A Review of: “Geographic Information Systems for Geoscientists—Modelling with GIS”

Laxton, John L.

doi:10.1080/02693799608902084

Cited by 11 publications

(8 citation statements)

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“…A simple geospatial assessment tool for understanding the probabilistic relationship between dependent and independent variables, including spatial datasets with multiple classification levels, can be applied to the FR model [57]. This approach can be described as an FR index that represents the quantitative relationship between flash flooding hazards occurrence and different conditioning parameters.…”

Section: Frequency Ratiomentioning

confidence: 99%

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Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

et al. 2016

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This study focused on producing flash flood hazard susceptibility maps (FFHSM) using frequency ratio (FR) and statistical index (SI) models in the Xiqu Gully (XQG) of Beijing, China. First, a total of 85 flash flood hazard locations (n = 85) were surveyed in the field and plotted using geographic information system (GIS) software. Based on the flash flood hazard locations, a flood hazard inventory map was built. Seventy percent (n = 60) of the flooding hazard locations were randomly selected for building the models. The remaining 30% (n = 25) of the flooded hazard locations were used for validation. Considering that the XQG used to be a coal mining area, coalmine caves and subsidence caused by coal mining exist in this catchment, as well as many ground fissures. Thus, this study took the subsidence risk level into consideration for FFHSM. The ten conditioning parameters were elevation, slope, curvature, land use, geology, soil texture, subsidence risk area, stream power index (SPI), topographic wetness index (TWI), and short-term heavy rain. This study also tested different classification schemes for the values for each conditional parameter and checked their impacts on the results. The accuracy of the FFHSM was validated using area under the curve (AUC) analysis. Classification accuracies were 86.61%, 83.35%, and 78.52% using frequency ratio (FR)-natural breaks, statistical index (SI)-natural breaks and FR-manual classification schemes, respectively. Associated prediction accuracies were 83.69%, 81.22%, and 74.23%, respectively. It was found that FR modeling using a natural breaks classification method was more appropriate for generating FFHSM for the Xiqu Gully.

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Section: Frequency Ratiomentioning

confidence: 99%

“…The FR can be defined as the ratio of the area where flash flooding hazards may occur to the total study area, or the ratio of the probability of a flash flood hazard occurrence to a non-occurrence as shown in Equation (4) [57]:…”

Section: Frequency Ratiomentioning

confidence: 99%

Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

et al. 2016

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“…In this study, the FR method was used to perform mass-wasting susceptibility mapping. The FR is defined as the ratio of the probability of the occurrence of a mass-wasting to the probability of a nonoccurrence for a given attribute [52,53]. The larger the FR, the stronger the effect of the given factor on the debris flow [54].…”

Section: Methodsmentioning

confidence: 99%

Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing

Cao

Chen

Zhang

et al. 2019

IJERPH

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Driven by the pull of gravity, mass-wasting comprises all of the sedimentary processes related to remobilization of sediments deposited on slopes, including creep, sliding, slumping, flow, and fall. It is vital to conduct mass-wasting susceptibility mapping, with the aim of providing decision makers with management advice. The current study presents two individual data mining methods—the frequency ratio (FR) and information value model (IVM) methods—to map mass-wasting susceptibility in four catchments in Miyun County, Beijing, China. To achieve this goal, nine influence factors and a mass-wasting inventory map were used and produced, respectively. In this study, 71 mass-wasting locations were investigated in the field. Of these hazard locations, 70% of them were randomly selected to build the model, and the remaining 30% of the hazard locations were used for validation. Finally, a receiver operating characteristic (ROC) curve was used to assess the mass-wasting susceptibility maps produced by the above-mentioned models. Results show that the FR had a higher concordance and spatial differentiation, with respective values of 0.902 (area under the success rate) and 0.883 (area under the prediction rate), while the IVM had lower values of 0.865 (area under the success rate) and 0.855 (area under the prediction rate). Both proposed methodologies are useful for general planning and evaluation purposes, and they are shown to be reasonable models. Slopes of 6–21° were the most common thresholds that controlled occurrence of mass-wasting. Farmland terraces were mainly composed of gravel, mud, and clay, which are more prone to mass-wasting. Mass-wasting susceptibility mapping is feasible and potentially highly valuable. It could provide useful information in support of environmental health policies.

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“…Frequency ratio as bivariate statistical method describes the spatial relationship between flash floods with each variable class. Laxton (1996) mentioned that the Journal of Geoscience and Environment Protection frequency ratio (FR) can be defined as the ratio of the area where flash flooding hazards may occur to the total study area, or the ratio of the probability of a flash flood hazard occurrence to a non-occurrence as shown in the following Equation (Equation (1)).…”

Section: Frequency Ratiomentioning

confidence: 99%

Flash Flood Hazard Mapping Using GIS and Bivariate Statistical Method at Wadi Bada’a, Gulf of Suez, Egypt

El-Magd¹

2019

GEP

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The area is a part of the Egyptian Eastern Desert in the northwestward to the Gulf of Suez. It covers an area of about 542 square kilometers. Wadi Bada'a is devoid of vegetation, because of the arid climate and water scarcity. However, the present study concerns the flash flood and its impact on the industrial zone and connected road at wadi Bada'a. In this work, the bivariate statistical method using frequency ratio was used to evaluate the areas of potential risk. Geographic Information System package (GIS) was used to analyze and calculate different data sets. The different data source has been used in the research to produce a flood hazard susceptibility map of the area, including the geologic maps, Landsat-8 imagery, land use, and soil type associated with field investigation and data collection. Spatial database with elements at risk, related features and attributes at wadi Bada'a, were constructed. Training data were created randomly in the study area to create an inventory map with testing data. The inventory location of 95 location points has been created. The inventory datasets were divided into 75% of training datasets and 25% testing data. The independent flood-related factors were evaluated by analyzing each independently and assessing their impact on flooding with inventory datasets. The flood susceptibility maps were constructed-using training and testing datasets have been used to evaluate using the success rate method. The results of the accuracy assessment showed a success rate of 76.6% of Area Under Curve. Therefore, the main road in the study area almost at high risk in many parts because of flash flood, additionally the industrial activities located in the moderate risk zone.

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A Review of: “Geographic Information Systems for Geoscientists—Modelling with GIS”

Cited by 11 publications

References 0 publications

Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas

Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing

Flash Flood Hazard Mapping Using GIS and Bivariate Statistical Method at Wadi Bada’a, Gulf of Suez, Egypt

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