In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management.

Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.

Scholars and practitioners can now enhance their analytical capabilities and unlock deeper insights from geospatial data with the guidance of this pivotal book. From manipulating data structures to employing machine learning algorithms, it equips readers with the tools and knowledge to tackle complex geospatial problems confidently and precisely. With Ethics, Machine Learning, and Python in Geospatial Analysis, the era of cumbersome manual processes gives way to a new frontier of efficient, data-driven analysis, empowering scholars to make meaningful contributions to geospatial science.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Advanced Analysis Techniques
Climate Change
Complex Data Sets
Data Analysis Ethics
Data Interpretation
Data Structures
Geospatial Analysis Ethics
Machine Learning
Manual Approaches
Python
Resource Management
Rule-Based Strategies

Table of Contents

Search this Book:

Reset

Editor/Author Biographies

Mohammad Gouse Galety has been working in CS since 1999. He is now a Professor in the CS department of Samarkand International University of Technology, Samarkand, Uzbekistan. He holds two Ph. D.s in web mining and image processing of CS and two master's degrees in computers. The first master's degree is in computer applications, and the second is in computer science. His research interests span computer and information science, mainly web mining, IoT, and AI. He (co) authorizes over 50 journal papers and international conference proceedings indexed by Springer and Scopus, four patents, and five books. He is a Fellow of the IEEE and ACM. Since 1999, he has served in different national and international organizations like Sree Vidyanikethan Degree College, India; Emeralds Degree College, Tirupati, India; Brindavan College of Engineering, India; Kuwait Educational Center, Kuwait, Ambo University, Ethiopia; Debre Berhan University, Ethiopia, Lebanese French University, Erbil, Iraq, CUE, Erbil, Iraq. He teaches undergraduate and postgraduate students several courses on computer science and information technology/science engineering.

Arul Kumar Natarajan currently serves as an Assistant Professor in the Department of Computer Science at the Samarkand International University of Technology in Uzbekistan. He earned his Doctor of Philosophy degree from Bharathidasan University, India 2017. Concurrently, he is engaged in postdoctoral research in Generative AI for Cybersecurity at the Singapore Institute of Technology, Singapore. Throughout his 14-year teaching career, Dr. Arul has held esteemed positions at various institutions, including Christ University, Bishop Heber College in India, and Debre Berhan University in Ethiopia. Dr. Arul has made significant contributions to academia, specializing in cybersecurity and artificial intelligence, evidenced by his portfolio of scholarly works. He has authored 32 international publications indexed in Scopus and 03 international publications and has delivered 34 conference presentations. Additionally, he has edited and published two books with IGI Global Publisher, USA. In addition to his academic pursuits, Dr. Arul is a prolific innovator, holding 17 patents in India and 01 granted patent in the United Kingdom across diverse domains, including communication and computer science. He demonstrates proficiency in Networking and Cybersecurity, having completed the CCNA Routing and Switching Exam from CISCO and the Networking Fundamentals exam from Microsoft. He maintains a sincere interest in GenAI for Cybersecurity.

Tesfaye Fufa Gedefa who holds a Bachelor's Degree in Information Technology from Jima University (2012) and a Master of Science in Software Engineering from Adama Science and Technology University, transitioned from lecturing at Debre Berhan University to his current role as an Associate Researcher II at the Space Science and Geospatial Institute. His research journey encompasses diverse fields such as artificial intelligence, network security, cloud computing, big data, image processing, data science, and disaster management. With a keen interest in extending his expertise, Tesfaye plans to delve into new sensor development and calibration, big data analytics, data assimilation, and integration, alongside image fusion techniques for urban climate monitoring, disaster risk reduction, and food security. He is committed to applying space technology across multidisciplinary domains, leveraging Python programming to amplify the impact of his research endeavors. Through international collaborations and a dedication to advancing knowledge, Tesfaye aims to make meaningful contributions at the intersection of technology and societal challenges.

Archiving

All of IGI Global's content is archived via the CLOCKSS and LOCKSS initiative. Additionally, all IGI Global published content is available in IGI Global's InfoSci^® platform.