PM587 Remote Sensing Environmental Change Detection and Time Series Analysis

6 ECTS - 3-0 Duration (T+A)- 1. Semester- 3 National Credit

Information

Unit INSTITUTE OF NATURAL AND APPLIED SCIENCES
LANDSCAPE ARCHITECTURE (MASTER) (WITH THESIS)
Code PM587
Name Remote Sensing Environmental Change Detection and Time Series Analysis
Term 2018-2019 Academic Year
Term Fall
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. HAKAN ALPHAN
Course Instructor
The current term course schedule has not been prepared yet.


Course Goal / Objective

Drought, floods, extreme natural events

Course Content

Concepts of natural and technological risks.

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understands change detection based on digital image processing on the basic level
LO02 Decides the correct procedures about image processing prior to operations when necessary
LO03 Learns change detection methods based on digital image processing
LO04 Decides appropriate analysis approaches to produce digital data which is required to deal with the problem
LO05 Expresses change information through maps and statistics


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Analyzes the information obtained during the collection, interpretation and application of data related to the field, taking into account social, scientific, cultural and ethical values. 2
PLO02 Bilgi - Kuramsal, Olgusal Describes current knowledge in the same or a different field, based on undergraduate level qualifications.
PLO03 Beceriler - Bilişsel, Uygulamalı Gains and applies the ability to identify, define, formulate and solve engineering problems. 3
PLO04 Beceriler - Bilişsel, Uygulamalı Collects data related to the field, analyzes and interprets the results. 4
PLO05 Beceriler - Bilişsel, Uygulamalı Uses the knowledge of the principles, processes and tools of Landscape Architecture together with solutions in the professional field.
PLO06 Beceriler - Bilişsel, Uygulamalı Works effectively individually or by taking responsibility in multi-disciplinary teams. 3
PLO07 Beceriler - Bilişsel, Uygulamalı He/she follows the developments in science and technology and renews himself/herself on issues related to his/her field. 3
PLO08 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği He/she independently carries out a study that requires expertise in his/her field. 3
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği It uses the knowledge and competence to reflect the philosophy, elements, principles and tools of landscape design into the detailed landscape 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. 5
PLO12 Yetkinlikler - İletişim ve Sosyal Yetkinlik Landscape Architecture uses contemporary communication methods to develop and explain ideas and presents them visually, verbally or in writing.
PLO13 Yetkinlikler - Alana Özgü Yetkinlik It adopts the principle of complying with scientific and ethical values in all its works.
PLO14 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.
PLO15 Yetkinlikler - Alana Özgü Yetkinlik Evaluates the knowledge and skills acquired in the field with a critical approach.
PLO16 Yetkinlikler - Alana Özgü Yetkinlik It presents plans and design proposals that are sensitive to society, area and nature for different landscape types.


Week Plan

Week Topic Preparation Methods
1 Introduction to digital image processing for change detection. Announging scopes of micro-projects and formation of project groups Lecture, Brainstorming, Question and Answer, Discussion
2 Pre-processing requirements for change detection, their significance level, overview and classification of change detection methods Lecture, Brainstorming, Question and Answer, Discussion
3 Image algebra methods: Image differencing, image ratioing,image regression, and change vector analysis Lecture, Brainstorming, Question and Answer, Discussion
4 Image algebra methods: Binary change detection, and, labeling change detection Lecture, Brainstorming, Question and Answer, Discussion
5 Image algebra methods: Change detection using vegetation indices such as NDBI made by using NDVI, SAVI, MSAVI Lecture, Brainstorming, Question and Answer, Discussion
6 Image transformation methods, Principal components analysis (PCA), Kauth-Thomas (Tasseled Cap) and Gramm-Schmidt transformations Lecture, Brainstorming, Question and Answer, Discussion
7 Transforming bi-temporal and multitemporal data Lecture, Brainstorming, Question and Answer, Discussion
8 Mid-Term Exam Written examination
9 Classification method: post-classification comparison, spectral and temporal mixture analysis, expectation maximization, unsupervised classification, etc. Lecture, Brainstorming, Question and Answer, Discussion
10 Advanced methods of change detection Lecture, Brainstorming, Question and Answer, Discussion
11 GIS and other analysis methods Lecture, Brainstorming, Question and Answer, Discussion
12 Change detection for forest, urban, agriculture and wetland areas Lecture, Brainstorming, Question and Answer, Discussion
13 Advantages and disadvantages of selecting appropriate change detection procedure , determiners and constraints in fictionalization of ideal change detection Lecture, Brainstorming, Question and Answer, Discussion
14 Project presentations Lecture, Brainstorming, Question and Answer, Discussion
15 Project presentations Lecture, Brainstorming, Question and Answer, Discussion
16 Term Exams Written examination
17 Term Exams Written examination


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

Update Time: 22.04.2025 04:15