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|Title:||Multi-Sensor and Multi-Temporal Fusion of VHR Satellite Imagery based on KIM|
|Citation:||IEEE Geoscience and Remote Sensing Letters vol. 7 no. 1 p. 48-52|
|Publisher:||IEEE Geoscience and Remote Sensing Society|
|Type:||Articles in periodicals and books|
|Abstract:||Similar to many advanced approaches in data fusion and multi-sensor image analysis, Image Information Mining (IIM) is hampered by sensor-specific differences in spatial resolution and spectral response. This study examines the representation of semantic categories integrating Ikonos and Quickbird imagery in the Knowledge-Based Information Mining system KIM. An operationally viable processing sequence is presented which accounts for sensor-related differences along with an evaluation of the application of IIM technologies in operational rapid mapping scenarios.|
|JRC Institute:||Space, Security and Migration|
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