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PD-29 - Programming of Mobile GIS Applications

Mobile technology has significantly changed how we communicate and interact with the outside world. With the increasing use of mobile devices and advancement of information communication information (ICT) technologies, mobile GIS emerged to provide real-time data collection and update, and made GIS easier and convenient to access. This entry introduces the concept, types, and general architecture of mobile GIS, key technologies used for mobile GIS development, and examples of mobile GIS applications.

PD-32 - JavaScript for GIS

JavaScript (which has no connection to the Java computer language) is a popular high-level programming languages used to develop user interfaces in web pages. The principle goal of using JavaScript for programming web and mobile GIS applications is to build front-end applications that make use of spatial data and GIS principles, and in many cases, have embedded, interactive maps. It is considered much easier to program than Java or C languages for adding automation, animation, and interactivity into web pages and applications. JavaScript uses the leading browsers as runtime environments (RTE) and thus benefits from rapid and continuously evolving browser support for all web and mobile applications.

PD-28 - Visual Programming for GIS Applications

Visual programming languages (VPLs) in GIS applications are used to design the automatic processing of spatial data in an easy visual form. The resulted visual workflow is useful when the same processing steps need to be repeated on different spatial data (e.g. other areas, another period). In the case of visual programming languages, simple graphical symbols represent spatial operations implemented in GIS software (tools, geoalgorithms). Users can create a sequence of operation in a simple visual form, like a chain of graphical symbols. Visual programs can be stored and reused. The graphical form is useful to non-programmers who are not familiar with a textual programming language, as is the case with many professionals such as urban planners, facility managers, ecologists and other users of GIS. VPLs are implemented not only in GIS applications but also in remote sensing (RS) applications. Sometimes both types of applications are bundled together in one geospatial application that offers geoalgorithms in a shared VPL environment. Visual programming languages are an integral part of software engineering (SE). Data flow and workflow diagrams are one of the oldest graphical representations in informatics.

PD-33 - GDAL/OGR and Geospatial Data IO Libraries

Manipulating (e.g., reading, writing, and processing) geospatial data, the first step in geospatial analysis tasks, is a complicated step, especially given the diverse types and formats of geospatial data combined with diverse spatial reference systems. Geospatial data Input/Output (IO) libraries help facilitate this step by handling some technical details of the IO process. GDAL/OGR is the most widely-used, broadly-supported, and constantly-updated free library among existing geospatial data IO libraries. GDAL/OGR provides a single raster abstract data model and a single vector abstract data model for processing and analyzing raster and vector geospatial data, respectively, and it supports most, if not all, commonly-used geospatial data formats. GDAL/OGR can also perform both cartographic projections on large scales and coordinate transformation for most of the spatial reference systems used in practice. This entry provides an overview of GDAL/OGR, including why we need such a geospatial data IO library and how it can be applied to various formats of geospatial data to support geospatial analysis tasks. Alternative geospatial data IO libraries are also introduced briefly. Future directions of development for GDAL/OGR and other geospatial data IO libraries in the age of big data and cloud computing are discussed as an epilogue to this entry.

PD-31 - PySAL and Spatial Statistics Libraries

As spatial statistics are essential to the geographical inquiry, accessible and flexible software offering relevant functionalities is highly desired. Python Spatial Analysis Library (PySAL) represents an endeavor towards this end. It is an open-source python library and ecosystem hosting a wide array of spatial statistical and visualization methods. Since its first public release in 2010, PySAL has been applied to address various research questions, used as teaching materials for pedagogical purposes in regular classes and conference workshops serving a wide audience, and integrated into general GIS software such as ArcGIS and QGIS. This entry first gives an overview of the history and new development with PySAL. This is followed by a discussion of PySAL’s new hierarchical structure, and two different modes of accessing PySAL’s functionalities to perform various spatial statistical tasks, including exploratory spatial data analysis, spatial regression, and geovisualization. Next, a discussion is provided on how to find and utilize useful materials for studying and using spatial statistical functions from PySAL and how to get involved with the PySAL community as a user and prospective developer. The entry ends with a brief discussion of future development with PySAL.

PD-05 - Design, Development, Testing, and Deployment of GIS Applications

A systems development life cycle (SDLC) denes and guides the activities and milestones in the design, development, testing, and de ployment of software applications & information systems. Various choices of SDLC are available for different types of software applications & information systems and compositions of development teams and stakeholders. While the choice of an SDLC for building geographic information system (GIS) applications is similar to that of other types of software applications, critical decisions in each phase of the GIS development life cycle (GiSDLC) should take into account essential questions concern ing the storage, access, and analysis of (geo)spatial data for the target application. This article aims to introduce various considerations in the GiSDLC, from the perspectives of handling (geo)spatial data. The article rst introduces several (geo)spatial processes and types as well as various modalities of GIS applications. Then the article gives a brief introduction to an SDLC, including explaining the role of (geo)spatial data in the SDLC. Finally, the article uses two existing real-world applications as an example to highlight critical considerations in the GiSDLC.