A Review On Accuracy and Uncertainty of Spatial Data and Analyses with special reference to Urban and Hydrological Modelling
Data quality for GIS processing and analysis is becoming an increased concern due to the accelerated application of GIS technology for problem solving and decision making roles. Uncertainty in the geographic representation of the real world arises as these representations are incomplete. Identificat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-11-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-8/171/2014/isprsannals-II-8-171-2014.pdf |
| Summary: | Data quality for GIS processing and analysis is becoming an increased concern due to the accelerated application of GIS technology
for problem solving and decision making roles. Uncertainty in the geographic representation of the real world arises as these
representations are incomplete. Identification of the sources of these uncertainties and the ways in which they operate in GIS based
representations become crucial in any spatial data representation and geospatial analysis applied to any field of application. This
paper reviews the articles on the various components of spatial data quality and various uncertainties inherent in them and special
focus is paid to two fields of application such as Urban Simulation and Hydrological Modelling. Urban growth is a complicated
process involving the spatio-temporal changes of all socio-economic and physical components at different scales. Cellular Automata
(CA) model is one of the simulation models, which randomly selects potential cells for urbanisation and the transition rules evaluate
the properties of the cell and its neighbour. Uncertainty arising from CA modelling is assessed mainly using sensitivity analysis
including Monte Carlo simulation method. Likewise, the importance of hydrological uncertainty analysis has been emphasized in
recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures. The Soil
and Water Assessment Tool (SWAT) is a continuous time watershed model to evaluate various impacts of land use management and
climate on hydrology and water quality. Hydrological model uncertainties using SWAT model are dealt primarily by Generalized
Likelihood Uncertainty Estimation (GLUE) method. |
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| ISSN: | 2194-9042 2194-9050 |