Author Profile

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.

About The Book

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.

Table of Contents

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