Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object. It deals with the data collection of natural and man-made objects on the Earth to show their geographic locations as well as characteristics on the maps. Remote sensing systems, which provide a global perspective and a wealth of data (the panchromatic, multispectral, thermal, hyperspectral, stereo, LiDAR, etc.) about the Earth systems at various resolutions, allow users to capture, visualize, and analyze objects and features on the Earth’s surface for faster decision making, based on the current and future state of land resources. Remotely sensed data today can be applied for a large number of applications, and is especially important for studies of the Earth that require frequent monitoring, such as inventories and surveys in agriculture, urban, disaster, floods, hydrography, geology, mineralogy, land use, etc. In addition, it is highly valuable as it can provide information about regions that are difficult or dangerous to access directly. With the introduction of computer and automation, algorithms are available which can analyze the digital remote sensing data quickly, economically, and accurately, and provide useful information, as per the need of applications. Addressing the need for updated information in remote sensing, this book consists of two major divisions: theory covering principal topics and different applications. The book discusses the basic concept of remote sensing, remote sensing systems, processing, classification, and applications of data. Remote Sensing: Theory and Applications stands as a definitive, masterfully crafted guide to one of the most transformative geospatial technologies of our time. This book serves as both an intellectual blueprint and a practical toolkit, bridging the gap between foundational physics and the cutting-edge computation required to interpret our changing planet. It is an essential resource for students, researchers, and industry professionals across civil engineering, data science, environmental tracking, and urban management.
Antonio Velasco is a distinguished geospatial scientist, researcher, and educator whose career spans over two decades of cutting-edge innovation in earth observation systems. Holding a Ph.D. in Geomatics and Remote Sensing, Dr. Velasco has dedicated his life to decoding the complex languages of our planet from space. His authoritative academic foundation—combined with years of field research across diverse ecosystems and close collaboration with global aerospace agencies—places him at the absolute forefront of the modern geospatial revolution. In Remote Sensing: Theory and Application, Dr. Velasco bridges the gap between dense electromagnetic physics and real-world planetary management. As a scholar who has spearheaded pioneering projects in satellite image processing, machine learning integration, and environmental monitoring, he writes not just as an academic, but as a practitioner who has shaped the evolution of the field. His extensive qualifications include a legacy of peer-reviewed publications, keynote addresses at international geospatial summits, and a proven track record of training the next generation of engineers and data scientists. This book represents the culmination of his life’s work, offering readers an uncompromising, rigorous, and deeply inspiring roadmap to understanding the technology that maps our changing world. Beyond his academic tenure, Velasco has authored over 50 peer-reviewed papers in top-tier journals, focusing on machine learning applications in radar polarimetry and thermal infrared sensing.
Preface 1. Introduction: Geographical Information Systems Historical Overview Geographical Information Systems Definitions Of GIS 2. Remote Sensing: Concept And Scope Introduction History Of Remote Sensing Concepts In Remote Sensing Scope Of Remote Sensing Conclusion 3. Data Models And Axioms: Formal Abstractions Of Reality Conceptual Models Of World Geographical Phenomena Conceptual Models Of Space: Entities Or Fields Tessellations Of Continuous Fields Display Of Geographical Primitives Using Vector And Raster Approaches Data Modelling And Spatial Analysis 4. Computerisation Of Geographical Data Processing Data In The Computer Data Organization And Coding Using Hexadecimal Coding The Basic Data Models For Input To The Computer Data Base Structures And Data Organisation Database Structures And Database Management Database Management Systems Data Organisation In Vector Data Structures Data Structures For Spatial Data: The Choice Between Raster And Vector Database Storage Of Vector And Raster Data Structures 5. Data Input, Verification, Storage, And Output Geographical Data Sources Data Collectors And Providers Acquiring Digital Datasets From A Data Supplier Data Presentation 6. Creating Continuous Surfaces From Point Data Interpolation Global Prediction Using Classification Models Global Interpolation Using Trend Surfaces Nearest Neighbours: Thiessen Polygons Digital Elevation Models: Case Of Continuous Surfaces Created By Interpolation 7. The Analysis Of Discrete Entities In Space Spatial Analysis Is More Than Asking Questions Deriving New Attributes For Spatial Entities Operations On Attributes Of Multiple Entities That Overlap In Space 8. Optimal Interpolation Using Geostatistics Regionalised Variable Theory And Kriging Fitting Variogram Models Isotropic And Anisotropic Variation Variograms Showing Spatial Variation At Several Scales Kriging Using Extra Information Probabilistic Kriging Relative Merits Of Different Interpolation Methods 9. Spatial Analysis Using Continuous Fields Basic Operations For Spital Analysis With Discretised Continuous Fields Spatial Analysis Using Square Windows Higher Order Derivatives Of A Continuous Surface Deriving Surface Topology And Drainage Networks Using Ldd Network For Spatial Analysis Summary Of Operators Used On Continuous Fields And Its Products 10. Errors And Quality Control Sources Of Errors In Spatial Data Factors Affecting The Reliability Of Spatial Data Faults Stemming From Assumptions Concerning The Exactness Of Spatial Entities Errors Resulting From Rasterizing A Vector Map Errors Associated With Overlaying Two Or More Polygon Networks 11. Types Of Remote Sensing: Air Borne And Space Borne Airborne Platforms Spaceborne Platforms 12. Aerial Photos: Types And Characteristics Introduction Types Of Aerial Photograph Elements Of Aerial Photo Interpretation 13. Remote Sensing Satellites: Platform And Sensors History Of India’s Space Programme History Of International Space Programme Sensors Installed On Ground Based Platforms Classification Of Sensors Multispectral Imaging Sensor Systems Satellite Characteristics: Swaths And Orbi 14. Remote Sensing Data Processing And Applications Visual And Image Processing Techniques Elements Of Visual Image Interpretation Minimum Mapping Unit Digital Image Processing Bibliography Index
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