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Lecture 1

Open source concepts, installation of QGIS and GRASS 6.4 under Windows XP and other OS

1. QGIS for students
2. Course data
3. Introduction to Quantum GIS

Lecture 2

First steps in GRASS using the GRASS plugin, planning a GRASS project area, region settings, deleting maps and projects

1. First steps in Quantum GIS

Lecture 3

Georeferencing of topographic raster maps as basic information, geocoding of aerial photos

1. Georeferencing a topographic map
2. Georeferencing an aerial photograph
3. Mosaicing

Lecture 4

WebGis and Database applications, coordinate and datum transformations. Assigning color tables, image statistics, histogram, color composites, subsets and multilayer stacking

1. Load a WMS-Layer
2. OpenStreet Map layer
3. Reprojection of vectors
4. Reprojection of rasters# Color tables
5. Color composites

Lecture 5

Import and processing of digital terrain models (DTM), filling missing values, DEM profiles, calculating slope, aspect and contour lines, 3D visualization and shaded relief

1. Creating a DEM from vector data
2. The Profile plugin
3. Terrain analysis
4. Evaluation of digital elevation models

Lecture 6

Download and Processing of GPS data. Geocaching, GPS tracking, creation of waypoints, updating Open Street Map layers

1. The GPS tools plugin
2. Defining an own custom Spatial Reference System (SRS)
3. Creating GPS waypoints
4. Outdoors with the GPS receiver
5. Using the GPS Tracking Plugin
6. Download from GPS receiver
7. Digital photo links with the eVIS plugin

Lecture 7

Radiometric corrections, atmospheric effects. Introduction to raster algebra, atmospheric effects, cloud masking and haze reduction, image fusion (IHS, Brovey)

1. Image fusion using color transformations
2. Brovey Transformation
3. Automated cloud detection

Lecture 8

Vegetation indices, tasseled cap transformation

1. Principal components analysis (PCA)
2. Normalized Difference Vegetation Index (NDVI)
3. Image subtraction
4. Spectral ratioing
5. Tasseled cap

Spatial filtering

1. Geometric feature analysis with matrix filters
2. Defining filters
3. Low pass filter
4. High pass filter
5. Edge detection
6. Texture features

Lecture 9

Theory of vector topology, visual interpretation of remote sensing imagery, mapping of land cover polygons and roads, topology management

1. CORINE LUCCS (Land use / cover classification system)
2. Creating new vector layers

Digitizing

1. Configure digitizing options
2. Digitizing

Sampling tools

1. Random sampling
2. Systematic sampling with circular sampling plots
3. Construction of a regular grid
4. Using external information sources as reference for training site delineation
5. Digitizing reference areas

Lecture 10

Intro to classification methods in remote sensing, pixel-based unsupervised methods, the maximum liklihood algorithm

1. Creating groups and subgroups of image bands
2. Unsupervised classification
3. Supervised Maximum Likelihood Classification

Lecture 11

Supervised classification, accuracy statistics

1. Supervised SMAP classification
2. Classification accuracy

Lecture 12

Change detection techniques and hardcopy map production

1. Multitemporal color composites
2. Image Algebra change detection
3. Principal components

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