Spatial Modeling in GIS and R for Earth and Environmental Sciences

Spatial Modeling in GIS and R for Earth and Environmental Sciences

1st Edition - January 18, 2019
This is the Latest Edition
  • Editors: Hamid Reza Pourghasemi, Candan Gokceoglu
  • Paperback ISBN: 9780128152263
  • eBook ISBN: 9780128156957

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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

  • No. of pages: 798
  • Language: English
  • Copyright: © Elsevier 2019
  • Published: January 18, 2019
  • Imprint: Elsevier
  • Paperback ISBN: 9780128152263
  • eBook ISBN: 9780128156957
  • About the Editors

    Hamid Reza Pourghasemi

    Hamid Reza Pourghasemi is an Associate Professor of Watershed Management Engineering in the College of Agriculture, Shiraz University, Iran. His main research interests are GIS-based spatial modelling using machine learning/data mining techniques in various fields including as landslides, floods, gully erosion, forest fires, land subsidence, species distribution modelling, and groundwater/hydrology. Hamid Reza also works on multi-criteria decision-making methods in natural resources and environmental science. He has published over 150 peer-reviewed papers in high-quality journals and four Edited books, and is an active reviewer for over 65 international journals. Hamid Reza 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.

    Affiliations and Expertise

    Associate Professor, Watershed Management Engineering, College of Agriculture, Shiraz University, Shiraz, Fars, Iran

    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