Kooperativer Bibliotheksverbund

UID:

Format: Online-Ressource

ISSN: 2194-9034

Content: Abstract. On 6 February 2023, two major earthquakes occurred in the East Anatolian Fault Zone (EAFZ) of Türkiye. The EAFZ forms the east border of the Anatolian Plate. The magnitude 7.7 and 7.5 Kahramanmaraş – Türkiye Earthquakes that struck southern Türkiye and resulted in common destruction in 11 provinces in the region. Total 6 main fault segments of the EAFZ ruptured during the earthquake sequence on 6 February 2023, and approximately 400 km surface rupture occurred. The life losses are reported as over 50000, and approximately 300,000 buildings were collapsed or severely damaged. In addition to damages on the buildings and the infrastructures, liquefactions, landslides, rockfalls, and rock avalanches were also observed during the earthquake sequence. The purpose of this study is to present a general overview on the 6 February 2023 Earthquake sequence.

In: volume:XLVIII-M-1-2023

In: year:2023

In: pages:417-424

In: extent:8

In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Katlenburg-Lindau : Copernicus Publications, [2011?]-, XLVIII-M-1-2023 (2023), 417-424 (gesamt 8), 2194-9034

Language: English

DOI: 10.5194/isprs-archives-XLVIII-M-1-2023-417-2023

URN: urn:nbn:de:101:1-2023061504380066120005

URL: https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-417-2023

URL: https://nbn-resolving.org/urn:nbn:de:101:1-2023061504380066120005

URL: https://d-nb.info/1292771097/34

URL: https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/417/2023/isprs-archives-XLVIII-M-1-2023-417-2023.pdf

URL: https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/417/2023/

UID:

Format: S. 841 - 974

Series Statement: Expert systems with applications 40.2013,3

Language: English

Keywords: Konferenzschrift

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Format: 1 Online-Ressource (xxviii, 770 Seiten) , Illustrationen, Diagramme

ISBN: 9780128156957 , 9780128152263

Note: Literaturangaben

Additional Edition: Erscheint auch als Druck-Ausgabe 9780128152263

Language: English

Subjects: Geography

DOI: 10.1016/C2017-0-02950-6

URL: https://doi.org/10.1016/C2017-0-02950-6

URL: https://www.sciencedirect.com/book/9780128152263

UID:

Format: 1 Online-Ressource (xxviii, 770 Seiten) , Illustrationen, Diagramme, Karten

ISBN: 9780128156957

Note: Literaturangaben

Additional Edition: 9780128152263

Language: English

Subjects: Geography

DOI: 10.1016/C2017-0-02950-6

UID:

Format: xxviii, 770 Seiten , Illustrationen, Diagramme, Karten, Fotografien (farbig)

ISBN: 9780128152263

Additional Edition: Erscheint auch als Online-Ausgabe 9780128156957

Language: English

Subjects: Geography

Keywords: Umweltwissenschaften ; Geoinformationssystem ; R ; Konferenz Fernerkundung, Stand und Entwicklungstendenzen ; Raum ; Modellierung ; Aufsatzsammlung

URL: Inhaltsverzeichnis

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Format: 1 online resource (800 pages)

Content: "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."--Publisher's website.

Note: Spatial Analysis of Extreme Rainfall Values Based on Support Vector Machines Optimized by Genetic Algorithms: The Case of Alfeios Basin, Greece / , Remotely Sensed Spatial and Temporal Variations of Vegetation Indices Subjected to Rainfall Amount and Distribution Properties / , Numerical Recipes for Landslide Spatial Prediction by Using R-INLA: A Step-By-Step Tutorial / , Geospatial Multicriteria Decision Analysis in Forest Operational Planning / , Parameter Optimization of KINEROS2 Using Particle Swarm Optimization Algorithm within R Environment for Rainfall-Runoff Simulation / , Land-Subsidence Spatial Modeling Using the Random Forest Data-Mining Technique / , 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 / , Application of SWAT and MCDM Models for Identifying and Ranking Suitable Sites for Subsurface Dams / , Habitat Suitability Mapping of Artemisia aucheri Boiss Based on the GLM Model in R / , Flood-Hazard Assessment Modeling Using Multicriteria Analysis and GIS: A Case Study: Ras Gharib Area, Egypt / , Landslide Susceptibility Survey Using Modeling Methods / , Prediction of Soil Disturbance Susceptibility Maps of Forest Harvesting Using R and GIS-Based Data Mining Techniques / , Spatial Modeling of Gully Erosion Using Linear and Quadratic Discriminant Analyses in GIS and R / , Artificial Neural Networks for Flood Susceptibility Mapping in Data-Scarce Urban Areas / , Modeling the Spatial Variability of Forest Fire Susceptibility Using Geographical Information Systems and the Analytical Hierarchy Process / , Prioritization of Flood Inundation of Maharloo Watershed in Iran Using Morphometric Parameters Analysis and TOPSIS MCDM Model / , A Robust Remote Sensing-Spatial Modeling-Remote Sensing (R-M-R) Approach for Flood Hazard Assessment / , Prioritization of Effective Factors on Zataria Multiflora Habitat Suitability and Its Spatial Modeling / , Prediction of Soil Organic Carbon and its Mapping Using Regression Analyses and Remote Sensing Data in GIS and R / , 3D Reconstruction of Landslides for the Acquisition of Digital Databases and Monitoring Spatiotemporal Dynamics of Landslides based on GIS Spatial Analysis and UAV Techniques / , A Comparative Study of Functional Data Analysis and Generalized Linear Model Data-Mining Techniques for Landslide Spatial Modeling / , Regional Groundwater Potential Analysis Using Classification and Regression Trees / , Comparative Evaluation of Decision-Forest Algorithms in Object-Based Land Use and Land Cover Mapping / , Statistical Modelling of Landslides: Landslide Susceptibility and Beyond / , Assessing the Vulnerability of Groundwater to Salinization Using GIS-Based Data-Mining Techniques in a Coastal Aquifer / , A Framework for Multiple Moving Objects Detection in Aerial Videos / , Modeling Soil Burn Severity Prediction for Planning Measures to Mitigate Post Wildfire Soil Erosion in NW Spain / , Factors Influencing Regional Scale Wildfire Probability in Iran: An Application of Random Forest and Support Vector Machine / , Land Use/Land Cover Change Detection and Urban Sprawl Analysis / , Spatial Modeling of Gully Erosion: A New Ensemble of CART and GLM Data Mining Algorithms / , Multi-Hazard Exposure Assessment on the Valjevo City Road Network / , Producing a Spatially Focused Landslide Susceptibility Map Using an Ensemble of Shannon's Entropy and Fractal Dimension (Case Study: The Ziarat Watershed, Iran) / , A Conceptual Model of the Relationship between Plant Distribution and Desertification Trend in Rangeland Ecosystems Using R Software /

Additional Edition: ISBN 9780128152263

Additional Edition: ISBN 0128152265

Additional Edition: ISBN 9780128156957

Additional Edition: ISBN 0128156953

Language: English

UID:

Format: Online-Ressource , online resource.

ISSN: 1435-9537 , 1435-9537

In: volume:77

In: number:2

In: day:12

In: month:3

In: year:2018

In: pages:761-762

In: date:5.2018

In: Bulletin of engineering geology and the environment, Berlin ; Heidelberg : Springer, 1970-, 77, Heft 2 (12.3.2018), 761-762, 5.2018, 1435-9537

Language: English

DOI: 10.1007/s10064-018-1260-3

URN: urn:nbn:de:101:1-2018070422163863439023

URL: https://doi.org/10.1007/s10064-018-1260-3

URL: https://nbn-resolving.org/urn:nbn:de:101:1-2018070422163863439023

URL: https://d-nb.info/1162260459/34

URL: http://dx.doi.org/10.1007/s10064-018-1260-3

UID:

Format: 1 Online-Ressource

ISBN: 0128156953

Content: Front Cover; Spatial Modeling in GIS and R for Earth and Environmental Sciences; Copyright Page; Dedication; Contents; List of Contributors; 1 Spatial Analysis of Extreme Rainfall Values Based on Support Vector Machines Optimized by Genetic Algorithms: The Case of ... ; 1.1 Introduction; 1.2 The Study Area; 1.3 Methodology and Data; 1.4 Results; 1.5 Performance Criteria; 1.6 Discussion; 1.7 Conclusions; References; 2 Remotely Sensed Spatial and Temporal Variations of Vegetation Indices Subjected to Rainfall Amount and Distribution Prope ... ; 2.1 Introduction; 2.2 Materials and Methods

Content: 2.2.1 Study Area2.2.2 Data; 2.2.3 Vegetation Indices; 2.2.4 Rainfall Distribution Parameters; 2.3 Results and Discussion; 2.3.1 Vegetation Indices; 2.3.1.1 Normalized Difference Vegetation Index; 2.3.1.2 Spatial Variations of the Normalized Difference Vegetation Index; 2.3.1.3 Green Normalized Difference Vegetation Index; 2.3.1.4 Global Environmental Monitoring Index; 2.3.2 Spatial Normalized Differential Reflectance and Shortwave Crop Reflectance Index; 2.3.3 Rainfall Properties Versus Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index, Glob ...

Content: 2.3.3.1 Prespring Rainfall2.3.3.2 Cumulative Rainfall; 2.3.3.3 Rainfall Distribution; 2.4 Conclusion; References; Further Reading; 3 Numerical Recipes for Landslide Spatial Prediction Using R-INLA: A Step-by-Step Tutorial; 3.1 Introduction; 3.2 Dataset Description and Preparation; 3.2.1 Multiple Occurrence Regional Landslide Event, Messina, 2009; 3.2.2 Computing Slope Units in GIS; 3.3 Point Process Modeling and Estimation Using R-INLA; 3.3.1 Preprocessing; 3.3.2 Fitting a Cox Point Process Model Using R-INLA; 3.4 Results; 3.4.1 Estimated Fixed and Random Effects

Content: 3.4.2 Estimated Landslide Intensity at Various Spatial Resolutions3.4.3 Model Checking and Goodness-of-Fit Assessment; 3.4.4 Cross-Validation Study and Out-of-Sample Predictive Skill; 3.5 Discussion; 3.6 Conclusion; References; 4 Geospatial Multicriteria Decision Analysis in Forest Operational Planning; 4.1 Introduction; 4.1.1 Multicriteria Decision Elements; 4.1.1.1 Decision-Maker Analysis; 4.1.1.2 Hierarchical Structure; 4.1.1.3 Decision Elements; Criteria and Subcriteria; Decision Alternatives; 4.1.1.4 Interpretation Findings; 4.1.2 Classification of Spatial Decision Support System

Content: 4.1.2.1 Geostatistical Analysis With R packages4.1.2.2 Forest Management Hierarchy; Strategic Planning; Tactical Planning; Operational Planning; 4.1.3 A Perspective of Forest Resource Management in Iran; 4.1.3.1 General Information; 4.1.3.2 The Role of Decision Support Systems in Iranian Forestry; 4.2 Planning Problems; 4.3 Methods; 4.3.1 Multicriteria Decision Analysis; 4.3.2 Geostatistical Analysis; 4.3.3 Spatial Modeling Procedure; 4.3.4 Model Application; 4.4 Results; 4.4.1 The Current Conditions of the Terrain; 4.5 Discussion; 4.6 Conclusions; Acknowledgments; References; Further Reading

Content: "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."--Provided by publisher

Note: Includes bibliographical references and index

Additional Edition: 0128152265

Additional Edition: Erscheint auch als Druck-Ausgabe Spatial modeling in GIS and R for earth and environmental sciences Amsterdam, Netherlands ; Cambridge, MA, United States : Elsevier, 2019 0128152265

Additional Edition: 9780128152263

Language: English

Keywords: Electronic books

URL: Volltext  (lizenzpflichtig)

UID:

Format: xxviii, 770 Seiten , Illustrationen, Diagramme, Karten

ISBN: 9780128152263

Note: Literaturangaben und Index

Language: English

Keywords: Umweltwissenschaften ; Geowissenschaften ; Fernerkundung ; Geoinformationssystem ; R

URL: Inhaltsverzeichnis

URL: https://www.elsevier.com/books/spatial-modeling-in-gis-and-r-for-earth-and-environmental-sciences/pourghasemi/978-0-12-815226-3

UID:

Format: 1 Online-Ressource

ISBN: 0128156953

Note: Includes bibliographical references and index

Additional Edition: 0128152265

Language: English

URL: Volltext