Advances in remote sensing technology and the three poles

Advances in remote sensing technology and the three poles

ADVANCES IN REMOTE SENSING TECHNOLOGY AND THE THREE POLES Covers recent advances in remote sensing technology applied to the "Three Poles", a concept encompassing the Arctic, Antarctica, and the Himalayas Advances in Remote Sensing Technology and the Three Poles is a multidisciplinary appr...

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Detalles Bibliográficos
Otros Autores: Pandey, Manish (Assistant professor), author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, NJ : John Wiley & Sons, Inc [2023]
Materias:
Remote sensing > Polar regions.
Remote sensing > Hindu Kush-Himalayan Region.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755210606719
Tabla de Contenidos:
  • Intro
  • Advances in Remote Sensing Technology and the Three Poles
  • Contents
  • About the Editors
  • Notes on Contributors
  • Foreword
  • Preface
  • List of Acronyms
  • Section I Earth Observation (EO) and Remote Sensing (RS) Applications in Polar Studies
  • 1 The Three Poles: Advances in Remote Sensing in Relation to Spheres of the Planet Earth
  • 1.1 Introduction
  • 1.1.1 Earth as a System and Components of the Earth System
  • 1.1.2 Role of the "Three Poles" and the Three Poles Regions in the Earth System
  • 1.1.2.1 Defining the Three Poles, Three Poles Regions, and Their Geographical Extent
  • 1.1.2.2 Interaction Among Components of the Earth System and Role of the Three Poles
  • 1.1.3 Advancement of RS Technologies in Relation to Their Application in the Three Poles Regions
  • 1.1.3.1 Remote Sensing Technology Advancements
  • 1.1.3.2 Role of Remote Sensing (RS) in Mapping/Monitoring/Quantitative Analysis of Sub-Systems of Our Planet in the Three Poles Regions
  • 1.2 Aim of the Book and Its Five Sections
  • 1.3 Overview of the Contributing Chapters Covering Research About Different Aspects of the Sub-Systems of Our Planet in the Three Poles Regions
  • 1.4 Summary and Recommendations
  • References
  • 2 Continuous Satellite Missions, Data Availability, and Nature of Future Satellite Missions with Implications to Polar Regions
  • 2.1 Introduction
  • 2.1.1 Types of Orbit
  • 2.1.1.1 High Earth Orbit (HEO)
  • 2.1.1.2 Medium Earth Orbit (MEO)
  • 2.1.1.3 Semi-Synchronous Orbit
  • 2.1.1.4 Molniya Orbit
  • 2.1.1.5 Low Earth Orbit (LEO)
  • 2.1.1.6 Polar Orbit and Sun-Synchronous Orbit
  • 2.1.1.7 Lagrange's Point
  • 2.2 Satellite Missions and Data Availability
  • 2.3 Future Satellite Missions
  • 2.4 Applicability of Satellite Products in Three Poles Regions
  • 2.5 Challenges and Limitations
  • 2.6 Summary
  • Acknowledgments
  • References.
  • 3 Assessing the Accuracy of Digital Elevation Models for Darjeeling-Sikkim Himalayas
  • 3.1 Introduction
  • 3.2 Study Area
  • 3.3 Materials and Methods
  • 3.3.1 Generation of Cartosat-1 DEM and Orthoimage
  • 3.3.2 TanDEM-X
  • 3.3.3 ALOS PALSAR
  • 3.3.4 DGPS Survey for Obtaining Ground Control Points (GCPs)
  • 3.3.5 Datum Transformation
  • 3.3.6 Accuracy Assessment Methods
  • 3.3.6.1 Vertical Accuracy
  • 3.3.6.2 Spatial Accuracy
  • 3.4 Results and Discussion
  • 3.4.1 Vertical Accuracy Assessment: Comparison of DEMs With Reference to GCPs
  • 3.4.2 Vertical Accuracy of DEMs for Different Land Use Classes
  • 3.4.2.1 Dense Forest
  • 3.4.2.2 Open Forest
  • 3.4.2.3 Tea Garden
  • 3.4.2.4 Built-up Area
  • 3.4.3 Spatial Accuracy Assessment: Comparison of DEMs With Reference to Stream Networks
  • 3.5 Conclusions
  • Acknowledgments
  • References
  • 4 An Overview of Morphometry Software Packages, Tools, and Add-ons
  • 4.1 Introduction
  • 4.2 Overview of Morphometry Tools and Toolboxes
  • 4.3 Stand-Alone Tools
  • 4.4 Tools that Run within Coding Bases
  • 4.5 Conclusion
  • References
  • 5 Landscape Modeling, Glacier and Ice Sheet Dynamics, and the Three Poles: A Review of Models, Softwares, and Tools
  • 5.1 Introduction
  • 5.2 Taxonomy
  • 5.2.1 Geomorphic Process-Based Models
  • 5.2.2 Classification Based on Process of Modeling
  • 5.2.2.1 Based on Geomorphic Processes
  • 5.2.2.2 Based on Modeling Process
  • 5.3 Working Principles for Geomorphological Models
  • 5.3.1 Soil Production
  • 5.3.2 Hillslope Transport
  • 5.3.3 Land Sliding
  • 5.3.4 Fluvial Incision and Transport
  • 5.3.5 Glacial Erosion
  • 5.4 Landscape Evolution Models
  • 5.4.1 DEM-Based Models
  • 5.4.2 SIBERIA
  • 5.4.3 GOLEM
  • 5.4.4 CASCADE
  • 5.4.5 ZScape
  • 5.4.6 CHILD
  • 5.4.7 CAESAR
  • 5.4.8 APERO
  • 5.4.9 SIGNUM (Simple Integrated Geomorphological Numerical Model).
  • 5.4.10 TTLEM (TopoToolbox Landscape Evolution Model) 1.0
  • 5.5 Other Models
  • 5.5.1 DELIM
  • 5.5.2 EROS
  • 5.5.3 Landscape Evolution Model Using Global Search
  • 5.5.4 eSCAPE
  • 5.5.5 r.sim.terrain 1.0
  • 5.6 Combined/Application-Specific Models
  • 5.7 Machine Learning Models
  • 5.8 LEMs Developed for Glaciated Landscapes
  • 5.9 Some Significant Glacier Evolution Models
  • 5.10 Models Developed for Alpine Regions
  • 5.11 Models Developed for the Arctic Regio
  • 5.12 Models Developed for the Antarctic Region
  • 5.13 Conclusion and Future Prospects
  • Acknowledgment
  • Declaration of Competing Interest
  • References
  • 6 Spectral Indices Across Remote Sensing Platforms and Sensors Relating to the Three Poles: An Overview of Applications, Challenges, and Future Prospects
  • 6.1 Introduction
  • 6.2 Database and Methodology
  • 6.3 Rationale of Different Spectral Indices Across RS Sensors and Platforms
  • 6.4 RS Sensors and Platforms: Characteristics (Spatial, Temporal, Spectral, and Radiometric Resolutions)
  • 6.5 Most Widely and Popularly Used Spectral Indices
  • 6.5.1 Spectral Indices and Lithosphere
  • 6.5.2 Spectral Indices and Hydrosphere
  • 6.5.3 Spectral Indices and Atmosphere
  • 6.5.4 Spectral Indices and Biosphere
  • 6.5.5 Spectral Indices and Anthroposphere
  • 6.6 Thematic Evolution and Trends
  • 6.6.1 Thematic and Network Maps
  • 6.7 Summary and Recommendations
  • Acknowledgments
  • References
  • Section II Antarctica: The Southernmost Continent Having the South Pole Environment and Remote Sensing
  • 7 Glacier Dynamics in East Antarctica: A Remote Sensing Perspective
  • 7.1 Introduction
  • 7.2 Satellite Remote Sensing of Glacier Dynamics in East Antarctica
  • 7.3 Glacier Velocity Estimation Using Remote Sensing
  • 7.3.1 Glacier Velocity Estimation Using SAR Interferometry
  • 7.3.2 Glacier Velocity Estimation Using Offset Tracking.
  • 7.4 Remote Sensing Based Dynamics of PRG: A Case Study
  • 7.4.1 Data and Methods
  • 7.4.2 Results and Discussion
  • 7.4.2.1 Ice Front Location
  • 7.4.2.2 Glacier Velocity Over the Period of 2016-2019
  • 7.4.3 Summary and Conclusion
  • References
  • 8 Terrestrial Deglaciation Signatures in East Antarctica
  • 8.1 Introduction
  • 8.2 Geomorphology
  • 8.2.1 East Antarctica
  • 8.3 Landform Variation Concerning Various Sectors and Elevation
  • 8.3.1 Dronning Maud Land
  • 8.3.2 Enderby Land
  • 8.3.3 Mac. Robertson Land, Amery Ice Shelf, and Prince Elizabeth Land
  • 8.3.4 Wilkes Land
  • 8.4 Chronology
  • 8.4.1 Dronning Maud Land
  • 8.4.2 Enderby Land
  • 8.4.3 Mac. Robertson Land, Amery Ice Shelf 's and Princess Elizabeth Land
  • 8.4.4 Wilkes Land
  • 8.5 Discussion
  • 8.6 Conclusion
  • Acknowledgments
  • References
  • 9 Geospatial Tools for Monitoring Vertebrate Populations in Antarctica With a Note on the Ecological Component of the Indian Antarctic Program
  • 9.1 Introduction
  • 9.2 Novel Geospatial Tools for Biodiversity Monitoring in Antarctica
  • 9.2.1 Unmanned Aerial Vehicles
  • 9.2.2 Satellite Imagery
  • 9.3 Spatial Mapping of Seabirds Under the Indian Antarctic Program
  • 9.4 Recommendations to Incorporate New Tools for Antarctic Wildlife Monitoring Program
  • 9.5 Conclusion
  • Acknowledgments
  • References
  • 10 Bryophytes of Larsemann Hills, East Antarctica and Future Prospects
  • 10.1 Introduction
  • 10.2 Study Area
  • 10.3 Materials and Methods
  • 10.4 Taxonomic Treatment
  • 10.5 Phytosociological Studies
  • 10.6 Results and Discussion
  • 10.7 Future Prospects
  • Acknowledgments
  • References
  • 11 Antarctic Sea Ice Variability and Trends Over the Last Four Decades
  • 11.1 Introduction
  • 11.2 Datasets and Methods
  • 11.2.1 Sea Ice Extent Analysis
  • 11.2.2 Analysis of Physical Parameters
  • 11.3 Results and Discussion.
  • 11.3.1 Sea Ice Variability in the Southern Ocean
  • 11.3.2 Sea Ice Distribution With Respect to Ocean-Atmospheric Temperature
  • 11.4 Summary and Conclusions
  • Acknowledgments
  • References
  • Section III Himalayas: The Third Pole Environment and Remote Sensing
  • 12 Some Unresolved Problems in the Himalaya: A Synoptic View
  • 12.1 Introduction
  • 12.2 Stratigraphic Ages, Basin Configuration, and Palaeontology
  • 12.3 Sedimentology
  • 12.4 Tectonics and Structure
  • 12.5 Magmatism and Geochronology
  • 12.6 Metamorphism
  • 12.7 Mineral Deposits
  • 12.8 Palaeomagnetic Studies
  • 12.9 Glaciological Studies
  • 12.10 Geomorphological Studies
  • 12.11 Conclusion
  • Acknowledgments
  • References
  • 13 Fluctuations of Kolahoi Glacier, Kashmir Valley, Its Assessment With Tree-Rings of Pinus wallichiana and Comparable Satellite Imageries and Field Survey Records
  • 13.1 Introduction
  • 13.2 Tree-Ring Sampling Site and Data Acquisition
  • 13.3 Tree-Ring Chronology and Its Assessments
  • 13.4 Fluctuations of Kolahoi Glacier: Existing Records and Its Assessment With Tree-Rings
  • 13.5 Conclusions
  • Acknowledgements
  • References
  • 14 Applications of ICESat-2 Photon Data in the Third Pole Environment
  • 14.1 Introduction
  • 14.2 Brief Background About NASA's ICESat-2 Mission
  • 14.3 Terrain Profiling From ICESat-2 Photon Elevations Over a Mountainous Region
  • 14.4 Longitudinal Profiling of Rivers in a Mountainous Region
  • 14.5 Inland Water Level Detection in Mountainous Regions Using ICESat-2 Photon Data
  • 14.6 Inferring Annual Variations of Water Levels in Mountain Lakes Using ICESat-2's ATL13 Data Product
  • 14.7 Inferring Lake Ice Phenology in Mountainous Regions Using ICESat-2 Photon Data
  • 14.8 Estimating Tree Heights in Mountain Regions Using ICESat-2 Photon Data
  • 14.9 Utilization of ICESat-2 Photon Data to Generate Digital Elevation Models.
  • 14.10 Conclusion.

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