Abstract
Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.
Highlights
Recent developments in remote sensing data, monitoring networks, and geographic information systems (GIS), like movements of open access and open data lead to the unprecedented growth of data [1–3]
The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML
Alternatives to commercial vendors are open-source suppliers, but existing open-source suppliers, such as GeoServer [40] and MapServer [41], provide fragmented solutions for geospatial data, services, and infrastructure. These open-source projects are independent of each other, GeoServer and MapServer will allow for clients to connect using a Web Map Service (WMS) protocol [42] from the OpenGeospatial Consortium (OGC) [34,43]
Summary
Recent developments in remote sensing data, monitoring networks, and geographic information systems (GIS), like movements of open access and open data lead to the unprecedented growth of data [1–3]. Sustainable development requires multidisciplinary approaches to process Big Data, including climate change, environmental health, water resources, land use and land cover, web technologies, digital earth, and so on [8–10]. This requires dealing with big data complexity, such as large scale, structured and unstructured data, online and real-time interaction and processing, cross formats, and so on [9–12]. This makes data management and processing very difficult using conventional methods in a reasonable time big data offers an environment rich information and opportunities to explore the data in more precise ways. It is still challenging how to process such big amount of data to extract useful information of economic and environmental sustainability because of complexity of the big data obtained from various sources and scales
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