Automated processing of high resolution airborne images for earthquake damage assessment

Several spectral, altimetric, and planimetric spatial data sets were used for feature extraction and quality assessment, namely: a pansharpened QuickBird image, its multispectral

Classification and extraction of spatial features in urban areas using high- resolution multi-spectral imagery, IEEE Geoscience and Remote Sensing Letters ,

Therefore, thanks also to a 1 m pixel airborne LiDAR (Light Detection And Ranging) dataset, we analyzed in detail the correlation between geomorphological features and

In 2011, assessment was conducted using a combination of Landsat (5 and 7) and for the first time, 5m high resolution imagery, with RapidEye coverage for approximately half of

Rottensteiner F., Briese C., 2002, A new method for building extraction in urban areas from high-resolution LiDAR data, International Archives of the

A high resolution climatology of precipitation and deep convection over the Mediterranean region from operational satellite microwave data: development and application to the

Change detection of buildings in urban environment from high spatial resolution satellite images using existing cartographic data and prior knowledge. In: IEEE

This study investigates the potential of using very high resolution (VHR) QuickBird data to conduct vegetation classification of the Sundarban mangrove forest in Bangladesh