Scalable Geo Web Techniques using Spatial Data Mining for Air Pollution

The sharing and interoperability of geospatial data are important issues for spatial information grid (SIG). Based on an existing SIG platform, we tentatively propose a three-level overview SIG layout. Within this new architecture, some grid service entities (GSEs) complying with Open GIS Consortium (OGC) interoperability specifications, such as Web Map Service (WMS), Web Feature Service and Web Coverage Service, are implemented to solve the challenge mentioned above. We focus on explaining the characteristics of the new architecture and on implementation of the OGC GSE utilizing MapServer. A WMS GSE application example with satisfactory results is also presented.

Interoperability, interactivity and 3D visualization are three of the most important challenges related to Geographical Information Systems. In the last few years, research on interoperability has evolved from simple exchange of spatial data files, through the establishment of standardized spatial data repositories, to the first initiatives allowing management of semantic aspects of data. Interoperability has been mainly hampered by the need to agree on standards, and to develop appropriate tools and methods. The Open Geospatial Consortium (OGC) has proposed a number of standards with the intention of promoting interoperability through the use of open services such as Web Mapping Service (WMS), Web Processing Service (WPS), Web Feature Service (WFS) and Web Coverage Service (WCS). However, there are a number of open issues regarding interactivity, 3D data visualization, fault tolerance, scalability, server-independent implementation, delayed-time transactions, to name but a few, that clearly reflect the need for further study and discussion. This paper presents a service-oriented architecture in the context of interoperable Web 3D GIS applications, designed to support features such as manipulation, processing and visual analysis of geographical information.

In order to benefit as much as possible from geographical information, users have expressed a strong need to integrate their data with other data. The need to integrate historical data is particularly expressed as it often contains invaluable information which is often unmapped or not represented in current maps or data. Unfortunately, easily accessible data integration treatments are not yet available for users. This paper aims to introduce a solution to solve this problem by explaining the building of a data integration web platform, called SEREDONA, a French acronym for “SErvice de REcalage de DONnees Anciennes” which can be translated as follows: “Web service platform for the adjustment of historical data”. The approach to build this platform, its functionalities and its architecture are fully described. In particular the architecture is based on OGC Web Services (Web Map Service, Web Feature Service and Web Processing Service), Open Source components and the principles of a service oriented architecture. Thus, it allows using the developed components in a more global spatial data infrastructure or separately in other contexts.

• A data service system for the selected SMAP data and its derivative data products over CONUS is developed. • All map and geoprocessing services are implemented via the OGC standard interface. • The data service system is interoperable with web and desktop clients. • Monitoring and analyzing U.S. cropland soil moisture conditions are significantly simplified. Soil moisture is an essential parameter to understand crop conditions throughout the growing season. Collecting soil moisture data by field observation is labor-intensive, especially when attempting to obtain Conterminous United States (CONUS) geographic coverage. In addition, using soil moisture for assessing current and future crop conditions is best realized by combining soil moisture estimates with concurrent observations of crop conditions. However, until recently, this capability has not been available to the public. In this paper, we present an interoperable data service application system, the Crop Condition and Soil Moisture Analytics (Crop-CASMA) system, that facilitates the retrieval, analysis, visualization, and sharing of soil moisture data for the CONUS. This system delivers a variety of satellite remote sensing based data products that are derived from Soil Moisture Active Passive (SMAP) Level-4 data and SMAP Thermal Hydraulic disaggregation of Soil Moisture (THySM) data, as well as vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations. To make services interoperable and reusable, all data products are disseminated via Open Geospatial Consortium (OGC) Web Map Service (WMS) and Web Coverage Service (WCS) interface standards. Additionally, a suite of geoprocessing operations, such as geospatial statistics, time-series profile generation, PDF map production, and image composition, has been implemented in the OGC Web Processing Service (WPS) interface standard. The implementation shows the proposed web service system can significantly simplify the mapping and quantitative analysis of soil moisture and crop condition over U.S. cropland. In addition, it is interoperable with GIS software and has been successfully integrated with web-based applications.

Interoperability is the main challenge on the way to efficiently find and access spatial data on the web. Significant contributions regarding interoperability have been made by the Open Geospatial Consortium (OGC), where web service standards to publish and download spatial data have been established. The OGCs GeoSPARQL specification targets spatial data on the Web as Linked Open Data (LOD) by providing a comprehensive vocabulary for annotation and querying. While OGC web service standards are widely implemented in Geographic Information Systems (GIS) and offer a seamless service infrastructure, the LOD approach offers structured techniques to interlink and semantically describe spatial information. It is currently not possible to use LOD as a data source for OGC web services. In this chapter we make a suggestion for technically linking OGC web services and LOD as a data source, and we explore and discuss its benefits. We describe and test an adapter that enables access to geographic LOD datasets from within OGC Web Feature Service (WFS), enabling most current GIS to access the Web of Data. We discuss performance tests by comparing the proposed adapter to a reference WFS implementation.

OGC (open geospatial consortium) has developed the implementation specifications especially WMS (Web map service) and WFS (Web feature service) which facilitate GIS data dissemination including the map image distribution for visualization and online GIS data exchange. WPS (Web processing service) is also one of the OGC specifications for processing service which allow GIS functions available on the Internet. This paper reports the implementation and development of WPS which enables user to perform geospatial processing with data requested from another WFS site. Spatial databases are used as spatial engine to carry out the geoprocessing function. Oracle spatial, PostGIS and MySQL are the spatial databases which are tested in this research. WPS request form is adapted by applying SQL statement to be used for calling function from spatial database, and also to simplify and shorten the request form. The result clearly shows the success of implementation of this concept by testing the implemented WPS with available external WFS to get new information through the spatial engine available from the desired databases.

Denmark’s Depth Model (DDM) is a Digital Bathymetric Model based on hundreds of bathymetric survey datasets and historical sources within the Danish Exclusive Economic Zone. The DDM represents the first publicly released model covering the Danish waters with a grid resolution of 50 m. When modern datasets are not available for a given area, historical sources are used, or, as the last resort, interpolation is applied. The model is generated by averaging depths values from validated sources, thus, not targeted for safety of navigation. The model is available by download from the Danish Geodata Agency website. DDM is also made available by means of Open Geospatial Consortium web services (i.e., Web Map Service). The original datasets—not distributed with the model—are described in the auxiliary layers to provide information about the bathymetric sources used during the compilation.

International studies of expertise have shown that the difficulty of data access is one of the major hindrances that brakes any effort to conduct studies on groundwater. This research paper is an attempt to address this problematic through developing a technical framework to implement a Spatial Data Infrastructure (SDI) with a view to improving the status of access to data related to groundwater in Morocco, and achieving their interoperability. This prototype is primarily based on international standards (OGC & ISO) such as Web Map Service (WMS), Web Feature Service (WFS), Catalog Web Service (CSW) and Sensor Observation Service (SOS) accompanied by the use of associated specifications such as Geography Markup Language (GML) and Filter Encoding (FE). This platform is considered both as a tool for sharing updated data collected from numerous and divers source providers, and as a tool of web-based GIS for groundwater management, which constitutes the basis for decision making.

Open-source mapping and services for Web-based land-cover validation

This article intends to provide an advanced traveller information system based on open geospatial consortium (OGC) standards to perform a fuzzy bi-criteria shortest-path analysis for a multimodal transportation network. To do so, chaining of OGC web services is used to resolve interoperability problems among distributed and heterogeneous resource data. First, a web feature service is assigned to each mode of transportation to gather and convert the data to a standard format, such as geographic markup language. Then, the obtained data are combined to model and construct the multimodal transportation network. Subsequently, a web processing service is designed for performing a fuzzy bi-criteria shortest-path analysis in the multimodal transportation network. Finally, the best routes between the origin–destination pair are presented on a digital map by using a web map service. In the study, among various route-selection criteria, travel time and comfort are considered. To model these criteria, the fuzzy set theory is utilized. By using fuzzy decision tables and a Tsukamoto fuzzy inference system, the desirability of the routes is calculated. The results of comparison among the four travel routes between various origin–destination pairs indicate that the proposed system could be an applicable tool for providing pre-trip information and assisting multimodal travellers under uncertain conditions.

Many of the standards used to build spatial data infrastructure (SDI), such as Web Map Service (WMS) or Web Feature Service (WFS), have become outdated. They do not follow current web technology development and do not fully exploit its capabilities. Spatial data often remains available only through application programming interfaces (APIs), reflecting the persistence of organizational silos. The potential of the web for discovering knowledge hidden in data and discoverable through integration and fusion remains very difficult. This article presents a strategy to take advantage of these newer semantic web technologies for SDI. We describe the implementation of a public registry in the age of Web 3.0. Our goal is to convert existing geographic information systems (GIS) data into explicit knowledge that can be easily used for a variety of purposes. This turns SDI into a framework to utilize the many advantages of the web. In this paper we present the working prototype system developed for the province of Mazowieckie in Poland and describes the underlying concepts. Further development of this approach comes from using linked data (LD) with expert systems to support analysis functions and tasks.

Successful information integration and sharing data across disparate systems and designs are required for fast access to and interpretation of many types of geospatial information. Spatial data are highly heterogeneous - not only they differ from data representation and storage methods, but they also differ in the way of querying the data. Finding and accessing spatial data in an environment like this is a crucial task. Enterprise geographic information system (E-GIS) is an organization-wide approach to GIS implementation, operation, and management. The main focus of the paper is to integrate diverse spatial data repositories for geographic applications using service-based methodology. We have adopted service-oriented architecture (SOA) for the discovery and retrieval of geospatial data. The architecture uses a central ontology as metadata information, which acts as service broker. Ontology-based discovery and retrieval of geographic data solves the problem of semantic heterogeneity, the major bottleneck for spatial interoperability. The implementation is in compliant with the Web Map Service (WMS) and Web Feature Service (WFS), the web service standards proposed by OGC. The need for loosely coupled service-based access of data in the spatial domain has been exploited. A query processing mechanism in distributed environment of spatial data sources has been discussed at the end. The proposed system has been implemented and fully tested.

Abstract. The continuous growth of remotely sensed data raises the need for efficient ways of accessing data archives. The classical model of accessing remote sensing (satellite) archives via distribution of large files is increasingly making way for a more dynamic and interactive data service. A challenge, though, is interoperability of such services, in particular when multi-dimensional data and advanced processing are involved. Individually crafted service interfaces typically do not allow substitution and combination of services. Open standards can provide a way forward if they are powerful enough to address both data and processing model. The OGC Web Coverage Service (WCS) is a modular service suite which provides high-level interface definitions for data access, subsetting, filtering, and processing of spatio-temporal raster data. WCS based service interfaces to data archives deliver data in their original semantics useful for further client-side processing, as opposed to the Web Map Service (WMS) (de la Beaujardière, 2006) which performs a pre-rendering into images only useful for display to humans. In this paper we present a case study where the OGC coverage data and service model defines the client/server interface for a climate data service. In particular, we show how flexible temporal analysis can be performed efficiently on massive spatio-temporal coverage objects. This service, which is operational on a several Terabyte data holding, has been established as part of the EarthServer initiative focusing on Big Data in the Earth and Planetary sciences.

Knowledge sharing and semantic interoperability is a significant research theme in Geographical Information Science (GIScience) because many researchers believe that semantic heterogeneity has been identified as the main obstacle for GIScience development. Interoperability issues can exist at three levels: syntactic, structural (also called systemic) and semantic. The former two, however, can be achieved by implementing international or domain standards proposed by several organizations, for example, Open Geospatial Consortium (OGC), World Wide Web Consortium (W3C) and the International Organization for Standardization/Technical Committee for Geographic information/Geomatics (ISO/TC 211). In this paper, we are concentrating on semantic interoperability, which is the sort of topic that halt conversations and cause people's eyes to glaze over, from two aspects: data/information/knowledge and operation/processing. We presented a service-centered architecture for semantic interoperability of geospatial data and processes. OGC standards like Web Feature Service (WFS) and Web Map Service (WMS) have been employed as normative interfaces for analyzing requests, division requests and delivering small requests. Ontology has been introduced to describe distributed resource including various data and geo-processing operations. The role of interoperability, especially from semantic perspective, has been distinguished at the first section in this paper. As a fundamental principal, the following section introduces semantic web, web service and other related works at this orientation. We present our service-based architecture in detail and its simple application at part three. Conclusion and further orientations have been illustrated at last section.

Pandemic diseases, such as avian influenza, can be deadly and disastrous although they do not happen frequently. Simulation is called for to control the spread of such diseases in preparing for the outbreaks. The spread of pandemic diseases can be affected by many factors, including virus vectors (such as migratory birds), climatic changes, and environment en route of virus vector migration. Many datasets and observations need to be assimilated into the simulation systems. The data and observations can be grouped into three types, i.e. satellite remotely sensed observations, in-situ data, and simulated model outputs. Satellite observations provide a timely large-scale coverage of environment changes and weather conditions. In situ data gives detailed ecological observations of birds at different stations and sites for simulation model construction and validation. Global climate models provide predictions of climate/weather changes, especially useful for filling the gaps when actual observations are not available. In this study, the Self-adaptive Earth Predictive System (SEPS), a general framework of Sensor Web service coordination and integration, was used as the basic framework to develop the observation and data assimilation services for the simulation of avian influenza. With the framework, these three types of data and observations are served through three different Web services. Remotely sensed observations are served through either Sensor Observation Service or Web Coverage Service. Climate models and simulation models are wrapped as Web Processing Services. In-situ bird observations are extracted online and populated as Web Feature Services. The integration of these services is managed using the central piece of SEPS, Coordinate and Event Notification Service (CENS). Internally, a Business Process Execution Language (BPEL) engine is used to actually execute the service integration.