High Resolution Multispectral and Hyperspectral Data Fusion for Advanced Geospatial Information Products

2007 ◽  
Author(s):  
W. P. Bissett ◽  
David D. Kohler
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Hyperspectral Data ◽  
Geospatial Information ◽  
Information Products

scholarly journals Development of urban area geospatial information products from high resolution satellite imagery using advanced image analysis techniques

2004 ◽  
Author(s):  
◽  
Aaron K. Shackelford
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Urban Area ◽  
Satellite Imagery ◽  
Training Data ◽  
Automated Image Analysis ◽  
Data Generation ◽  
Geospatial Information ◽  
Information Products ◽  
High Resolution Satellite Imagery

The latest generation of commercial satellite imaging sensors have a number of characteristics (e.g. high spatial resolution, multispectral bands, and quick revisit time), that make them ideal data sources for a variety of urban area applications. The goal of this doctoral research was to develop advanced automated and semi-automated image analysis and classification techniques for the extraction of urban area geospatial information products from commercial high-resolution satellite imagery. We developed two semi-automated urban land cover classification approaches, as well as fully automated techniques for road network and 2-D building footprint extraction. By utilizing fully automated feature extraction techniques for training data generation, a self-supervised classification approach was also developed. The self-supervised classifier is significantly more accurate than traditional classification approaches, and unlike traditional approaches it is fully automated. The development of automated and semi-automated techniques for generation of urban geospatial information products is of high importance not only for the many applications where they can be used but also because the large volume of data collected by these sensors exceeds the human capacity of trained image specialists to analyze. In addition, many applications, especially those for the military and intelligence communities, require near real time exploitation of the image data.

scholarly journals Resolution Enhancement of Hyperspectral Data Exploiting Real Multi-Platform Data

2020 ◽  
Author(s):  
Rocco Restaino ◽  
Gemine Vivone ◽  
Paolo Addesso ◽  
Daniele Picone ◽  
Jocelyn Chanussot
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Resolution Enhancement ◽  
Remotely Sensed ◽  
Hyperspectral Data ◽  
Image Sharpening ◽  
Limited Availability ◽  
The Earth ◽  
Remotely Sensed Images

Multi-platform data introduce new possibilities in the context of data fusion, as they allow to exploit several remotely sensed images acquired by different combinations of sensors. This scenario is particularly interesting for the sharpening of hyperspectral (HS) images, due to the limited availability of high-resolution (HR) sensors mounted onboard of the same platform as that of the HS device. However, the differences in the acquisition geometry and the nonsimultaneity of this kind of observations introduce further difficulties whose effects have to be taken into account in the design of data fusion algorithms. In this study, we present the most widespread HS image sharpening techniques and assess their performances by testing them over real acquisitions taken by the Earth Observing-1 (EO-1) and the WorldView-3 (WV3) satellites. We also highlight the difficulties arising from the use of multi-platform data and, at the same time, the benefits achievable through this approach.

Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis

2013 ◽  
Vol 54 ◽  
pp. 249-258 ◽  
Author(s):  
Simon J. Buckley ◽  
Tobias H. Kurz ◽  
John A. Howell ◽  
Danilo Schneider
Keyword(s):  
Data Fusion ◽  
Hyperspectral Data ◽  
Terrestrial Lidar ◽  
Fusion Products

Synthetic data generation of high-resolution hyperspectral data using DIRSIG

2007 ◽  
Author(s):  
Marek K. Jakubowski ◽  
David Pogorzala ◽  
Timothy J. Hattenberger ◽  
Scott D. Brown ◽  
John R. Schott
Keyword(s):  
High Resolution ◽  
Synthetic Data ◽  
Hyperspectral Data ◽  
Data Generation ◽  
Synthetic Data Generation

Data fusion in buildings: Synthesis of high-resolution IEQ and occupant tracking data

2021 ◽  
pp. 146047
Author(s):  
Brett Pollard ◽  
Fabian Held ◽  
Lina Engelen ◽  
Lauren Powell ◽  
Richard de Dear
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Tracking Data
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