With the emergence of smart technology and automated systems in today’s world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications.

Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.

Coverage:

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

Agricultural Sector
Artificial Intelligence
Deep Learning
Field Spectra
Geospatial Data
High-Resolution Remote Sensing Imagery
Hyperspectral Images
Internet of Things (IoT)
Machine Learning
Spatiotemporal Data Engineering
Spatiotemporal Outlier Detection
Vehicle Detection

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Editor/Author Biographies

Loveleen Gaur is currently working as an adjunct professor with Taylor's University, Malaysia & University of South Pacific, Fiji and academic consultant with Australian School of Graduate Studies.She has supervised several PhD scholars, Post Graduate students, mainly in Artificial Intelligence and Data Analytics for business and healthcare. Under her guidance, the AI/Data Analytics research cluster has published extensively in high impact factor journals and has established extensive research collaboration globally with several renowned professionals. She is a senior IEEE member and Series Editor with CRC and Wiley. She has high indexed publications in SCI/ABDC/WoS/Scopus and has several Patents/copyrights on her account, edited/authored many research books published by world-class publishers. She has excellent experience in supervising and co-supervising postgraduate and PhD students internationally. An ample number of Ph.D. and master’s students graduated under her supervision. She is an external Ph.D./Master thesis examiner/evaluator for several universities globally. She has also served as Keynote speaker for several international conferences, presented several Webinars worldwide, chaired international conference sessions. Prof. Gaur has significantly contributed to enhancing scientific understanding by participating in many scientific conferences, symposia, and seminars, by chairing technical sessions and delivering plenary and invited talks. She has specialized in the fields of Artificial Intelligence, Machine Learning, Pattern Recognition, Internet of Things, Data Analytics and Business Intelligence. She has chaired various positions in International Conferences of repute and is a reviewer with top rated journals of IEEE, SCI and ABDC Journals. She has been honored with prestigious National and International awards. She has introduced courses related to Artificial Intelligence specialization including, Predictive Analytics, Deep and Reinforcement learning etc. She has vast experience teaching advanced-era specialized courses, including Predictive Analytics, Data Visualization, Social Network Analytics, Deep Learning, Power BI, Digital Marketing and Digital Innovation etc., besides other undergraduate and postgraduate courses, graduation projects, and thesis supervision.

Pradeep Garg is currently serving as Professor in Geomatics Engineering Group, Civil Engineering Department at IIT Roorkee. He is B.Tech (Civil Engg.) and M.Tech both from the University of Roorkee (now IIT Roorkee). He is a recipient of Gold Medal at IIT Roorkee to stand first during M.Tech programme, Commonwealth Scholarship Award for doing Ph.D. from University of Bristol (UK), and Commonwealth Fellowship Award to carry out post-doctoral research work at University of Reading (UK). He joined IIT Roorkee in 1982, and gradually advancing his career rose to the position of Head of the Civil Engg Department at IIT Roorkee in 2015, and then Vice Chancellor, Uttarakhand Technical University, Dehradun from 2015-2018. He was given additional charge of Vice Chancellor of a Govt. Medical University in Dehardun, for about 8 months. Prof. Garg has published more than 310 technical papers, undertaken 27 research and 94 consultancy projects and guided about 73 M.Tech and 29 Ph.D. Thesis. He has authored text books on (i) Remote Sensing, (ii) Geoinformatics, (iii) Introduction to UAVs, (iv) Digital Land Surveying, and (v) Digital mapping of soil, and (vi) Remote Sensing and Its Applications, and Edited three books and produced two technical films on Story of Mapping. He is a life member of 24 professional societies, out of which he is a Fellow member of 8 societies.

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