Research on representing remote sensing images based on QTM

Zhenhua Lv*, Jianping Wu, Shengmao Zhang, Hui Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Representing RS (remote sensing) images under multi-resolution is a key component of "Digital Earth", and becomes one of the fundamental problems in Geography and Spatial Information Science. QTM (Quaternary Triangular Mesh) with excellent features of global continuity, stability, hierarchy, and uniformity has the potential ability to represent the global model. In this paper, we present a method of displaying the RS images. This method is primarily divided into two steps. First, the calculated geographical coordinate of each pixel in a dataset is transformed into a QTM code at a proper subdivision level, and the pixel value is also mapped into a triangular cell which is correlative to the pixel. Second, all the triangular cells are displayed by the use of OpenGL. The transformation from geographical coordinates to QTM codes are also examined at different subdivision levels. In the end, the experiment is performed with FengYun(FY-3) Satellite Data(HDF5 format) and aerial remote images (Tif format) of Shanghai in China. The results illustrate that this method is acceptable.

Original languageEnglish
Title of host publicationSixth International Symposium on Digital Earth
Subtitle of host publicationData Processing and Applications
Edition1
DOIs
StatePublished - 2010
Event6th International Symposium on Digital Earth: Data Processing and Applications - Beijing, China
Duration: 9 Sep 200912 Sep 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Number1
Volume7841
ISSN (Print)0277-786X

Conference

Conference6th International Symposium on Digital Earth: Data Processing and Applications
Country/TerritoryChina
CityBeijing
Period9/09/0912/09/09

Keywords

  • Coordinates transformation
  • HDF
  • QTM code
  • Quaternary triangular mesh
  • Remote sensing image

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