scholarly journals Remaining gaps in open source software for Big Spatial Data

2018 ◽  
Author(s):  
Luís Moreira de Sousa
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Daily Basis ◽  
Earth Observation ◽  
Data Sets ◽  
Equal Area ◽  
Cartesian System ◽  
Gis Software ◽  
Good Number

The volume and coverage of spatial data has increased dramatically in recent years, with Earth observation programmes producing dozens of GB of data on a daily basis. The term Big Spatial Data is now applied to data sets that impose real challenges to researchers and practitioners alike. The difficulties are partly related to a lack of tools supporting appropriate Coordinate Reference Systems (CRS). As rule, these data are provided in highly irregular geodesic grids, defined along equal intervals of latitude and longitude. Compounding the problem, users of such data end up taking geodesic coordinates in these grids as a Cartesian system, implicitly applying Marinus of Tyre's projection. A first approach towards the compactness of global geo-spatial data is to work in a Cartesian system produced by an equal-area projection. There are a good number to choose from, but those commonly supported by GIS software invariably relate to the sinusoidal or pseudo-cylindrical families, that impose important distortions of shape and distance. The land masses of Antarctica, Alaska, Canada, Greenland and Russia are particularly distorted with such projections. A more effective approach is to store and work with data in modern cartographic projections, in particular those defined with the Platonic and Archimedean solids. In spite of various attempts at open source software supporting these projections, in practice they remain today largely out of reach to GIS practitioners. This communication reviews persisting difficulties in working with worldwide big spatial data, current strategies to address such difficulties, the compromises they impose and the remaining gaps in open source software.

scholarly journals Remaining gaps in open source software for Big Spatial Data

2018 ◽  
Author(s):  
Luís Moreira de Sousa
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Daily Basis ◽  
Earth Observation ◽  
Data Sets ◽  
Equal Area ◽  
Cartesian System ◽  
Gis Software ◽  
Good Number

The volume and coverage of spatial data has increased dramatically in recent years, with Earth observation programmes producing dozens of GB of data on a daily basis. The term Big Spatial Data is now applied to data sets that impose real challenges to researchers and practitioners alike. As rule, these data are provided in highly irregular geodesic grids, defined along equal intervals of latitude and longitude, a vastly inefficient and burdensome topology. Compounding the problem, users of such data end up taking geodesic coordinates in these grids as a Cartesian system, implicitly applying Marinus of Tyre's projection. A first approach towards the compactness of global geo-spatial data is to work in a Cartesian system produced by an equal-area projection. There are a good number to choose from, but those supported by common GIS software invariably relate to the sinusoidal or pseudo-cylindrical families, that impose important distortions of shape and distance. The land masses of Antarctica, Alaska, Canada, Greenland and Russia are particularly distorted with such projections. A more effective approach is to store and work with data in modern cartographic projections, in particular those defined with the Platonic and Archimedean solids. In spite of various attempts at open source software supporting these projections, in practice they remain today largely out of reach to GIS practitioners. This communication reviews persisting difficulties in working with global big spatial data, current strategies to address such difficulties, the compromises they impose and the remaining gaps in open source software.

scholarly journals Remaining gaps in open source software for Big Spatial Data

2018 ◽  
Author(s):  
Luís Moreira de Sousa
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Daily Basis ◽  
Earth Observation ◽  
Data Sets ◽  
Equal Area ◽  
Cartesian System ◽  
Gis Software ◽  
Good Number

The volume and coverage of spatial data has increased dramatically in recent years, with Earth observation programmes producing dozens of GB of data on a daily basis. The term Big Spatial Data is now applied to data sets that impose real challenges to researchers and practitioners alike. As rule, these data are provided in highly irregular geodesic grids, defined along equal intervals of latitude and longitude, a vastly inefficient and burdensome topology. Compounding the problem, users of such data end up taking geodesic coordinates in these grids as a Cartesian system, implicitly applying Marinus of Tyre's projection. A first approach towards the compactness of global geo-spatial data is to work in a Cartesian system produced by an equal-area projection. There are a good number to choose from, but those supported by common GIS software invariably relate to the sinusoidal or pseudo-cylindrical families, that impose important distortions of shape and distance. The land masses of Antarctica, Alaska, Canada, Greenland and Russia are particularly distorted with such projections. A more effective approach is to store and work with data in modern cartographic projections, in particular those defined with the Platonic and Archimedean solids. In spite of various attempts at open source software supporting these projections, in practice they remain today largely out of reach to GIS practitioners. This communication reviews persisting difficulties in working with global big spatial data, current strategies to address such difficulties, the compromises they impose and the remaining gaps in open source software.

A Departmental Open Source Pipeline GIS

2006 ◽  
Author(s):  
Geoffrey R. Kneller
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Setup Time ◽  
Geographic Information ◽  
Cost Estimating ◽  
Web Based ◽  
Gis Software

Geographic Information System (GIS) software has evolved to the point where it is extremely valuable to the planning, construction and operation of pipelines across a range of industries. Recently, GIS software of high quality has become freely available for use and modification under open source licensing schemes. This paper evaluates the utility of a geographic information system prepared using open source software for shared departmental use. Analysis includes areas such as functionality of the software, setup time, and total cost of ownership. The departmental focus is at a level concerned with pipeline planning and cost estimating. The full GIS package used for the analysis consists of a database, spatial data management software, and a web server providing web-based access to geomatic data suitable for a pipeline construction department. The utility of application programming interfaces provided through the GIS with open source software development tools is analysed in the form of a what-if economic comparison tool for pipeline route selection. The ability of the GIS to integrate data from other departmental systems is also examined. Final conclusions serve to aid pipeline GIS teams in determining if open source solutions are ready for widespread use.

scholarly journals Integration of Open Source GIS Software for Improving Decision Making in Small and Medium Companies

2018 ◽  
pp. 1-6
Author(s):  
Ali Hameed Yassir
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Software Components ◽  
Open Source Gis ◽  
Gis Software ◽  
And Training ◽  
Support Decision Making

In this paper, a prototype is proposed of integrating various features and functionalities of different open source GIS software to improve decision-making in small and medium companies. The paper shows possibilities of integrating various open source GIS software to support decision making. Open source software features is combined with the functionalities of GIS such as processing using Quantum GIS, storing and analyzing of spatial data to produce results using PostgreSQL, Providing and sharing Geo-data over the network locally or over the globe using Geoserver, The prototype is based on the three basics features low /free cost of using GIS open source software, simplicity and usability, multiplatform supporting. The integration of open source software is appropriate and successful for the use of companies in the field of GIS, this initiative represents a suitable business solutions that do not consume a lot of money and training to develop the skills of the technicians in this field, therefore, this will open the door for other companies to follow this trend. This prototype provides an opportunity for open source software components to process and store data in databases or shares the results over different networks.  

scholarly journals Comparison of FOSS4G Supported Equal-Area Projections Using Discrete Distortion Indicatrices

2019 ◽  
Vol 8 (8) ◽  
pp. 351 ◽  
Author(s):  
Luís Moreira de Sousa ◽  
Laura Poggio ◽  
Bas Kempen
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Superior Performance ◽  
Equal Area ◽  
Trade Offs ◽  
Visual Expression

This study compares the performance of five popular equal-area projections supported by Free and Open Source Software for Geo-spatial (FOSS4G)—Sinusoidal, Mollweide, Hammer, Eckert IV and Homolosine. A set of 21,872 discrete distortion vindicatrices were positioned on the ellipsoid surface, centred on the cells of a Snyder icosahedral equal-area grid. These indicatrices were projected on the plane and the resulting angular and distance distortions computed, all using FOSS4G. The Homolosine is the only projection that manages to minimise angular and distance distortions simultaneously. It yields the lowest distortions among this set of projections and clearly outclasses when only land masses are considered. These results also indicate the Sinusoidal and Hammer projections to be largely outdated, imposing too large distortions to be useful. In contrast, the Mollweide and Eckert IV projections present trade-offs between visual expression and accuracy that are worth considering. However, for the purposes of storing and analysing big spatial data with FOSS4G the superior performance of the Homolosine projection makes its choice difficult to avoid.

Development of Assessment Criteria for Various Open Sources GIS Software Packages

2021 ◽  
pp. 398-412
Author(s):  
Shahriar Shams
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Assessment Criteria ◽  
Significant Development ◽  
Analysis And Design ◽  
Advantages And Disadvantages ◽  
Software Packages ◽  
Open Source Gis ◽  
Gis Software

There has been a significant development in the area of free and open source geospatial software. Research has flourished over the decades from vendor-dependent software to open source software where researchers are paying increasing attention to maximize the value of their data. It is often a difficult task to choose particular open source GIS (OGIS) software among a number of emerging OGIS software. It is important to characterise the projects according to some unified criteria. Each software has certain advantages and disadvantages and it is always time consuming to identify exactly which software to select for a specific purpose. This chapter focuses on the assessment criteria enabling developers, researchers, and GIS users to select suitable OGIS software to meet their requirements for analysis and design of geospatial application in multidisciplinary fields. This chapter highlights the importance of assessment criteria, followed by an explanation of each criteria and their significance with examples from existing OGIS software.

scholarly journals HARVESTING, INTEGRATING AND DISTRIBUTING LARGE OPEN GEOSPATIAL DATASETS USING FREE AND OPEN-SOURCE SOFTWARE

2016 ◽  
Vol XLI-B7 ◽  
pp. 939-940
Author(s):  
Ricardo Oliveira ◽  
Rafael Moreno
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Information ◽  
Open Data ◽  
Federal State ◽  
Data Sets ◽  
Data Set ◽  
Geospatial Datasets ◽  
State And Local ◽  
The City

Federal, State and Local government agencies in the USA are investing heavily on the dissemination of Open Data sets produced by each of them. The main driver behind this thrust is to increase agencies’ transparency and accountability, as well as to improve citizens’ awareness. However, not all Open Data sets are easy to access and integrate with other Open Data sets available even from the same agency. The City and County of Denver Open Data Portal distributes several types of geospatial datasets, one of them is the city parcels information containing 224,256 records. Although this data layer contains many pieces of information it is incomplete for some custom purposes. Open-Source Software were used to first collect data from diverse City of Denver Open Data sets, then upload them to a repository in the Cloud where they were processed using a PostgreSQL installation on the Cloud and Python scripts. Our method was able to extract non-spatial information from a ‘not-ready-to-download’ source that could then be combined with the initial data set to enhance its potential use.

scholarly journals HARVESTING, INTEGRATING AND DISTRIBUTING LARGE OPEN GEOSPATIAL DATASETS USING FREE AND OPEN-SOURCE SOFTWARE

2016 ◽  
Vol XLI-B7 ◽  
pp. 939-940 ◽  
Author(s):  
Ricardo Oliveira ◽  
Rafael Moreno
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Information ◽  
Open Data ◽  
Federal State ◽  
Data Sets ◽  
Data Set ◽  
Geospatial Datasets ◽  
State And Local ◽  
The City

Federal, State and Local government agencies in the USA are investing heavily on the dissemination of Open Data sets produced by each of them. The main driver behind this thrust is to increase agencies’ transparency and accountability, as well as to improve citizens’ awareness. However, not all Open Data sets are easy to access and integrate with other Open Data sets available even from the same agency. The City and County of Denver Open Data Portal distributes several types of geospatial datasets, one of them is the city parcels information containing 224,256 records. Although this data layer contains many pieces of information it is incomplete for some custom purposes. Open-Source Software were used to first collect data from diverse City of Denver Open Data sets, then upload them to a repository in the Cloud where they were processed using a PostgreSQL installation on the Cloud and Python scripts. Our method was able to extract non-spatial information from a ‘not-ready-to-download’ source that could then be combined with the initial data set to enhance its potential use.

scholarly journals Comparative analysis of QGIS plugins for Web Maps creation

La Granja ◽  
2021 ◽  
Vol 34 (2) ◽  
pp. 8-26
Author(s):  
Lia Duarte ◽  
Catarina Queirós ◽  
Ana Cláudia Teodoro
Keyword(s):  
Information System ◽  
Comparative Analysis ◽  
Geographic Information System ◽  
Open Source ◽  
Open Source Software ◽  
Geographic Information ◽  
Geospatial Data ◽  
Advantages And Disadvantages ◽  
Gis Software

QGIS is a free and open-source software that allows viewing, editing, and analyzing georeferenced data. It is a Geographic Information System (GIS) software composed by tools that allow to manipulate geographic information and consequently to create maps which help to get a better understanding and organization of geospatial data. Unfortunately, maps created directly in the GIS desktop software are not automatically transferred to a website. This research aimed to compare publishing capabilities in different QGIS plugins to create Web Maps. This study analyzes four QGIS plugins (QGIS2Web, QGIS Cloud, GIS Cloud Publisher and Mappia Publisher), performing a comparison between them, considering their advantages and disadvantages, the free and subscription plans, the tools offered by each plugin and other generic aspects. The four plugins were tested in a specific case study to automatically obtain different Web Maps. This study could help users to choose the most adequate tools to publish Web Maps under QGIS software.

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