GIS Based Chemical Fate Modeling Principles and Applications 1st Edition by Alberto Pistocchi – Ebook PDF Instant Download/Delivery: 1118059972, 9781118059975
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Product details:
ISBN 10: 1118059972
ISBN 13: 9781118059975
Author: Alberto Pistocchi
This book covers the integration of chemical fate modeling for use in Geographic Information System (GIS) functions. The practical and hands on approach this book provides can be used for modelers preparing maps of chemical emissions, and creating landscape and climate properties within a GIS, while chemical fate calculations are performed using specialized model codes.
GIS Based Chemical Fate Modeling Principles and Applications 1st Table of contents:
CHAPTER 1: Chemicals, Models, and GIS: Introduction
CHAPTER 2: Basics of Chemical Compartment Models and Their Implementation with GIS Functions
CHAPTER 3: Basics of GIS Operations
CHAPTER 4: Map Algebra
CHAPTER 5: Distance Calculations
CHAPTER 6: Spatial Statistics and Neighborhood Modeling in GIS
CHAPTER 7: Digital Elevation Models, Topographic Controls, and Hydrologic Modeling in GIS
CHAPTER 8: Elements of Dynamic Modeling in GIS
CHAPTER 9: Metamodeling and Source–Receptor Relationship Modeling in GIS
CHAPTER 10: Spatial Data Management in GIS and the Coupling of GIS and Environmental Models
CHAPTER 11: Soft Computing Methods for the Overlaying of Chemical Data with Other Spatially Varying Parameters
CHAPTER 12: Types of Data Required for Chemical Fate Modeling
CHAPTER 13: Retrieval and Analysis of Emission Data
CHAPTER 14: Characterization of Environmental Properties and Processes
CHAPTER 15: Complex Models, GIS, and Data Assimilation
CHAPTER 16: The Issue of Monitoring Data and the Evaluation of Spatial Models of Chemical Fate
CHAPTER 17: From Fate to Exposure and Risk Modeling with GIS
CHAPTER 18: GIS Based Models in Practice: The Multimedia Assessment of Pollutant Pathways in the Environment (MAPPE) Model
CHAPTER 19: Inverse Modeling and Its Application to Water Contaminants
CHAPTER 20: Chemical Fate and Transport Indicators and the Modeling of Contamination
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