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GIS based chemical fate modeling : principles and applications / Alberto Pistocchi.

By: Material type: TextTextPublisher: Hoboken, New Jersey : Wiley, 2014Copyright date: ©2014Description: 1 online resource (506 pages) : color illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118523650
  • 1118523652
  • 1118059972
  • 9781118059975
  • 9781118523667
  • 1118523660
Subject(s): Genre/Form: Additional physical formats: Print version:: GIS based chemical fate modeling : principles and applications.DDC classification:
  • 577/.140285 23
LOC classification:
  • TD193 .P57 2014eb
Other classification:
  • SCI013040
Online resources:
Contents:
Cover; Title Page; Copyright; Preface; Contributors; Chapter 1: Chemicals, Models, and GIS: Introduction; 1.1 Chemistry, Modeling, and Geography; 1.2 Mr. Palomar and Models; 1.3 What Makes a Model Different?; 1.4 Simple, Complex, or Tiered?; 1.5 For Whom is this Book Written?; References; Chapter 2: Basics of Chemical Compartment Models and Their Implementation with GIS Functions; 2.1 Introduction; 2.2 Phase Partitioning; 2.3 Diffusion, Dispersion, and Advection; 2.4 Fluxes at the Interfaces; 2.5 Reactions; 2.6 Transport within An Environmental Medium: The Advection-Diffusion Equation (ADE).
2.7 Analytical Solutions; 2.8 Box Models, Multimedia and Multispecies Fate and Transport; 2.9 Spatial Models: Implicit, Explicit, Detailed Explicit, and GIS-Based Schemes; References; Chapter 3: Basics of GIS Operations; 3.1 What is GIS?; 3.2 GIS Data; 3.3 GIS Software; 3.4 GIS Standards; 3.5 A Classification of GIS Operations for Chemical Fate Modeling; 3.6 Spatial Thinking; 3.7 Beyond GIS; 3.8 Further Progress on GIS; References; Chapter 4: Map Algebra; 4.1 MAP Algebra Operators and Syntaxes; 4.2 Using MAP Algebra to Compute a Gaussian Plume.
4.3 Using MAP Algebra to Implement Isolated box Models; References; Chapter 5: Distance Calculations; 5.1 Concepts of Distance Calculations; 5.2 Distance Along a Surface and Vertical Distance; 5.3 Applications of Euclidean Distance in Pollution Problems; 5.4 Cost Distance; References; Chapter 6: Spatial Statistics and Neighborhood Modeling in GIS; 6.1 Variograms: Analyzing Spatial Patterns; 6.2 Interpolation; 6.3 Zonal Statistics; 6.4 Neighborhood Statistics and Filters; References; Chapter 7: Digital Elevation Models, Topographic Controls, and Hydrologic Modeling in GIS.
7.1 Basic Surface Analysis; 7.2 Drainage; 7.3 Using GIS Hydrological Functions in Chemical Fate and Transport Modeling; 7.4 Non-D8 Methods and the TauDEM Algorithms; 7.5 ESRI's "Darcy Flow" and "Porous Puff" Functions; References; Chapter 8: Elements of Dynamic Modeling in GIS; 8.1 Dynamic GIS Models; 8.2 Studying Time-Dependent Effects with Simple Map Algebra; 8.3 Decoupling Spatial and Temporal Aspects of Models: The Mappe Global Approach; References; Chapter 9: Metamodeling and Source-Receptor Relationship Modeling in GIS; 9.1 Introduction; 9.2 Metamodeling; 9.3 Source-Receptor Relationships.
References; Chapter 10: Spatial Data Management in GIS and the Coupling of GIS and Environmental Models; 10.1 Introduction; 10.2 Historical Perspective of Emergence of Spatial Databases in Environmental Domain; 10.3 Spatial Data Management in GIS: Theory and History; 10.4 Spatial Database Solutions; 10.5 Simple environmental spatiotemporal database skeleton and GIS: hands-on examples; 10.6 Generalized Environmental Spatiotemporal Database Skeleton and Geographic Mashups; References; Chapter 11: Soft Computing Methods for the Overlaying of Chemical Data with Other Spatially Varying Parameters.
11.1 Introduction.
Summary: Explains how GIS enhances the development of chemical fate and transport models Over the past decade, researchers have discovered that geographic information systems (GIS) are not only excellent tools for managing and displaying maps, but also useful in the analysis of chemical fate and transport in the environment. Among its many benefits, GIS facilitates the identification of critical factors that drive chemical fate and transport. Moreover, GIS makes it easier to communicate and explain key model assumptions. Based on the author's firsthand experience in environmental asse.
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Includes bibliographical references at the end of each chapters and index.

Print version record.

Cover; Title Page; Copyright; Preface; Contributors; Chapter 1: Chemicals, Models, and GIS: Introduction; 1.1 Chemistry, Modeling, and Geography; 1.2 Mr. Palomar and Models; 1.3 What Makes a Model Different?; 1.4 Simple, Complex, or Tiered?; 1.5 For Whom is this Book Written?; References; Chapter 2: Basics of Chemical Compartment Models and Their Implementation with GIS Functions; 2.1 Introduction; 2.2 Phase Partitioning; 2.3 Diffusion, Dispersion, and Advection; 2.4 Fluxes at the Interfaces; 2.5 Reactions; 2.6 Transport within An Environmental Medium: The Advection-Diffusion Equation (ADE).

2.7 Analytical Solutions; 2.8 Box Models, Multimedia and Multispecies Fate and Transport; 2.9 Spatial Models: Implicit, Explicit, Detailed Explicit, and GIS-Based Schemes; References; Chapter 3: Basics of GIS Operations; 3.1 What is GIS?; 3.2 GIS Data; 3.3 GIS Software; 3.4 GIS Standards; 3.5 A Classification of GIS Operations for Chemical Fate Modeling; 3.6 Spatial Thinking; 3.7 Beyond GIS; 3.8 Further Progress on GIS; References; Chapter 4: Map Algebra; 4.1 MAP Algebra Operators and Syntaxes; 4.2 Using MAP Algebra to Compute a Gaussian Plume.

4.3 Using MAP Algebra to Implement Isolated box Models; References; Chapter 5: Distance Calculations; 5.1 Concepts of Distance Calculations; 5.2 Distance Along a Surface and Vertical Distance; 5.3 Applications of Euclidean Distance in Pollution Problems; 5.4 Cost Distance; References; Chapter 6: Spatial Statistics and Neighborhood Modeling in GIS; 6.1 Variograms: Analyzing Spatial Patterns; 6.2 Interpolation; 6.3 Zonal Statistics; 6.4 Neighborhood Statistics and Filters; References; Chapter 7: Digital Elevation Models, Topographic Controls, and Hydrologic Modeling in GIS.

7.1 Basic Surface Analysis; 7.2 Drainage; 7.3 Using GIS Hydrological Functions in Chemical Fate and Transport Modeling; 7.4 Non-D8 Methods and the TauDEM Algorithms; 7.5 ESRI's "Darcy Flow" and "Porous Puff" Functions; References; Chapter 8: Elements of Dynamic Modeling in GIS; 8.1 Dynamic GIS Models; 8.2 Studying Time-Dependent Effects with Simple Map Algebra; 8.3 Decoupling Spatial and Temporal Aspects of Models: The Mappe Global Approach; References; Chapter 9: Metamodeling and Source-Receptor Relationship Modeling in GIS; 9.1 Introduction; 9.2 Metamodeling; 9.3 Source-Receptor Relationships.

References; Chapter 10: Spatial Data Management in GIS and the Coupling of GIS and Environmental Models; 10.1 Introduction; 10.2 Historical Perspective of Emergence of Spatial Databases in Environmental Domain; 10.3 Spatial Data Management in GIS: Theory and History; 10.4 Spatial Database Solutions; 10.5 Simple environmental spatiotemporal database skeleton and GIS: hands-on examples; 10.6 Generalized Environmental Spatiotemporal Database Skeleton and Geographic Mashups; References; Chapter 11: Soft Computing Methods for the Overlaying of Chemical Data with Other Spatially Varying Parameters.

11.1 Introduction.

Explains how GIS enhances the development of chemical fate and transport models Over the past decade, researchers have discovered that geographic information systems (GIS) are not only excellent tools for managing and displaying maps, but also useful in the analysis of chemical fate and transport in the environment. Among its many benefits, GIS facilitates the identification of critical factors that drive chemical fate and transport. Moreover, GIS makes it easier to communicate and explain key model assumptions. Based on the author's firsthand experience in environmental asse.

Management Information Systems