Ordu Üniversitesi Bilgi Paketi / Ders Kataloğu

Ders Öğretim Planı

Dersin Kodu	Dersin Adı	Dersin Türü	Yıl	Yarıyıl	AKTS
TOB615	REMOTE SENSING IN AGRICULTURE	Zorunlu	1	2	6

Dersin Seviyesi

Yüksek Lisans

Dersin Amacı

resentation of remote sensing techniques, image processing and classification, using of Remote Sensing in natural resources.

Dersi Veren Öğretim Görevlisi/Görevlileri

Assist. Prof. Ferhat TÜRKMEN

Öğrenme Çıktıları

1	Students are learned Basic concepts of Remote Sensing
2	Satellites, sensors, data processing knows
3	Knows to use remote sensing for natural resources
4
5

Öğrenim Türü

Formal Education

Dersin Ön Koşulu Olan Dersler

None

Ders İçin Önerilen Diğer Hususlar

None

Dersin İçeriği

A brief description of the basic concepts and principles of remote sensing, The history of remote sensing, Information systems in Remote sensing, Projections systems, different satellite data sources and their characteristics, Digital geographic data integration with the of satellite data and uses, global positioning systems uses in remote sensing, Cameras and aerial photographs, geometric distortions Image processing, Image enhancement, Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis, Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis, Classification and interpretation of image data

Haftalık Ayrıntılı Ders İçeriği

Hafta	Teorik	Uygulama	Laboratuvar
1	A brief description of the basic concepts and principles of remote sensing,	Display data in Imagine Viewer
2	The history of remote sensing	Import data
3	Information systems in Remote sensing ,	Images compare
4	Projections systems	From image to image rectification
5	different satellite data sources and their characteristics,	Change the band combination
6	Digital geographic data integration with the of satellite data and uses	Shape files to produce and update
7	global positioning systems uses in remote sensing,	Produce images of the slope
8	Mid-term exam	Mid-term exam
9	Cameras and aerial photographs,	Produce images of Aspect
10	geometric distortions	Produce shaded relief images
11	Image processing,	Visibility analysis
12	Image enhancement,	Digital elevation model produce from the Line coverage data type
13	Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis,	Raster images produce from the contour lines
14	Using Erdas Imagine, images load, sources of errors in images, make corrections and analysis,	Supervised classification
15	Classification and interpretation of image data	Unsupervised classification
16	Final Exam	Final Exam

Ders Kitabı / Malzemesi / Önerilen Kaynaklar

Levin, N. 1999. Fundamentals of Remote Sensing. Hydrographic Data Management course, IMO - International Maritime Academy, Trieste, Italy Natural Resources Canada. Fundamentals of Remote Sensing. Erdas imagine basic. İşlem Companies Group Publications. 2002

Planlanan Öğrenme Aktiviteleri ve Metodları

Değerlendirme

Yarıyıl (Yıl) İçi Etkinlikleri	Adet	Değer
TOPLAM		0
Yarıyıl(Yıl) Sonu Etkinlikler	Adet	Değer
TOPLAM		0
Yarıyıl (Yıl) İçi Etkinlikleri		40
Yarıyıl (Yıl) Sonu Etkinlikleri		60
TOPLAM		100

Dersin Sunulduğu Dil

Staj Durumu

None

İş Yükü Hesaplaması

Etkinlikler	Sayısı	Süresi (saat)	Toplam İş Yükü (saat)
Midterm Examination	1	2	2
Final Examination	1	2	2
Attending Lectures	14	4	56
Report Preparation	5	8	40
Individual Study for Homework Problems	7	5	35
Individual Study for Mid term Examination	1	20	20
Individual Study for Final Examination	1	25	25
TOPLAM İŞ YÜKÜ (saat)			180

Program ve Öğrenme Çıktıları İlişkisi

	PÇ 1	PÇ 2	PÇ 3	PÇ 4	PÇ 5	PÇ 6	PÇ 7	PÇ 8	PÇ 9	PÇ 10
ÖÇ1	2		3	2
ÖÇ2	2	2					3
ÖÇ3			4	4	4	3
ÖÇ4
ÖÇ5

* Katkı Düzeyi : 1 Çok düşük 2 Düşük 3 Orta 4 Yüksek 5 Çok yüksek