Full feature data model for spatial information network integration

2006 ◽  
Vol 13 (5) ◽  
pp. 584-589
Author(s):  
Ji-qiu Deng ◽  
Guang-shu Bao
2020 ◽  
Vol 9 (9) ◽  
pp. 499
Author(s):  
Melanie Brauchler ◽  
Johannes Stoffels

Up-to-date information about the type and spatial distribution of forests is an essential element in both sustainable forest management and environmental monitoring and modelling. The OpenStreetMap (OSM) database contains vast amounts of spatial information on natural features, including forests (landuse=forest). The OSM data model includes describing tags for its contents, i.e., leaf type for forest areas (i.e., leaf_type=broadleaved). Although the leaf type tag is common, the vast majority of forest areas are tagged with the leaf type mixed, amounting to a total area of 87% of landuse=forests from the OSM database. These areas comprise an important information source to derive and update forest type maps. In order to leverage this information content, a methodology for stratification of leaf types inside these areas has been developed using image segmentation on aerial imagery and subsequent classification of leaf types. The presented methodology achieves an overall classification accuracy of 85% for the leaf types needleleaved and broadleaved in the selected forest areas. The resulting stratification demonstrates that through approaches, such as that presented, the derivation of forest type maps from OSM would be feasible with an extended and improved methodology. It also suggests an improved methodology might be able to provide updates of leaf type to the OSM database with contributor participation.


2019 ◽  
Vol 11 (17) ◽  
pp. 1957 ◽  
Author(s):  
Jingya Yan ◽  
Siow Jaw ◽  
Kean Soon ◽  
Andreas Wieser ◽  
Gerhard Schrotter

With the pressure of the increasing density of urban areas, some public infrastructures are moving to the underground to free up space above, such as utility lines, rail lines and roads. In the big data era, the three-dimensional (3D) data can be beneficial to understand the complex urban area. Comparing to spatial data and information of the above ground, we lack the precise and detailed information about underground infrastructures, such as the spatial information of underground infrastructure, the ownership of underground objects and the interdependence of infrastructures in the above and below ground. How can we map reliable 3D underground utility networks and use them in the land administration? First, to explain the importance of this work and find a possible solution, this paper observes the current issues of the existing underground utility database in Singapore. A framework for utility data governance is proposed to manage the work process from the underground utility data capture to data usage. This is the backbone to support the coordination of different roles in the utility data governance and usage. Then, an initial design of the 3D underground utility data model is introduced to describe the 3D geometric and spatial information about underground utility data and connect it to the cadastral parcel for land administration. In the case study, the newly collected data from mobile Ground Penetrating Radar is integrated with the existing utility data for 3D modelling. It is expected to explore the integration of new collected 3D data, the existing 2D data and cadastral information for land administration of underground utilities.


1981 ◽  
Vol 2 (2) ◽  
pp. 148-160 ◽  
Author(s):  
Milford B. Green ◽  
R. Keith Semple

2014 ◽  
Vol 7 (5) ◽  
pp. 1933-1943 ◽  
Author(s):  
W. Chang ◽  
P. J. Applegate ◽  
M. Haran ◽  
K. Keller

Abstract. Computer models of ice sheet behavior are important tools for projecting future sea level rise. The simulated modern ice sheets generated by these models differ markedly as input parameters are varied. To ensure accurate ice sheet mass loss projections, these parameters must be constrained using observational data. Which model parameter combinations make sense, given observations? Our method assigns probabilities to parameter combinations based on how well the model reproduces the Greenland Ice Sheet profile. We improve on the previous state of the art by accounting for spatial information and by carefully sampling the full range of realistic parameter combinations, using statistically rigorous methods. Specifically, we estimate the joint posterior probability density function of model parameters using Gaussian process-based emulation and calibration. This method is an important step toward calibrated probabilistic projections of ice sheet contributions to sea level rise, in that it uses data–model fusion to learn about parameter values. This information can, in turn, be used to make projections while taking into account various sources of uncertainty, including parametric uncertainty, data–model discrepancy, and spatial correlation in the error structure. We demonstrate the utility of our method using a perfect model experiment, which shows that many different parameter combinations can generate similar modern ice sheet profiles. This result suggests that the large divergence of projections from different ice sheet models is partly due to parametric uncertainty. Moreover, our method enables insight into ice sheet processes represented by parameter interactions in the model.


Author(s):  
Arie Wisianto ◽  
Hidayatus Saniya ◽  
Oki Gumilar

Development of web based GIS application often requires high cost on base map datasets and software licenses. Web based GIS Pipeline Data Management Application can be developed using the benefit of Google Maps datasets combined with available local spatial datasets resulting comprehensive spatial information. Sharp Map is an easy-to-use mapping library for use in web and desktop applications. It provides access and enables spatial querying to many types of GIS data. The engine is written in C# and based on the .Net 2.0 frameworks and provides advantages for integration with Pipeline Data Model such as PODS using .NET technology. Sharp Map enables development of WMS and web services for serving pipeline data management information on internet/intranet web based application. Open Layers is use to integrate pipelines data model and Google Maps dataset on single map display with user friendly and dynamic user interfaces. The use of Sharp Map and Open Layers creating powerful Pipeline Data Management web based GIS application by combining specific information from pipelines data model and comprehensive Google Maps satellites datasets without publishing private information from local datasets. The combination on Sharp Map, Open Layers, Google Maps datasets, and .NET technology resulting a low cost and powerful Pipeline Data Management web based GIS solution. Impact zone of the event then we can calculate their consequences and finally we can figure their risk.


2012 ◽  
Vol 268-270 ◽  
pp. 1688-1691
Author(s):  
Xiao Guo Ye ◽  
Ru Chuan Wang

Aircraft communication and satellite link handoff issues in spatial information network are very important and are focused in this paper. The simulation modules of satellite network nodes and links in network simulator version 2(NS-2) are analyzed in details in this paper. A method of extending NS-2 kernel module is proposed based on analysis of satellite network simulation principle and approach. As an example, the aircraft communication simulation module is designed and implemented. Simulation results show that flight of aircraft has effect on the link handoff characteristic, and show that the proposed extension method is feasible.


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