Utilization of Latest Geospatial Web Service Technologies for Remote Sensing Education through GeoBrain Sysem

2006 ◽  
Author(s):  
M. Deng ◽  
L. Di
Keyword(s):  
Remote Sensing ◽  
Web Service ◽  
Geospatial Web Service

scholarly journals Model-driven geospatial web service composition

2014 ◽  
Vol XL-6 ◽  
pp. 7-11
Author(s):  
W. Du ◽  
H. Fan ◽  
J. Li ◽  
H. Wang
Keyword(s):  
Web Service ◽  
Service Composition ◽  
Process Model ◽  
Heterogeneous Data ◽  
Web Service Composition ◽  
Dynamic Binding ◽  
Service Chain ◽  
Model Driven ◽  
Geospatial Web Service

A lot of work has been done on the geospatial service composition to support advanced processing, spatial calculation, and invoking of heterogeneous data. However, the quality of service chain is rarely considered and the process model cannot be reused. A modeldriven way of geospatial web service composition is proposed in this work, the service composition is treated as an optimization problem by <i>GwcsFlow</i> model and dynamic binding mechanism. The case of facility location analysis is provided to demonstrate the improvements in geospatial service composition through optimization algorithms.

Geospatial Web Service Sub-chain Ranking and Recommendation

2014 ◽  
Author(s):  
Xiaolei Wang ◽  
Zehui Cheng ◽  
Zhangbing Zhou ◽  
Ke Ning ◽  
Liang Jie Zhang
Keyword(s):  
Web Service ◽  
Geospatial Web Service

Semantics-based automatic composition of geospatial Web service chains

2007 ◽  
Vol 33 (5) ◽  
pp. 649-665 ◽  
Author(s):  
Peng Yue ◽  
Liping Di ◽  
Wenli Yang ◽  
Genong Yu ◽  
Peisheng Zhao
Keyword(s):  
Web Service ◽  
Automatic Composition ◽  
Geospatial Web Service

scholarly journals REMOTE SENSING ANALYTICAL GEOSPATIAL OPERATIONS DIRECTLY IN THE WEB BROWSER

2018 ◽  
Vol XLII-4 ◽  
pp. 403-410 ◽  
Author(s):  
J. Masó ◽  
A. Zabala ◽  
I. Serral ◽  
X. Pons
Keyword(s):  
Remote Sensing ◽  
Web Service ◽  
Remote Sensing Data ◽  
Web Browsers ◽  
Spectral Indices ◽  
Spatial Filters ◽  
Web Browser ◽  
Server Side ◽  
Client Side ◽  
Fine Tune

<p><strong>Abstract.</strong> Current map viewers that run on modern web browsers are mainly requesting images generated on the fly in the server side and transferred in pictorial format that they can display (PNG or JPEG). In OGC WMS standard this is done for the whole map view while in WMTS is done per tiles. The user cannot fine tune personalized visualization or data analysis in the client side. Remote sensing data is structured in bands that are visualize individually (manually adjusting contrast), create RGB combinations or present spectral indices. When these operations are not available in map browsers professional are forced to download hundreds of gigabytes of remote sensing imagery to take a good look at the data before deciding if it fits for a purpose. A possible solution is to create a web service that is able to perform these operations on the server side (https://www.sentinel-hub.com). This paper proposes that the server should communicate the data values to the client in a format that the client can directly process using two new additions in HTML5: canvas edition and array buffers. In the client side, the user can interact with a JavaScript interface changing symbolizations and doing some analytical operations without having to request any data again to the server. As a bonus, the user is able to perform queries to the data in a more dynamic way, applying spatial filters, creating histograms, generating animations of a time series or performing complex calculations among bands of the different loaded datasets.</p>

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