Introduction

Enabling visual explorations of large-scale geospatial data over the Web is practically useful in many domains. While sophisticated techniques have been developed in GIS and spatial databases to speed up query processing and more complex analytical tasks, the limited network bandwidth and computing power of Web browsers have made explorations of large-scale geospatial data over the Web a true technical challenge. Our research focuses have been on designing and implementing novel efficient data structures and algorithms on the server side to improve overall system performance. Needless to say, there are quite a few practical technical issues to be solved, such as security and user access control, efficient communications between clients and servers and effective GUIs, to build real-world applications.

 

Visual Exploration of Large-Scale Species Distribution Data

Online Demo: URL http://geoteci.engr.ccny.cuny.edu/birds30s/BirdsQuest.html

Related Publication: 

1.       Jianting Zhang (2012). A high-performance web-based information system for publishing large-scale species range maps in support of biodiversity studies. Ecological Informatics 8: 68-77. [Link][Local Copy]

2.      Jianting Zhang, Michael Gertz, Le Gruenwald, Efficiently Managing Large-Scale Raster Species Distribution Data in PostgreSQL. Proceedings of ACM-GIS09, Nov. 4-6, Seattle, WA. (doi: 10.1145/1653771.1653815) (Full paper acceptance rate 38/185). [Link][Local Copy]

3.  Jianting Zhang, Efficiently managing large scale species range maps in a spatial database environment, Proceedings of 17th International Conference on GeoInformatics, Aug 12-14, 2009, Fairfax, VA. (DOI: 10.1109/GEOINFORMATICS.2009.5293395). [Link][Local Copy]

 

Visual Exploration of Large-Scale Geospatial Rasters

Online Demo: UR: http://geoteci.engr.ccny.cuny.edu/rasterexplorer/comgeotiling/TestOverlay.html

 Related Publications

1.     Jianting Zhang and Simin You. Supporting Web-based Visual Exploration of Large-Scale Raster Geospatial Data Using Binned Min-Max Quadtree. Proceedings of the 22nd International Scientific and Statistical Database Management Conference (SSDBM10). June 30-July 2 2010, Heidelberg, Germany. Springer Lecture Notes in Computer Science (LNCS) 6187, pp. 379-396. (10.1007/978-3-642-13818-8_27) [Link][Local Copy]

2.     Jianting Zhang and Simin You. Dynamic Tiled Map Services: Supporting Query-Based Visualization of Large-Scale Raster Geospatial Data. Proceedings of the 1st International Conference on Computing for Geospatial Research & Application (COM.Geo10). June 21-23, Washington DC. USA. ACM Digital Library DOI 10.1145/1823854.1823877. [Link][Local Copy]

 

NYC CrashMap: interactive visualizing and querying millions of crashes over the Web

Project page with Screen Snapshots

Online Demo (password required)

Brief Description: NYC has more than 1.7 traffic million crashes from 1998 to 2007. As part of the NYC Traffic Calming Measurement project, we have been working with the Office of Road Safety at the NYC Department of Transportation (NYCDOT) to develop a Web-based tool to efficiently manage crash records over the Web.  While the project is application driven and considerable efforts have been put on improving user interfaces, several optimization techniques have been developed which are more interesting from a research perspective.