The AJAX Application of Public Map Service Website

2010 ◽  
Author(s):  
Yang Shangying ◽  
Zhou Tao ◽  
Jiang Honggan
Keyword(s):  
Map Service

QARTA

2021 ◽  
Vol 14 (11) ◽  
pp. 2273-2282
Author(s):  
Mashaal Musleh ◽  
Sofiane Abbar ◽  
Rade Stanojevic ◽  
Mohamed Mokbel
Keyword(s):  
Machine Learning ◽  
Road Network ◽  
Contextual Information ◽  
Time Of Day ◽  
Food Delivery ◽  
Machine Learning Techniques ◽  
Navigation Systems ◽  
Query Result ◽  
Learning Techniques ◽  
Map Service

Maps services are ubiquitous in widely used applications including navigation systems, ride sharing, and items/food delivery. Though there are plenty of efforts to support such services through designing more efficient algorithms, we believe that efficiency is no longer a bottleneck to these services. Instead, it is the accuracy of the underlying road network and query result. This paper presents QARTA; an open-source full-fledged system for highly accurate and scalable map services. QARTA employs machine learning techniques to construct its own highly accurate map, not only in terms of map topology but more importantly, in terms of edge weights. QARTA also employs machine learning techniques to calibrate its query answers based on contextual information, including transportation modality, location, and time of day/week. QARTA is currently deployed in all Taxis and the third largest food delivery company in the State of Qatar, replacing the commercial map service that was in use, and responding in real-time to hundreds of thousands of daily API calls. Experimental evaluation of QARTA shows its comparable or higher accuracy than commercial services.

Web Feature Service (WFS) and Web Map Service (WMS)

2017 ◽  
pp. 2485-2488
Author(s):  
Christopher D. Michaelis ◽  
Daniel P Ames
Keyword(s):  
Web Map ◽  
Map Service

scholarly journals Research on Dynamic Knowledge Map Service System Using Computer Big Data

2021 ◽  
Vol 2083 (4) ◽  
pp. 042001
Author(s):  
Nan Zhang ◽  
Wenqiang Zhang ◽  
Yingnan Shang
Keyword(s):  
Big Data ◽  
Data Model ◽  
Structured Data ◽  
Knowledge Network ◽  
Practical Significance ◽  
Data Publishing ◽  
Knowledge Map ◽  
Related Data ◽  
Construction Of Knowledge ◽  
Map Service

Abstract The emergence of computer big data related data provides a new method for the construction of knowledge links in the knowledge map. This realizes an objective knowledge network with practical significance that is easier to be understood by machines. The article combines the four principles of linked data publishing content objects and their semantic characteristics, and uses the RDF data model to convert unstructured data on the Internet and structured data that adopts different standards into unified standard structured data for association. The system forms a huge knowledge map with semantics, intelligence, and dynamics.

scholarly journals Correction of Very High-Resolution Satellite Images using Control Points Captured by Web Map Service (WMS) server: Google Earth

2020 ◽  
Vol 9 (8) ◽  
pp. 188-194
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Google Earth ◽  
Ground Control ◽  
Control Points ◽  
Web Map ◽  
Ground Control Points ◽  
High Resolution Satellite Images ◽  
Map Scale ◽  
Map Service

The recent progress for spatial resolution of remote sensing imagery led to generate many types of Very HighResolution (VHR) satellite images, consequently, general speaking, it is possible to prepare accurate base map larger than 1:10,000 scale. One of these VHR satellite image is WorldView-3 sensor that launched in August 2014. The resolution of 0.31m makes WorldView-3 the highest resolution commercial satellite in the world. In the current research, a pan-sharpen image from that type, covering an area at Giza Governorate in Egypt, used to determine the suitable large-scale map that could be produced from that image. To reach this objective, two different sources for acquiring Ground Control Points (GCPs). Firstly, very accurate field measurements using GPS and secondly, Web Map Service (WMS) server (in the current research is Google Earth) which is considered a good alternative when GCPs are not available, are used. Accordingly, three scenarios are tested, using the same set of both 16 Ground Control Points (GCPs) as well as 14 Check Points (CHKs), used for evaluation the accuracy of geometric correction of that type of images. First approach using both GCPs and CHKs coordinates acquired by GPS. Second approach using GCPs coordinates acquired by Google Earth and CHKs acquired by GPS. Third approach using GCPs and CHKs coordinates by Google Earth. Results showed that, first approach gives Root Mean Square Error (RMSE) planimeteric discrepancy for GCPs of 0.45m and RMSE planimeteric discrepancy for CHKs of 0.69m. Second approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.75m. Third approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.40m. Taking map accuracy specification of 0.5mm of map scale, the worst values for CHKs points (1.75m&1,4m) resulted from using Google Earth as a source, gives the possibility of producing 1:5000 large-scale map compared with the best value of (0.69m) (map scale 1:2500). This means, for the given parameters of the current research, large scale maps could be produced using Google Earth, in case of GCPs are not available accurately from the field surveying, which is very useful for many users.

scholarly journals Performance Testing of Web Map Services tn three Dimensions – X, Y, Scale

2013 ◽  
Vol 21 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Dušan Cibulka
Keyword(s):  
Performance Testing ◽  
Service Performance ◽  
Performance Characteristics ◽  
Three Dimensions ◽  
Web Mapping ◽  
Practical Experiment ◽  
Web Map ◽  
Open Geospatial Consortium ◽  
Map Service ◽  
The Web

Abstract The paper deals with the performance testing of web mapping services. The paper describes map service tests in which it is possible to determine the performance characteristics of a map service, depending on the location and scale of the map. The implementation of the test is tailored to the Web Map Service specifications provided by the Open Geospatial Consortium. The practical experiment consists of testing the map composition acquired from OpenStreetMap data for the area of southwestern Slovakia. These tests permit checking the performance of services in different positions, verifying the configuration of services, the composition of a map, and the visualization of geodata. The task of this paper is to also highlight the fact that it is not sufficient to only interpret a map service performance with conventional indicators. A map service’s performance should be linked to information about the map’s scale and location.

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