In this online course, you can learn the complete process (A-Z) from scratch to production. How to select parameters and why, download raster and vector data, processing data, images in ArcGIS environment, justification of variables, step by step guide of SPI, CRITIC, WASPAS, and SAW models in excel, produced prediction map applying CRITIC, WASPAS, and SAW methods in Drought Vulnerability zonation using ArcGIS. Moreover, you will also learn validation of the susceptibility map using advanced techniques such as MAE, MSE, RMSE, ROC-AUC.
SPI (Standardized Precipitation Index) is a widely used index to characterize meteorological drought on a range of timescales. On short timescales, the SPI is closely related to soil moisture, while at longer timescales, the SPI can be related to groundwater and reservoir storage. The SPI can be compared across regions with markedly different climates. It quantifies observed precipitation as a standardized departure from a selected probability distribution function that models the raw precipitation data. The raw precipitation data are typically fitted to gamma or a Pearson Type III distribution and then transformed to a normal distribution. The SPI values can be interpreted as the number of standard deviations by which the observed anomaly deviates from the long-term mean. The SPI can be created for differing periods of 1-to-36 months, using monthly input data. For the operational community, the SPI has been recognized as the standard index that should be available worldwide for quantifying and reporting meteorological drought.
CRITIC (Criteria Importance Through Inter-criteria Correlation) a useful method that identifies the objective weight of MCDM problems based on contrast intensity and the conflicting character of the evaluation criteria proposed by Diakoulaki, Danae, George Mavrotas, and Lefteris Papayannakis (1995).
WASPAS method (weighted aggregated sum product assessment) is one of the MCDM methods. It was developed by Zavadskas et al. The WASPAS method is a unique combination of the Weighted Sum Model (WSM) and Weighted Product Model (WPM) which are two well-known MCDM methods. The WSM method determines the overall score of an alternative as a weighted sum of the criteria values while WPM determines the score of an alternative as a product of the scale rating of each criterion to a power equal to the weight of a given criterion. In addition to these methods, WASPAS tries to reach the highest accuracy of estimation by optimizing weighted aggregated function
SAW (Simple Additive Weighting) method is a well-known method relying on the linear utility function for multi-criteria evaluation (Hwang, Yoon 1981, Rozman et al. 2016, Vico 2017). Churchman and Ackoff (1954) first utilized the SAW method to cope with a portfolio selection problem. The SAW method is probably the best known and widely used method for multiple attribute decision-making (MADM). Because of its simplicity, SAW is the most popular method in MADM problems
After completing this course, you will be efficiently able to process, predict, and validate any data related to hazard, vulnerability, risk, and suitability assessment using the CRITIC, WASPAS, and SAW models.
Keywords: Excel, ArcGIS, R-studio, SPI, CRITIC, WASPAS, SAW, Drought, Mapping, Prediction
Students, researchers and professionals of Natural hazards, Environmental Science, Engineering, Remote Sensing and Geography.
Students, researchers and professionals who are interested in multi-criteria decision making and risk analysis using GIS Data.
Students, researchers and professionals who work on: Hazards, vulnerability and risk [flooding, landslides, drought], susceptibility [Groundwater potentiality, vulnerability] and Suitability [Agricultural suitability, Irrigation suitability].
Anyone interested in learning the Structured Decision-Making Using Step by Step Approach.
Comprehensive understanding of SPI, CRITIC, WASPAS, and SAW models and its Interface with Various Decision-Making Interfaces
An Integrated MCDM approach for Drought Vulnerability Assessment in ArcGIS
An Ensemble of Evidence Belief Function (EBF) with Frequency Ratio (FR) for GIS-based landslide prediction in ArcGIS
Live 16/07/22 to 27/08/22
INR. 10000.00 USD. 150.00
Enroll nowAn Ensemble of Evidence Belief Function (EBF) with Frequency Ratio (FR) for GIS-based landslide prediction in ArcGIS
In this online workshop and live practice, you can learn the complete process (A-Z) from scratch to production. How to select parameters and why, download raster and vector data, processing data, images in ArcGIS environment, justification of variables, step by step guide of Dempster-Shafer theory of EBF and FR models, produced prediction map applying combined EBF and FR methods in Landslide prediction zonation using ArcGIS. Moreover, you will also learn validation of the susceptibility map using advanced techniques such as success rate curve and prediction rate curve.
After completing this course, you will be efficiently able to process, predict, and validate any data related to hazard, vulnerability, risk, and suitability assessment using the EBF and FR models.
Groundwater potentiality and stress zonation using TOPSIS, VIKOR and EDAS models in ArcGIS
INR. 10000.00
USD. 150
In this online certificate course, you can learn the complete process (A-Z) from scratch to production. How to select parameters and why, download raster and vector data, processing data, images in ArcGIS environment, justification of variables, step by step guide of TOPSIS, VIKOR and EDAS in excel, produced prediction map applying these methods in groundwater potentiality and stress zonation using ArcGIS. Moreover, you will also learn validation of the potentiality map in ArcGIS software.
In this course, you can learn the complete process (A-Z) from scratch to production. How to select parameters and why, download raster and vector data, processing data, images in ArcGIS environment, justification of variables, step by step guide of Analytic Hierarchy Process (AHP) in excel, produced prediction map applying AHP method in hazard, vulnerability, and risk using GIS. Moreover, you can also learn sensitivity analysis in ArcGIS and validation of the susceptibility map in SPSS software.
Analytic Hierarchy Process (AHP) is the most powerful multi-criteria decision-making and Problem-Solving method first introduced by Saaty in 1980. In short, it is used for ranking the attributes to select the optimal attribute based on the hierarchical structure of goal at the top level, criteria at the second level, and alternative at third level
After completing this course, you will be efficiently able to process, predict, and validate any data related to hazard, vulnerability, risk, and suitability assessment using the Analytic Hierarchy Process (AHP).
Flood Hazards, Vulnerability and Risk Assessment using Analytical Hierarchy Process in ArcGIS
INR. 10000.00
USD. 150
Over two decades of experience and expertise in teaching Tech and coding helping students develop their tech skills for higher performance, better careers and growth in companies.
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Get certified with our premium courses and get started on your journey to a brand new career altogether
Get certified with our premium courses and get started on your journey to a brand new career altogether
Get certified with our premium courses and get started on your journey to a brand new career altogether