Related papers: Non-binary Snow Index for Multi-Component Surfaces
Spatiotemporal fusion aims to improve both the spatial and temporal resolution of remote sensing images, thus facilitating time-series analysis at a fine spatial scale. However, there are several important issues that limit the application…
Uncertainties of snowpack models and of their meteorological forcings limit their use by avalanche hazard forecasters, or for glaciological and hydrological studies. The spatialized simulations currently available for avalanche hazard…
With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and more difficult to manage sustainably. Reliable and automated methods for detecting,…
Road surface classification (RSC) is a key enabler for environment-aware predictive maintenance systems. However, existing RSC techniques often fail to generalize beyond narrow operational conditions due to limited sensing modalities and…
A satellite image is a remotely sensed image data, where each pixel represents a specific location on earth. The pixel value recorded is the reflection radiation from the earth's surface at that location. Multispectral images are those that…
Current Landsat Level 2 surface temperature products are derived using a single-channel (SC) methodology to estimate per-pixel surface temperature (ST) maps from Level~1 radiance data. A known issue with the Level 2 uncertainty, however, is…
Within the context of upcoming full-sky lensing surveys, the edge-preserving non- linear algorithm Aski is presented. Using the framework of Maximum A Posteriori inversion, it aims at recovering the full-sky convergence map from surveys…
In coded aperture snapshot spectral imaging (CASSI), the captured measurement entangles spatial and spectral information, posing a severely ill-posed inverse problem for hyperspectral images (HSIs) reconstruction. Moreover, the captured…
Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environments where only inertial navigation systems work, such as urban canyons. Despite decades of…
We present a blind multi-detector multi-component spectral matching method for all sky observations of the cosmic microwave background, working on the spherical harmonics basis. The method allows to estimate on a set of observation maps the…
Nowadays, the hyperspectral remote sensing imagery HSI becomes an important tool to observe the Earth's surface, detect the climatic changes and many other applications. The classification of HSI is one of the most challenging tasks due to…
Snapshot mosaic multispectral imagery acquires an undersampled data cube by acquiring a single spectral measurement per spatial pixel. Sensors which acquire $p$ frequencies, therefore, suffer from severe $1/p$ undersampling of the full data…
The exquisitely measured maps of fluctuations in the Cosmic Microwave Background (CMB) present the possibility to test the principle of Statistical Isotropy (SI) of the Universe through systematic observable measures for non-Statistical…
In this paper, we present a Bayesian approach for spectral unmixing of multispectral Lidar (MSL) data associated with surface reflection from targeted surfaces composed of several known materials. The problem addressed is the estimation of…
Defense Meteorological Satellite Program (DMSP-OLS) and Suomi National Polar-orbiting Partnership (SNPP-VIIRS) nighttime light (NTL) data are vital for monitoring urbanization, yet sensor incompatibilities hinder long-term analysis. This…
This paper proposes a novel non-terrestrial networks (NTNs) system that integrates optical intelligent reflecting surfaces (OIRS) and simultaneous transmitting and reflecting Intelligent reflecting surfaces (STAR-IRS) to address critical…
We investigate a novel non-parametric regression-based clustering algorithm for longitudinal data analysis. Combining natural cubic splines with Gaussian mixture models (GMM), the algorithm can produce smooth cluster means that describe the…
We present Multi-Layer Intensity Map, a novel 3D object representation for robot perception and autonomous navigation. Intensity maps consist of multiple stacked layers of 2D grid maps each derived from reflected point cloud intensities…
We present a Bayesian parametric component separation method for polarised microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarised foreground components. For the latter,…
During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction…