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Spatial Modeling in GIS and R for Earth and Environmental Sciences

  • 1st Edition - January 18, 2019
  • Latest edition
  • Editors: Hamid Reza Pourghasemi, Candan Gokceoglu
  • Language: English

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographi… Read more

Description

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions.

The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling.

Key features

  • Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography
  • Provides an overview, methods and case studies for each application
  • Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Readership

Students and researchers in earth and environmental sciences, especially hazard management, remote sensing, geophysics, cartography, land surveying, geology, natural resources, ecology, and geography

Table of contents

1. Spatial Analysis of Extreme Rainfall Values Based on Support Vector Machines Optimized by Genetic Algorithms: The Case of Alfeios Basin, Greece
Paraskevas Tsangaratos, Ioanna Ilia, and Ioannis Matiatos

2. Remotely Sensed Spatial and Temporal Variations of Vegetation Indices Subjected to Rainfall Amount and Distribution Properties
Mohammad Hossein Shahrokhnia and Seyed Hamid Ahmadi

3. Numerical Recipes for Landslide Spatial Prediction by Using R-INLA: A Step-By-Step Tutorial
Luigi Lombardo, Thomas Opitz, and Raphaël Huser

4. An Integrative Approach of Geospatial Multi-Criteria Decision Analysis for Forest Operational Planning
Sattar Ezzati

5. Parameters Optimization of KINEROS2 Using Particle Swarm Optimization Algorithm within R Environment for Rainfall-Runoff Simulation
Hadi Memarian, Mohsen Pourreza Bilondi, and Zinat Komeh

6. Land-Subsidence Spatial Modeling Using Random Forest Data Mining Technique
Hamid Reza Pourghasemi and Mohsen Mohseni Saravi

7. GIS-Based SWARA and its Ensemble by RBF and ICA Data Mining Techniques for Determining Suitability of Existing Schools and Site Selection of New School Buildings
Mahdi Panahi, Mohammad Yekrangnia, Zohre Bagheri, Hamid Reza Pourghasemi, Fahtemeh Rezai, Iman Nasiri Aghdam, and Ali Akbar Damavandi

8. Application of SWAT and MCDM Models for Identifying and Ranking the Suitable Sites for Subsurface Dams
Javad Chezgi

9. Habitat Suitability Mapping of Artemisia Aucheri Boiss Based on GLM Model in R
Gholamabbas Ghanbarian , Mohammad Reza Raoufat, Hamid Reza Pourghasemi, and Roja Safaeian

10. Flood-Hazard Assessment Modeling Using Multi-Criteria Analysis and GIS: A Case Study: Ras Gharib Area, Egypt
Ahmed M. Youssef and Mahmoud A. Hegab

11. Landslide Susceptibility Survey Using Modelling Methods
Hamidreza Moradi, Mohammad Taqhi Avand, and Saeid Janizadeh

12. Prediction of Soil Disturbance Susceptibility Maps of Forest Harvesting Using R and GIS-Based Data Mining Techniques
Saeid Shabani

13. Spatial Modeling of Gully Erosion Using Linear and Quadratic Discriminant Analyses in GIS and R
Alireza Arabameri and Hamid Reza Pourghasemi

14. Artificial Neural Networks for Flood Susceptibility Mapping in Data-Scarce Urban Areas
Fatemeh Falah, Omid Rahmati, Mohammad Rostami, Ebrahim Ahmadisharaf, Ioannis N. Daliakopoulos, and Hamid Reza Pourghasemi

15. Modelling the Spatial Variability of Forest Fire Susceptibility Using Geographical Information Systems (GIS) and Analytical Hierarchy Process (AHP)
Gigović Ljubomir, Dragan Pamučar, Siniša Drobnjak, and Hamid Reza Pourghasemi

16. Prioritization of Flood Inundation of Maharloo Watershed in Iran Using Morphometric Parameters Analysis and TOPSIS MCDM Model
Mahdis Amiri, Hamid Reza Pourghasemi, Alireza Arabameri, Arya Vazirzadeh, Hossein Yousefi, and Sasan Kafaei

17. A Robust R-M-R (Remote Sensing – Spatial Modeling – Remote Sensing) Approach for Flood Hazard Assessment
Stathopoulos Nikolaos, Kalogeropoulos Kleomenis, Chalkias Christos, Dimitriou Elias, Skrimizeas Panagiotis, Louka Panagiota, and Papadias Vagelis

18. Prioritization of Effective Factors on Zataria Multiflora Habitat Suitability and Its Spatial Modeling
Mohsen Edalat, Enayat Jahangiri, Emran Dastras, and Hamid Reza Pourghasemi

19. Prediction of Soil Organic Carbon Using Regression Kriging Model and Remote Sensing Data
Gouri Sankar Bhunia, Pravat Kumar Shit, Hamid Reza Pourghasemi, and Mohsen Edalat

20. 3D Reconstruction of Landslides for the Acquisition of Digital Databases and Monitoring Spatio-Temporal Dynamics of Landslides based on GIS Spatial Analysis and UAV Techniques
Ştefan Bilaşco, Sanda Roşca, Dănuț Petrea, Iuliu Vescan, Ioan Fodorean, and Sorin Filip

21. A Comparative Study of Functional Data Analysis and Generalized Linear Model Data Mining Techniques for Landslide Spatial Modelling
Wei Chen, Hamid Reza Pourghasemi, Shuai Zhang, and Jiale Wang

22. Regional Groundwater Potential Analysis Using Classification and Regression Trees
Bahram Choubin, Omid Rahmati, Freidoon Soleimani, Hossein Alilou, Ehsan Moradi, and Nasrin Alamdari

23. Comparative Evaluation of Decision-Forest Algorithms in Object-Based Land Use and Land Cover Mapping
Ismail Colkesen and Taskin Kavzoglu

24. Statistical Modelling of Landslides: Landslide Susceptibility and Beyond
Stefan Steger and Christian Kofler

25. Assessing the Vulnerability of Groundwater to Salinization Using GIS-Based Data Mining Techniques in a Coastal Aquifer
Alireza Motevalli, Hamid Reza Pourghasemi, Hossein Hashemi, and Vahid Gholami

26. A Framework for Multiple Moving Objects Detection in Aerial Videos
Bahareh Kalantar, Alfian Abdul Halin, Husam Abdulrasool H. Al-Najjar, Shattri Mansor, John L. van Genderen, Helmi Zulhaidi M. Shafri, and Mohsen Zand

27. Modelling Soil Burn Severity Prediction for Planning Measures to Mitigate Post Wildfire Soil Erosion in NW Spain
José M. Fernández-Alonso, Cristina Fernández, Stefano Arellano, and José A. Vega

28. Factors Influencing Regional Scale Wildfire Probability in Iran: An Application of Random Forest and Support Vector Machine
Abolfazl Jaafari and Hamid Reza Pourghasemi

29. Land Use/Land Cover Change Detection and Urban Sprawl Analysis
Cláudia M. Viana, Sandra Oliveira, Sérgio C. Oliveira, and Jorge Rocha

30. Spatial Modeling of Gully Erosion: A New Ensemble of CART and GLM Data Mining Algorithms
Amiya Gayen and Hamid Reza Pourghasemi

31. Multi-Hazard Exposure Assessment on the Valjevo City Road Network
Marjanović Miloš, Abolmasov Biljana, Milenković Svetozar, Đurić Uroš, Krušić Jelka, and Mileva Samardžić-Petrović

32. Producing a Spatially Focused Landslide Susceptibility Map Using an Ensemble of Shannon's Entropy and Fractal Dimension (The Ziarat Watershed, Iran)
Aiding Kornejady and Hamid Reza Pourghasemi

33. A Conceptual Model on Relationship between Plant Spatial Distribution and Desertification Trend in Rangeland Ecosystems
Hamid Reza Pourghasemi, Narges Kariminejad, and Mohsen Hosseinalizadeh

Product details

  • Edition: 1
  • Latest edition
  • Published: January 21, 2019
  • Language: English

About the editors

HP

Hamid Reza Pourghasemi

Hamid Reza Pourghasemi is a professor of watershed management engineering in the College of Agriculture, Shiraz University, in Iran. His main research interests are GIS-based spatial modelling using machine learning/data mining techniques in different fields such as landslides, floods, gully erosion, forest fires, land subsidence, species distribution modelling, and groundwater/hydrology. Professor Pourghasemi also works on multi-criteria decision-making methods in natural resources and environmental science. He has published over 230 peer-reviewed papers in high-quality journals and seven edited books for Springer and Elsevier and is an active reviewer for over 90 international journals. He was selected as one of the five young scientists under 40 by The World Academy of Science (TWAS 2019) and was a highly cited researcher in 2019 and 2020
Affiliations and expertise
Professor, Department of Natural Resources and Environment Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

CG

Candan Gokceoglu

Candan Gokceoglu is Professor and Chairman of the Applied Geology Division at Hacettepe University. He has published more than 175 articles in academic journals and is an Associate Editor of the Elsevier journal Computers and Geosciences.
Affiliations and expertise
Professor and Chairman, Applied Geology Division, Hacettepe University, Ankara, Turkey

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