collects data related to the field, analyzes and interprets the results. | 5 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | He/she follows the developments in science and technology and renews himself/herself on issues related to his/her field. | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | He/she conveys his/her studies produced in the graduate program in written, oral and/or visual formats in national and international platforms. | |
| PLO07 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | He/she independently carries out a study that requires expertise in his/her field. | |
| PLO08 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Analyzes the information analyzed during the collection, interpretation, implementation and announcement of the data related to the field by considering social, scientific, cultural and ethical values. | |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | It uses the knowledge and competence to reflect the philosophy, elements, principles and tools of landscape planning and design into the detailed landscape planning and design process. | |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Develops positive attitudes and behaviors regarding lifelong learning in the field of Landscape Architecture and adopts the universal conditions required by the profession. | |
| PLO11 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses advanced computer software, information and communication technologies at the level required by the field. | 4 |
| PLO12 | Yetkinlikler - Alana Özgü Yetkinlik | Presents plans and design proposals that are sensitive to society, area and nature for different landscape types. | |
| PLO13 | Yetkinlikler - Alana Özgü Yetkinlik | To be able to develop strategy, policy and implementation plans on issues related to his/her field and evaluate the results obtained within the framework of quality processes. | |
| PLO14 | Yetkinlikler - Alana Özgü Yetkinlik | Gains and applies the ability to identify, define, formulate and solve problems with related to the field. | |
| PLO15 | Yetkinlikler - Alana Özgü Yetkinlik | Acts in accordance with scientific and ethical values in all its work. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Remotely sensed data and characteristics | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım |
| 2 | Spatial, radiometric, temporal and spectral characteristics | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Image pre-processing and transformation | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Introduction to supervised classification | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Classification using maximum likelihood, Minimum distance, parallel pipe methods | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Introduction to non-parametric classification | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Introduction to artificial neural networks | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Preparation for exam | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Classification with support vector machines | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Classification with decision tree algorithms | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Classification accuracy | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | Unsupervised classification methods | Lecture notes, literature readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Pre-processing applications before classification | Lecture notes for laboratory practices | Öğretim Yöntemleri: Anlatım, Tartışma |
| 14 | Classification exercise | Lecture notes for laboratory practices | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 15 | Classification exercise and evaluation | Lecture notes for laboratory practices | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 16 | Term Exams | Preparation for exam | Ölçme Yöntemleri: Ödev |
| 17 | Term Exams and evaluation | Preparation for exam | Ölçme Yöntemleri: Ödev |
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 | ||