Mobile app approach by open source stack for satellite images utilization

Mobile apps in information communication technology is regarded as the dominant trend from many application fields covering science and engineering. However, most mobile apps in the application communities dealing with satellite image data sets are somewhat on the limited level, and it is generally...

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Bibliographic Details
Published in:Remote sensing letters 2013-07, Vol.4 (7), p.648-656
Main Authors: Kang, Sanggoo, Lee, Kiwon
Format: Article
Language:English
Subjects:
Applications programs
Applied geophysics
browsing
communications technology
data collection
Earth sciences
Earth, ocean, space
engineering
Exact sciences and technology
Freeware
image analysis
Image processing
Internal geophysics
Remote sensing
Satellites
Servers
Source code
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Summary:Mobile apps in information communication technology is regarded as the dominant trend from many application fields covering science and engineering. However, most mobile apps in the application communities dealing with satellite image data sets are somewhat on the limited level, and it is generally the case that air-photos or high-resolution satellite images are used for the background for other contents services. Along with the current status and latent possibility of mobile analytics, it is necessary to design and implement a sort of practical mobile app for satellite images utilization. The mobile device used in this study is a android-driven smartphone. The main functionalities with mobile apps in this study are geo-metadata searching and browsing interlinked with embedded database, vector layer overlay from users’ local data sets, actual image processing by mobile gesture requesting and geo-database server connection. Especially, examples for satellite image processing provided by this approach emphasize the filtering or detection level such as line segmentation, edge detection and corner point detection. It is practicable to implement its extension to customize and optimize the target applications along with more users’ requirements. Furthermore, all these tasks in both mobile client and server are carried out on open source stacks. It is expected that this study can be a meaningful attempt or an application model to develop more practical mobile apps for remote sensing images and geo-based contents.
ISSN:2150-7058
2150-704X
2150-7058
DOI:10.1080/2150704X.2013.781286