UA0023 Remote Sensing Classification Programs

6 ECTS - 3-1 Duration (T+A)- . Semester- 3.5 National Credit

Information

Code UA0023
Name Remote Sensing Classification Programs
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-1 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3.5 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal / Objective

To analyze the accuracy of classification programs prepared with ready-made programs used in remote sensing.

Course Content

What is an image, the types of images taken from satellites, the closest probability, the nearest neighbor, the condensed nearest neighbor, the new algorithm "condensed nearest neighbor", the introduction and applications of programs such as ellipsoid, plant index. and the work and performance of ready-made programs

Course Precondition

none

Resources

remote sensing

Notes

https://books.google.com.tr/books?id=OSFGd3jrUO4C&printsec=frontcover&dq=remote+sensing&hl=tr&sa=X&redir_esc=y#v=onepage&q=remote%20sensing&f=false


Course Learning Outcomes

Order Course Learning Outcomes
LO01 learns smallest image cell
LO02 Understands the differences between analog and digital images
LO03 what is resolution? pixel differences of satellites
LO04 What are the image bands of the satellites, which bands are applied for which examination, learn the differences


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. 3
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. 2
PLO06 Bilgi - Kuramsal, Olgusal The students gain technical competence and skills in using recent GIS and remote sensing software. 5
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. 5
PLO08 Yetkinlikler - Öğrenme Yetkinliği Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data. 4
PLO09 Yetkinlikler - Öğrenme Yetkinliği Students can generate data for GIS projects using Remote Sensing techniques. 2
PLO10 Bilgi - Kuramsal, Olgusal Gains the ability to analyze and interpret geographic data with GIS techniques. 3
PLO11 Bilgi - Kuramsal, Olgusal Gains the ability of problem solving, solving, solution oriented application development. 2
PLO12 Yetkinlikler - Öğrenme Yetkinliği Acquires the ability to acquire, evaluate, record and apply information from satellite data. 4


Week Plan

Week Topic Preparation Methods
1 what is image? lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Soru-Cevap
2 What is analog and digital image? lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım
3 Description and characteristics of satellites lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım
4 What is a pixel? lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım, Gösteri
5 What is resolution? lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Gösterip Yaptırma
6 meaning of pixel resolutions lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım
7 Image bands of satellites lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Ölçme Yöntemleri:
Sözlü Sınav
9 With which image bands, ground objects are determined best lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Anlatım
10 Sample selection for test sites and classification lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Gösterip Yaptırma
11 training classification lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Gösterip Yaptırma
12 cluster classification lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Gösterip Yaptırma
13 introduction and applications of classification programs lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Alıştırma ve Uygulama
14 Introduction and applications of class attendance classification programs lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Alıştırma ve Uygulama
15 introduction and applications of classification programs sample programs lecture, question-answer, discussion, research and application Öğretim Yöntemleri:
Alıştırma ve Uygulama
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 4 56
Out of Class Study (Preliminary Work, Practice) 14 4 56
Assesment Related Works
Homeworks, Projects, Others 1 1 1
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 28 28
Total Workload (Hour) 153
Total Workload / 25 (h) 6,12
ECTS 6 ECTS

Update Time: 15.01.2023 02:20