Spatial Analysis (5 cr)

Objectives (course unit)

The students know the basics of spatial analysis done for vector and raster data. The students are able to utilize different spatial data for spatial analyst processes.
The students can apply spatial analysis for forestry and environmental management purposes.

Content (course unit)

Vector and raster data, overlay analysis, neighborhood analysis, raster processing tools, surface analysis, functions for overlapping data analysis.

Prerequisites (course unit)

Previous knowledge on geographical information systems

Exam schedules

The exam is going to be a Tabula implementation where Arc Map is used as a GIS tool.
Exam 1: 30.11.2017
Exam 2 ( retake): 14.12.2017

Assessment methods and criteria

Exam 40 %
Practical work 60 %

Assessment scale

0-5

Teaching methods

lectures
exercises with ArcMap
assignmnet with ArcMap

Learning materials

Heywood, Ian.An introduction to geographical information systems / Ian Heywood, Sarah Cornelius and Steve Carver.
2nd ed., Prentice Hall, 2002
Geographical information systems and science / Paul A. Longley ... [et al.].
2nd ed.,Chichester : John Wiley & Sons Inc., 2005.
Lecture material delivered during the course
ArcGIS Desktop Resource Center (ArcMap Help)
Spatial data freely available

Student workload

Lectures 57 h, 78 h students' own work.

Content scheduling

Data download and updating
Raster concepts and management
Overlay analyses vector
Raster overlay
Neighbourhood analyses
Raster surface tools
Interpolation analyses
LAS data management
3D
Assignment

Completion alternatives

None

Further information

Prerequisites: GIS- course

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

The student does not reach the minimum satisfactory level 1.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

Satisfactory (1-2)
The student can:
make queries from vector and raster data
carry out a simple vector overlay analysis
process raster data suitable/required for analysis (conversions, resample, extract)
use tailor made surface analysis tools

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

Good (3-4)
The student can in addition to previous mentioned:
carry out vector overlay analysis combined with neighbourhood analysis
carry out simple raster overlay analysis
carry out spatial interpolation to make a new raster surface

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

Excellent 5
The student can in addition to previous mentioned:
combine successfully several previously mentioned analysis methods in solving spatial problems