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Geomatic Approaches for Modeling Land Change Scenarios

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Cover of 'Geomatic Approaches for Modeling Land Change Scenarios'

Table of Contents

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    Book Overview
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    Chapter 1 Geomatic Approaches for Modeling Land Change Scenarios. An Introduction
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    Chapter 2 LUCC Modeling Approaches to Calibration
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    Chapter 3 The Simulation Stage in LUCC Modeling
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    Chapter 4 Techniques for the Validation of LUCC Modeling Outputs
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    Chapter 5 LUCC Scenarios
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    Chapter 6 Obtaining and Comparing Factors in Land Change Models Using One or Two Time Points Based Calibration
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    Chapter 7 Impact and Integration of Multiple Training Dates for Markov Based Land Change Modeling
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    Chapter 8 Land Use Change Modeling with SLEUTH: Improving Calibration with a Genetic Algorithm
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    Chapter 9 The Importance of Scale in Land Use Models: Experiments in Data Conversion, Data Resampling, Resolution and Neighborhood Extent
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    Chapter 10 The Influence of Scale in LULC Modeling. A Comparison Between Two Different LULC Maps (SIOSE and CORINE)
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    Chapter 11 Who Knows Best? The Role of Stakeholder Knowledge in Land Use Models—An Example from Doñana, SW Spain
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    Chapter 12 Land Use and Cover Change Modeling as an Integration Framework: A Mixed Methods Approach for the Southern Coast of Jalisco (Western Mexico)
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    Chapter 13 Urban Land Use Change Analysis and Modeling: A Case Study of the Gaza Strip
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    Chapter 14 Constraint Cellular Automata for Urban Development Simulation: An Application to the Strasbourg-Kehl Cross-Border Area
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    Chapter 15 Modeling Land-Use Scenarios in Protected Areas of an Urban Region in Spain
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    Chapter 16 Navigating the Future: Land Redevelopment Scenarios and Broader Impact Assessment in Southern California
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    Chapter 17 Modeling the Future Evolution of Chilean Forests to Guide Current Practices. Native Forest and Industrial Timber Plantations in Southern Chile
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    Chapter 18 Urban Transportation Scenarios in a LUCC Model: A Case Study in Bogota, Colombia
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    Chapter 19 Integrating Econometric and Spatially Explicit Dynamic Models to Simulate Land Use Transitions in the Cerrado Biome
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    Chapter 20 Cellular Automaton
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    Chapter 21 Cellular Automata in CA_MARKOV
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    Chapter 22 Fuzzy Coincidence
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    Chapter 23 LUCC Based Validation Indices: Figure of Merit, Producer’s Accuracy and User’s Accuracy
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    Chapter 24 LUCC Budget
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    Chapter 25 Markov Chain
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    Chapter 26 Multi Criteria Evaluation (MCE)
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    Chapter 27 Multilayer Perceptron (MLP)
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    Chapter 28 Multi-objective Land Allocation (MOLA)
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    Chapter 29 The NASZ Model
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    Chapter 30 Receiver Operating Characteristic (ROC) Analysis
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    Chapter 31 Weights of Evidence
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    Chapter 32 A Short Presentation of the Actor, Policy, and Land Use Simulator (APoLUS)
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    Chapter 33 A Short Presentation of CA_MARKOV
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    Chapter 34 A Short Presentation of CLUMondo
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    Chapter 35 A Short Presentation of Dinamica EGO
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    Chapter 36 A Short Presentation of the Land Change Modeler (LCM)
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    Chapter 37 A Short Presentation of LucSim
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    Chapter 38 A Short Presentation of Metronamica
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    Chapter 39 A Short Presentation of SLEUTH
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Title
Geomatic Approaches for Modeling Land Change Scenarios
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-60801-3
ISBNs
978-3-31-960800-6, 978-3-31-960801-3
Editors

María Teresa Camacho Olmedo, Martin Paegelow, Jean-François Mas, Francisco Escobar

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 8%
Lecturer 2 5%
Researcher 2 5%
Student > Ph. D. Student 1 3%
Student > Bachelor 1 3%
Other 0 0%
Unknown 29 76%
Readers by discipline Count As %
Environmental Science 4 11%
Agricultural and Biological Sciences 2 5%
Unspecified 1 3%
Earth and Planetary Sciences 1 3%
Engineering 1 3%
Other 0 0%
Unknown 29 76%