Spatial modelling and geoprocessing Flashcards
Non spatial data
Not associated with locationSp
Spatial data
Associated with location and can provide more insights
Non spatial stats
Mean, median, mode
Spatial stats
Mean Center, standard distance
Importance of spatial data analysis
Redunduncy in data measurements
No direction is included
Modifiable areal unit problem (MAUP)
Redundancy in data measurements
Leads to loss of variability (non indep)
Spatial autocorrelation (close things in spaces are more related)
No direction is included
Many natural and human features change with direction
MAUP
Zone definitions and scale effects
Multivariate data analysis
Y=a1x1+a2x2+..+c
Y= dependent variable
Xn=indepedent
C=constant
Errors and uncertainties
Data quality
Completeness
Compatible
Consistent
Applicable
Data quality
Overall suitability of a dataset for a specific purpose
Error and uncertainty
Accuracy/precision
Resolution
Generalization
Complete
Compatible
Consistent
Applicable
Completeness
Data must be spatially and temporally complete
Compatible
Multiple datasets used in the same project must be of the same scale and extent
Consistent
Multiple datasets should undergo consistent methods of data capture, storage, manipulation and editing
Applicable
Data must be suitable for the analysis or project
Errors in data measurements
Gross error: blunders - mistake in reading a value
Systematic error: permanent deviation from the true value
Random error: normally distributed with zero mean
Improving accuracy
Check using various methods
Calibrate instrument
Improving precision
Use finger graduation instrument
Average multiple measurements
Model errors
Projection and datum errors: re-project data
Scale extents and mismatch: check data frame properties
Edge mismatch: correct alignment
Spatial thinking
Finds meaning in the shape, size, orientation, location, direction or trajectory or objects, processes or phenomena
Finds meaning in the relative spatial positions of multiple objects, processes or phenomena
GIS based analysis
- spatial analysis - geometric relations
- spatial statistics - multivariate data analysis
geometric relations
topological: separate, adjacent, contained
equivaleent, overlapping
proximal: distance, measures, nearness
network connections
