Search Page

Showing 1 - 4 of 4
PD-37 - Open Source Software Development

Open source geospatial software is now ubiquitous – it is used and supported across industries, in government agencies, as well as research institutions and academia. This entry describes general principles of open source software development and provides an overview of the development platforms and tools. Specific focus is on the Open Source Geospatial Foundation’s software stack, its development principles, practices, and initiatives. Several additional major open source software systems with geospatial support are also briefly discussed with examples of open source applications developed by integrating multiple libraries and packages.

CP-27 - GIS and Computational Notebooks

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows—and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user’s typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the “glue” that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

PD-10 - Natural Language Processing in GIScience Applications

Natural Language Processing (NLP) has experienced explosive growth in recent years. While the field has been around for decades, recent advances in NLP techniques as well as advanced computational resources have re-engaged academics, industry, and the general public. The field of Geographic Information Science has played a small but important role in the growth of this domain. Combining NLP techniques with existing geographic methodologies and knowledge has contributed substantially to many geospatial applications currently in use today. In this entry, we provide an overview of current application areas for natural language processing in GIScience. We provide some examples and discuss some of the challenges in this area.

CP-08 - Spatial Cloud Computing

The scientific and engineering advancements in the 21st century pose grand computing challenges in managing big data, using complex algorithms to extract information and knowledge from big data, and simulating complex and dynamic physical and social phenomena. Cloud computing emerged as new computing model with the potential to address these computing challenges. This entry first introduces the concept, features and service models of cloud computing. Next, the ideas of generalized architecture and service models of spatial cloud computing are then elaborated to identify the characteristics, components, development and applications of spatial cloud computing for geospatial sciences.