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Related Concept Videos

Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
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Manipulation and Analysis01:21

Manipulation and Analysis

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Methods of Obtaining Topography

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Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
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Levels of Use of a GIS01:29

Levels of Use of a GIS

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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Related Experiment Video

Updated: Dec 12, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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GIS-based spatial modeling of snow avalanches using four novel ensemble models.

Peyman Yariyan1, Mohammadtaghi Avand2, Rahim Ali Abbaspour3

  • 1Department of Surveying Engineering, Islamic Azad University Saghez Branch, Saghez, Iran.

The Science of the Total Environment
|August 8, 2020
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Summary

This study developed a novel hybrid model for snow avalanche susceptibility mapping in Iran. The probability density-logistic regression (PD-LR) model demonstrated superior accuracy in identifying avalanche-prone areas for effective management.

Keywords:
GISHybrid modelsSirvan watershedSnow avalancheStatistical models

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Area of Science:

  • Geosciences and Remote Sensing
  • Natural Hazard Assessment
  • Spatial Analysis

Background:

  • Snow avalanches pose significant risks to lives and infrastructure in vulnerable regions.
  • Accurate susceptibility mapping is crucial for disaster risk reduction and land-use planning.
  • Existing methods require enhancement for improved prediction accuracy.

Purpose of the Study:

  • To map snow avalanche susceptibility in Sirvan Watershed, Iran, using an innovative hybrid modeling approach.
  • To compare the performance of different statistical and machine learning models for avalanche prediction.
  • To provide a reliable tool for decision-making in avalanche risk management.

Main Methods:

  • Integration of statistical models (belief function and probability density) with machine learning models (multi-layer perceptron and logistic regression).
  • Utilized remote sensing data and a geographic information system (GIS) for spatial analysis.
  • Developed a snow avalanche inventory map from satellite imagery, documentation, and field surveys.

Main Results:

  • The hybrid probability density-logistic regression (PD-LR) model achieved the highest accuracy (AUC = 0.941).
  • All tested hybrid models (PD-LR, Bel-LR, Bel-MLP, PD-MLP) showed high predictive performance.
  • The study successfully identified and validated snow avalanche-prone areas.

Conclusions:

  • The proposed hybrid modeling approach offers accurate and reliable snow avalanche susceptibility mapping.
  • The PD-LR model is recommended for its superior performance in identifying high-risk zones.
  • This methodology supports effective management and decision-making for mitigating avalanche hazards.