In recent years, there has been a growing interest in deep learning-based pansharpening. Thus far, research mainly focused on architectures. Nonetheless, model training is an equally important issue. A first problem the absence of ground truths, unavoidable This often addressed by networks reduced resolution domain and using original data as truth, relying implicit scale invariance assumption. ...

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In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)CDOM) and absorption slope (S300–500) in lakes using field sampling and optical remote sensing data for an area of 350 km2 in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band refle...

The reliance on ground-based measurements has been a long-standing barrier toward deriving river discharge for ungauged headwaters, which are quite sensitive to climate change due relatively high contributions of snow and glacier meltwater discharge. In addition, information pertaining is scarce inconsistent across the globe economic, geographic, political reasons. Therefore, understanding spat...

The geometric resolution of space images has been improved. With WorldView-1 and GeoEye-1 images taken from space with 0.5m ground sampling distance (GSD) are now available. The Bosphorus Engineering Consultancy Services Inc (BIMTAS), company of Istanbul Greater Municipality ordered a WorldView-1 image, covering large parts of Istanbul city. For the orientation and investigation of the scene ac...

The Working Group 4 of Commission I on “Geometric and Radiometric Modelling of Optical Spaceborne Sensors” will provide on its website several stereo data sets from high and very high resolution spaceborne stereo sensors. Among these are data from the 2.5 meter class like ALOS-PRISM and Cartosat-1 as well as, in near future, data from the highest resolution sensors (0.5 m class) like GeoEye-1 a...

Remote sensing of the Earth's surface water is critical in a wide range environmental studies, from evaluating societal impacts seasonal droughts and floods to large-scale implications climate change. Consequently, large literature exists on classification satellite imagery. Yet, previous methods have been limited by 1) spatial resolution public imagery, 2) schemes that operate at pixel level, ...

This study proposes a novel method for multichannel image gray level co-occurrence matrix (GLCM) texture representation. It is well known that the standard procedure for the automatic extraction of GLCM textures is based on a mono-spectral image. In real applications, however, the GLCM texture feature extraction always refers to multi/hyperspectral images. The widely used strategy to deal with ...