Assessment of the usability of SAR and optical satellite data for monitoring spatio-temporal changes in surface water: Bodrog river case study

Ľ Kseňak, K Pukanská, K Bartoš, P Blišťan - Water, 2022 - mdpi.com
Mapping watercourses and their surroundings through remote sensing methods is a fast,
continuous, and effective method and is a crucial tool for capturing change and possibly …

[HTML][HTML] Incidence Angle Normalization of C-Band Radar Backscattering Coefficient over Agricultural Surfaces Using Dynamic Cosine Method

S Najem, N Baghdadi, H Bazzi, M Zribi - Remote Sensing, 2024 - mdpi.com
The radar-backscattering coefficient (σ0) depends on surface characteristics and
instrumental parameters (wavelength, polarization, and incidence angle). For Sentinel-1 …

Sentinel-1 Response to Canopy Moisture in Mediterranean Forests before and after Fire Events

F Pirotti, O Adedipe, B Leblon - Remote Sensing, 2023 - mdpi.com
This study investigates the sensibility of Sentinel-1 C-band backscatter to the moisture
content of tree canopies over an area of about 500 km2 in north-western Portugal, with …

Wet snow detection using dual-polarized Sentinel-1 SAR time series data considering different land categories

C Liu, Z Li, P Zhang, L Huang, Z Li, S Gao - Geocarto International, 2022 - Taylor & Francis
Snowmelt is a natural water resource, and its distribution is essential for understanding
regional climate change and hydrological cycle. In this study, using dual-polarized C-band …

Tracking burned area progression in an unsupervised manner using Sentinel-1 SAR data in Google Earth Engine

D Paluba, LG Papale, J Laštovička… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
The frequency of wildfires is increasing worldwide, contributing to a third of forest loss over
the last two decades. Tracking burned area progression using traditional optical remote …

Land cover mapping from colorized CORONA archived greyscale satellite data and feature extraction classification

A Agapiou - Land, 2021 - mdpi.com
Land cover mapping is often performed via satellite or aerial multispectral/hyperspectral
datasets. This paper explores new potentials for the characterisation of land cover from …

Estimating high-resolution snow depth over the North Hemisphere mountains utilizing active microwave backscatter and machine learning

Q Yang, L Yue, Y Peng, Q Yuan - Journal of Hydrology, 2024 - Elsevier
While ground meteorological stations provide accurate snow depth data, their limited spatial
coverage results in observational gaps. Satellites offer long-term, large-scale observations …

Estimating optical vegetation indices with Sentinel-1 SAR data and AutoML

D Paluba, BL Saux, F Sarti, P Stych - arXiv preprint arXiv:2311.07537, 2023 - arxiv.org
Current optical vegetation indices (VIs) for monitoring forest ecosystems are widely used in
various applications. However, continuous monitoring based on optical satellite data can be …

Application of Persistent Scatterer Interferometry to monitor land motion along radar line of sight in landslide-prone areas of Himachal Pradesh, India

M Kanwar, B Pokharel, S Lim - Geomatics, Natural Hazards and …, 2024 - Taylor & Francis
Landslides in mountainous regions are often triggered by vertical land movements induced
by tectonics or seismic activities, emphasizing the importance of monitoring such motions for …

Automatic forest cover classification using Sentinel-2 multispectral satellite data and machine learning algorithms in Google Earth Engine

K Onačillová, V Krištofová… - Acta Geographica …, 2023 - publications.cuni.cz
Forest cover plays an essential role in maintaining ecological equilibrium, mitigating climate
change, and securing a sustainable future for both humanity and the planet. Most countries …