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Application of Javascript Technology in Railway Remote Sensing Image Thematic Mapping Automation.
- Source :
- Railway Investigation & Surveying; 2024, Vol. 50 Issue 5, p38-44, 7p
- Publication Year :
- 2024
-
Abstract
- Due to the non-standardization and the personalized need of thematic mapping, the processing efficiency of basic geographic information data has not been effectively improved. The thematic mapping technology based on Photoshop has been adopted in railway industry widely. This paper applied the JavaScript technology to the secondary development of mapping, called the API of Windows and Photoshop, and used common mapping modules, mapping functions, main parameters, and hotkeys to encapsulate packages. It realized batch processing of remote sensing images, automatically processing of features on thematic map, and modification of map features in human-machine interaction manner. The research includes three parts: (1) The introduction of the configure environment, compile platform, and result of secondary development based on Javascript. (2) The application of four application scenarios for JavaScript technology: 1 Image batch processing to achieve automatic spectral enhancement of remote sensing image. 3 Automatic mapping for thematic map elements. 2 Batch and automatic modification of features on maps. 4 processing of elements on the map in human-machine interaction manner. (3) The example of the thematic mapping of a railway project in Europe using remote sensing image for the verification of the feasibility. The results show that the technology can significantly improve the mapping efficiency, make it easier to standardize drawing map symbol, and solve the problems on high redundancy of data and low efficiency of execution during batch and automatic processing scripts. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 16727479
- Volume :
- 50
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Railway Investigation & Surveying
- Publication Type :
- Academic Journal
- Accession number :
- 180331081
- Full Text :
- https://doi.org/10.19630/j.cnki.tdkc.202404090004