The Advanced Land Imager (ALI) is a multispectral sensor onboard the National Aeronautics and Space Administration Earth Observing 1 (EO-1) satellite. It has similar spatial resolution to Landsat-7 Enhanced Thematic Mapper Plus (ETM+), with three additional spectral bands. We developed new algorithms for estimating both land surface broadband albedo and leaf area index (LAI) from ALI data. A re...

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validatio...

Merging of different data sets is often used in digital image processing to improve the visual and analytical quality of the data. The analyst may need to merge different types of data. In this process, different data such as satellite imagery from the same sensor but with different resolution, satellite imagery from different sensors with varying resolution, digitized aerial photography and sa...

This paper presents an automatic system for generating multi-scale colour 3D satellite images and dynamic visualization of 3D images through the Internet. Medium-resolution satellite images such as Landsat 7 and high-resolution satellite images such as Ikonos or QuickBird are the data sources for the multi-scale 3D images. New image fusion, colour enhancement and stereoscopy algorithms are deve...

With the advancement of remote sensing sensor technologies, images of the earth’s surface have been collected at different spatial resolutions, in different spectral wavelengths (panchromatic, multispectral, hyperspectral), and with mono or stereoscopic views. The advancement of the technologies for geospatial information acquisition and extraction has allowed the generation of digital elevatio...

The reflections recorded on satellite images have been affected by various environmental factors. In these images, some of these factors are combined with other environmental factors that cannot be distinguished. Therefore, it seems wise to model these environmental phenomena in the form of hybrid indicators. In this regard, satellite imagery and machine learning methods can play a unique role ...