Attribute error and sensitivity analysis of map operations in geographical informations systems: suitability analysis

Lodwick, Weldon A.; Monson, W. J.; Svoboda, Larry

doi:10.1080/02693799008941556

Cited by 314 publications

(129 citation statements)

References 2 publications

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“…Based on the map removal sensitivity analysis test developed by [29] and adopted by [30], which was used in this research to identify the sensitivity of each factor in the SWSy map. In this test, Equation (2) was used to calculate the sensitivity index (S) for the factors used in the vulnerability index.…”

Section: Map Removal Sensitivity Analysismentioning

confidence: 99%

Modelling Surface Water Susceptibility to Pollution Using GIS

Al‐Adamat¹

2017

JGIS

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This research is an attempt to develop a new GIS index to investigate the surface water susceptibility to pollution (SWSi). In this index, the Weighted Linear Combination techniques within GIS environment was used to calculate the overall surface water susceptibility to pollution scores based on using 6 factors. The model includes 3 natural factors: gradient slope, distance to surface water and soil. Also, it includes 3 man-made activities: urban, agriculture and roads. Each factor was given the appropriate weight and ratings and then the final index was calculated using GIS techniques. The final results showed that the study area (1235 km 2 ) could be classified into low susceptibility with an area of 250 km 2 (20.2%), moderate susceptibility with an area of 815.5 km 2 (66%), high susceptibility with an area of 166.2 km 2 (13.5%) and very high susceptibility with an area of 3.3 km 2 (0.3%).

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Section: Map Removal Sensitivity Analysismentioning

confidence: 99%

Modelling Surface Water Susceptibility to Pollution Using GIS

Al‐Adamat¹

2017

JGIS

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“…Numerous sensitivity analysis studies have been done on DRASTIC (e.g. Bailey 1988, Heuvelink et al 1989, Lodwick et al 1990, Barber et al 1993, Merchant 1994, Babiker et al 2005, Panagopoulos et al 2006. There are two main methods of doing sensitivity analysis in DRASTIC: one is the map removal analysis and the other is single-parameter sensitivity analysis (Napolitano and Fabbri 1996).…”

Section: Classic Drastic and Fuzzy-optimization Methodsmentioning

confidence: 99%

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

Chen

Zhang

Yao

et al. 2012

Hydrological Sciences Journal

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., 2012. A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment. Hydrological Sciences Journal, 57 (7), 1420-1432.Abstract Groundwater vulnerability assessment based on the DRASTIC index has been widely used since the 1980s to map potential risks of groundwater contamination. However, its applicability and usefulness are affected by two uncertain and subjective factors. One is the discretization of continuous input variables and the other is the assignment of different weights to the index variables. In this study, an entropy-weighted fuzzy-optimization approach was developed to augment and improve the classic DRASTIC method by reducing the uncertainties associated with variable discretization and weight assignment. The modified DRASTIC method was applied to a study site in Shandong, north China. The entropy-weighted fuzzy-optimization approach is shown to provide a more rigorous delineation of the relative vulnerability distribution. Meanwhile, the new approach does not require the use of more parameters. The results suggest that this approach significantly improves and enhances the ability of the classic DRASTIC method in a more systematic and rigorous way.Key words groundwater vulnerability; DRASTIC index; entropy-weighted fuzzy optimization; sensitivity analysis Une démonstration de terrain de la méthode DRASTIC floue pondérée par l'entropie pour l'évaluation de la vulnérabilité des eaux souterraines Résumé L'évaluation de la vulnérabilité des eaux souterraines sur la base de l'indice DRASTIC a été largement utilisée depuis les années 1980 pour la cartographie des risques potentiels de pollution des eaux souterraines. Son applicabilité et son utilité sont cependant affectées par les deux facteurs que sont l'incertitude et la subjectivité. Il faut d'abord discrétiser les variables d'entrée continues, puis attribuer des poids aux variables de l'indice. Dans cette étude, nous avons adopté une approche d'optimisation floue pondérée par l'entropie, afin d'élargir et d'améliorer la méthode DRASTIC classique en réduisant les incertitudes liées à la discrétisation des variables et à l'attribution des poids. La méthode DRASTIC modifiée a été appliquée à un site d'étude dans le Shandong, au Nord de la Chine. L'approche d'optimisation floue pondérée par l'entropie s'est révélée fournir une définition plus rigoureuse de la distribution relative de vulnérabilité. En même temps, la nouvelle approche ne nécessite pas d'utiliser davantage de paramètres. Les résultats suggèrent que cette approche améliore significativement et de façon systématique et rigoureuse le potentiel de la méthode DRASTIC classique.

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“…Sensitivity analysis provides helpful information on the influence of rating and weighting values assigned to each parameter and helps hydrogeologist to judge the significance of subjectivity elements (Gogu and Dassargues 2000). There are two types of sensitivity analysis: map removal sensitivity analysis introduced by Lodwick et al (1994) and the single-parameter sensitivity analysis introduced by Napolitano and Fabbri (1996). The map removal sensitivity measure identifies the sensitivity of the vulnerability map towards removing one or more map from vulnerability analysis.…”

Section: Sensitivity Analysismentioning

confidence: 99%

A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq

2014

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In this study, intrinsic groundwater vulnerability for the shallow aquifer in northeastern Missan governorate, south of Iraq is evaluated using commonly used DRASTIC model in framework of GIS environment. Preparation of DRASTIC parameters is attained through gathering data from different sources including field survey, geological and meteorological data, a digital elevation model DEM of the study area, archival database, and published research. The different data used to build DRASTIC model are arranged in a geospatial database using spatial analyst extension of ArcGIS 10.2 software. The obtained results related to the vulnerability to general contaminants show that the study area is characterized by two vulnerability zones: low and moderate. Ninety-four percentage (94 %) of the study area has a low class of groundwater vulnerability to contamination, whereas a total of (6 %) of the study area has moderate vulnerability. The pesticides DRASTIC index map shows that the study area is also characterized by two zones of vulnerability: low and moderate. The DRASTIC map of this version clearly shows that small percentage (13 %) of the study area has low vulnerability to contamination, and most parts have moderate vulnerability (about 87 %). The final results indicate that the aquifer system in the interested area is relatively protected from contamination on the groundwater surface. To mitigate the contamination risks in the moderate vulnerability zones, a protective measure must be put before exploiting the aquifer and before comprehensive agricultural activities begin in the area.

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Attribute error and sensitivity analysis of map operations in geographical informations systems: suitability analysis

Cited by 314 publications

References 2 publications

Modelling Surface Water Susceptibility to Pollution Using GIS

Modelling Surface Water Susceptibility to Pollution Using GIS

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq

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