TGeoSource Lab


Taiwan Geospatial Open Source Lab

About

Taiwan Geospatial Open Source Lab (TGeoSource Lab) aims to promote open source and the development of free software on geospatial technologies, mainly in the fields of photogrammetry, remote sensing, and GIS. To facilitate this, the Lab members utilize the geospatial open source to carry out fundamental and to deliver geospatial solutions to engineering problems. Refer to the Open Source Project and Publications pages for more. We also organize tutorials, webinars, and joint sessions to provide training for undergraduate and graduate students in the programs of Surveying and Mapping, Geomatics, Geographic Information Science, Physical Geography. We currently provide training courses in Quantuim GIS, PostgreSQL, and OGC SensorThings API. The promotion of open source can provide us free software and make accessible the latest geospatial technologies to the wider geospatial community.


People

Dr. Chao-Hung Lin

National Cheng Kung University
Department of Geomatics
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Dr. Tee-Ann Teo

National Chiao Tung University
Department of Civil Engineering
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Dr. Chih‐Yuan Huang

National Central University
Center for Space and Remote Sensing Research
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Open Source Project

shp2geojson.js

Huang-Sin Syu


Convert shapefile to geoJSON via a web browser without Server-Side code. This conversion will unzip your file and reproject the data with correct encoding in JavaScript.

Traning & Education


Publications

Drawing Road Networks with Mental Maps

Shih-Syun Lin , Chao-Hung Lin, Yan-Jhang Hu, and Tong-Yee Lee

IEEE Transactions on Visualization and Computer Graphics, Vol. 20, No. 9, 2014.
A novel road network warping for stylized map generation.
Point Cloud Encoding for 3D Building Model Retrieval

Jyun-Yuan Chen, Chao-Hung Lin, Po-Chi Hsu, and Chung-Hao Chen

IEEE Transactions on Multimedia, Vsdfsdfsadfasdfsadfol. 16, No. 2, pp. 337-345, 2014.
A novel point cloud encoding method for 3D building model retrieval.
Eigen-feature Analysis of Weighted Covariance Matrices for LiDAR Point Cloud Classification

Chao-Hung Lin, Jyun-Yuan Chen, Po-Lin Su, and Chung-Hao Chen

ISPRS Journal of Photogrametry and Remote Sensing, Vol. 94, pp. 70-79, 2014.
An improved eigh-feature generation method for point cloud classification.

Resources


Other Geo4all Labs