Title

Article text.

-- Beata Hejmanowska - 2020-04-29

Lectures

Lecture1 .pdf

Lecture2.ppt

Lecture3.pdf

Lecture4.pdf

Lecture5.pdf

Lecture6.pdf

test_image.rar - ILWIS data for mmanual image classification

test_xls.rar - corresponding xls file

Lecture7.ppt

Lecture8.pdf

collinearity equation xls

Riegl TLS

Introduction to Terrestrial Laser Scanning

Details_concerning_exam_2013_01.tif

__________________________________________________________________________

LABORATORIES

Laboratory1 - Introduction

Laboratory2 - Landsat satellite image – initial analysis

Laboratory3 - Landsat satellite image – supervised classification

Laboratory4 - Landsat satellite image – quantitative analysis

Laboratory5 - Photomap creation

Laboratory6 - Orthophotomap creation

Laboratory7 - Airborne model orientation, 3D

__________________________________________________________________________________

EXAM – theoretical questions:

1. Digital image – definition, DN, mininum metadata, formats
2. Histogram – definition, graphic presentation, statistics
3. Histogram stretching, linear, with saturation, color composition
4. Landsat system, resolution: spatial, radiometric, spectral and temporal
5. Bilans of the electromagnetic energy on the earth ( coefficients: reflection, scattering, transmition, absorbtion, emissivity)
6. Interaction of EM radiation in the atmosphere (atmospheric windows)
7. Spectral curve: definition, exapmples: water, vegetaion, soil
8. Automatic image classification: steps, argorithms (box, mindist, maxlike), accuracy assessment
9. Albedo calculation for Landsat images
10. Temperature calculation from Landsat image: Planck's, Wien's, Stefan-Boltzman's law, radiant and kinetic temperature

11. Georeferencing, sources of the errors on the image


EXAM – practical excercises
1. Image histogram, stretching, color composite
2. Supervised classification (also manually)
3. Accuracy analysis

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