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Geospatial Data, Information, and Intelligence
This book provides practitioners with structured methods for transforming geospatial data into the useful information they need to solve some of the world’s most pressing problems. It spotlights the importance of location for human experience in the everyday world and introduces spatial thinking as a foundation and the location mindset as a foundational perspective. The book starts by showing how geospatial analysis is part of a more general data-to-information refinement process that requires the right mindset, toolset, and skillset to achieve. The book then presents structured principles and practices to help geospatial analysts—whether in government or industry—improve their observational, analytical, and communication techniques. These techniques are part of an original framework for interpreting geospatial data and information: the Observe, Analyze, Communicate (OAC) Framework. The OAC framework helps practitioners at all levels break down the basic steps of their day-to-day practice and learn valuable tradecraft that they can employ during each step. You’ll learn how to center location as a foundational perspective in everyday life; use unique geospatial observation, analysis, and communication techniques; and know how to account for the role of uncertainty in assessment and production processes -- including utilizing special techniques to effectively communicate levels of certainty and uncertainty to your audience. You’ll also understand how pairing visual information with precise locational information serves to anchor human attention and provides an antidote to the common problem of disorientation. The book reveals specific techniques and tradecraft that will greatly benefit all practitioners working with visual and locational information. One such tradecraft called Structured Geospatial Observation Techniques (SGOT) includes a technique called the Four Cornerstones that will allow you to structure your approach to visual data and extract more attribute and contextual data from your object of focus. Another technique reveals industry and government-gleaned tips and tricks to creating finished geospatial communications in paragraphs, products, and presentations. Bringing together the authors’ combined 30 years of experience with geospatial intelligence (GEOINT), this book is a must-have practical resource for students, faculty, and practitioners of geospatial endeavors at any level of experience, especially fields that use imagery and spatial analysis. It serves as a textbook for classroom beginners and as a go-to desktop reference for professionals in their day-to-day geospatial efforts.
eBook
IMPROVING DATA QUALITY AND MANAGEMENT FOR REMOTE SENSING ANALYSIS: USE-CASES AND EMERGING RESEARCH QUESTIONS
During the last decades satellite remote sensing has become an emerging technology producing big data for various application fields every day. However, data quality checking as well as the long-time management of data and models are still issues to be improved. They are indispensable to guarantee smooth data integration and the reproducibility of data analysis such as carried out by machine learning models. In this paper we clarify the emerging need of improving data quality and the management of data and models in a geospatial database management system before and during data analysis. In different use cases various processes of data preparation and quality checking, integration of data across different scales and references systems, efficient data and model management, and advanced data analysis are presented in detail. Motivated by these use cases we then discuss emerging research questions concerning data preparation and data quality checking, data management, model management and data integration. Finally conclusions drawn from the paper are presented and an outlook on future research work is given.
Journal Article
QGIS Quick Start Guide
Step through loading GIS data, creating GIS data, styling GIS and making maps with QGIS following a simple narrative that will allow you to build confidence as you progress. Key Features * Work with GIS data, a step by step guide from creation to making a map * Perform geoprocessing tasks and automate them using model builder * Explore a range of features in QGIS 3.4, discover the power behind open source desktop GIS Book Description QGIS is a user friendly, open source geographic information system (GIS). The popularity of open source GIS and QGIS, in particular, has been growing rapidly over the last few years. This book is designed to help beginners learn about all the tools required to use QGIS 3.4. This book will provide you with clear, step-by-step instructions to help you apply your GIS knowledge to QGIS. You begin with an overview of QGIS 3.4 and its installation. You will learn how to load existing spatial data and create vector data from scratch. You will then be creating styles and labels for maps. The final two chapters demonstrate the Processing toolbox and include a brief investigation on how to extend QGIS. Throughout this book, we will be using the GeoPackage format, and we will also discuss how QGIS can support many different types of data. Finally, you will learn where to get help and how to become engaged with the GIS community. What you will learn * Use existing data to interact with the canvas via zoom/pan/selection * Create vector data and a GeoPackage and build a simple project around it * Style data, both vector and raster data, using the Layer Styling Panel * Design, label, save, and export maps using the data you have created * Analyze spatial queries using the Processing toolbox * Expand QGIS with the help of plugins, model builder, and the command line Who this book is for If you know the basic functions and processes of GIS, and want to learn to use QGIS to analyze geospatial data and create rich mapping applications, then this is the book for you.
eBook
QGIS in remote sensing set. Volume 1, QGIS and generic tools
These four volumes present innovative thematic applications implemented using the open source software QGIS. These are applications that use remote sensing over continental surfaces. The volumes detail applications of remote sensing over continental surfaces, with a first one discussing applications for agriculture. A second one presents applications for forest, a third presents applications for the continental hydrology, and finally the last volume details applications for environment and risk issues.
BOOK
Benchmarking geospatial database on Kubernetes cluster
Kubernetes is an open-source container orchestration system for automating container application operations and has been considered to deploy various kinds of container workloads. Traditional geo-databases face frequent scalability issues while dealing with dense and complex spatial data. Despite plenty of research work in the comparison of relational and NoSQL databases in handling geospatial data, there is a shortage of existing knowledge about the performance of geo-database in a clustered environment like Kubernetes. This paper presents benchmarking of PostgreSQL/PostGIS geospatial databases operating on a clustered environment against non-clustered environments. The benchmarking process considers the average execution times of geospatial structured query language (SQL) queries on multiple hardware configurations to compare the environments based on handling computationally expensive queries involving SQL operations and PostGIS functions. The geospatial queries operate on data imported from OpenStreetMap into PostgreSQL/PostGIS. The clustered environment powered by Kubernetes demonstrated promising improvements in the average execution times of computationally expensive geospatial SQL queries on all considered hardware configurations compared to their average execution times in non-clustered environments.
Journal Article
Geospatial Data Science
This introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site: https://ai.di.uoa.gr/geospatial-data-science-book/index.html where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the Knowledge Technologies course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.
eBook