Geospatial Data Science Techniques and Applications

Environmental Engineering, Geospatial Data Science Techniques and Applications, Data science is about turning data into useful information and turning that information into knowledge. It is about the efforts needed to analyze and understand data in order to make decisions, predict outcomes, and identify phenomena. While most current systems and applications are prolific with data, without the appropriate techniques to understand the data, there is a breach in how they can effectively aid humans in detecting and recognizing patterns. Undoubtedly data science theories and techniques are integral for tackling real-world problems in a wide variety of disciplines and those that involve geospatial data are of prime interest and need special attention. This is because geospatial data-which are inherently multi-dimensional, multi-scale, very large, and complex-require special mathematical, statistical, and computational models and techniques beyond those applied to other data. Scientists and engineers in all geoscience disciplines and fields need appropriate techniques and tools for overcoming the challenges of converting raw geo-spatial data to information and making new knowledge. This indispensable guide discusses modern geospatial data science techniques and their use in geology, environmental studies, geography, and urban computing. It also provides case studies on the use of geospatial data science techniques in solving geospatial problems using raster data and vector data. These practical strategies based on widespread problems endow an in-depth knowledge that can be used for analyzing and solving geo-science problems in any geographic area. Professionals, researchers, developers, scientists, engineers, and students alike will benefit from this comprehensive assemblage of techniques and detailed explanations to help master new skills. Housed within these valuable chapters of Geospatial Data Science Techniques and Applications are case studies and real-world examples of applications involving geospatial data. Readers are also generously supplied with, The definition of the field of geospatial data science from a transdisciplinary perspective, Fundamentals of geocoding with the challenges associated with the logic of geocoding, Deep learning techniques applied to satellite images for pattern recognition, Visual analytical approaches to analyzing movement of massive floating car data, LiDAR technology and the type of data it produces, Approaches and techniques for spatial-temporal data understanding and analysis Book jacket.

• | Author: Taylor & Francis Group
• | Publisher: Crc Press
• | Publication Date: Jun 30, 2020
• | Number of Pages: 258 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0367572818
• | ISBN-13: 9780367572815