Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data

Q Zhang, L Ge, R Zhang, GI Metternicht, Z Du… - Remote Sensing of …, 2021 - Elsevier
Around 350 million hectares of land are affected by wildfires every year influencing the
health of ecosystems and leaving a trail of destruction. Accurate information over burned …

Landslide detection and susceptibility modeling on cameron highlands (Malaysia): A comparison between random forest, logistic regression and logistic model tree …

VH Nhu, A Mohammadi, H Shahabi, BB Ahmad… - Forests, 2020 - mdpi.com
We used remote sensing techniques and machine learning to detect and map landslides,
and landslide susceptibility in the Cameron Highlands, Malaysia. We located 152 landslides …

A Possible Land Cover EAGLE Approach to Overcome Remote Sensing Limitations in the Alps Based on Sentinel-1 and Sentinel-2: The Case of Aosta Valley (NW …

T Orusa, D Cammareri, E Borgogno Mondino - Remote Sensing, 2022 - mdpi.com
Land cover (LC) maps are crucial to environmental modeling and define sustainable
management and planning policies. The development of a land cover mapping continuous …

A tutorial on tomographic synthetic aperture radar methods

SA Khoshnevis, S Ghorshi - SN Applied Sciences, 2020 - Springer
Abstract Synthetic Aperture Radar (SAR) is a type of radar that is mounted on an airborne
platform and aims to increase the resolution of the acquisitions by traveling over the target …

Aquifer and land subsidence interaction assessment using sentinel-1 data and DInSAR technique

F Rafiei, S Gharechelou, S Golian… - … International Journal of …, 2022 - mdpi.com
Climate change and overpopulation have led to an increase in water demands worldwide.
As a result, land subsidence due to groundwater extraction and water level decline is …

A multi-sensor comparative analysis on the suitability of generated DEM from Sentinel-1 SAR interferometry using statistical and hydrological models

A Mohammadi, S Karimzadeh, SJ Jalal, KV Kamran… - Sensors, 2020 - mdpi.com
Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental
studies. Many essential layers can be extracted from this land surface information, including …

Applying machine learning and time-series analysis on Sentinel-1A SAR/InSAR for characterizing Arctic tundra hydro-ecological conditions

MA Merchant, M Obadia, B Brisco, B DeVries, A Berg - Remote Sensing, 2022 - mdpi.com
Synthetic aperture radar (SAR) is a widely used tool for Earth observation activities. It is
particularly effective during times of persistent cloud cover, low light conditions, or where in …

Modeling SAR Observables by Combining a Crop-Growth Model With Machine Learning

T Nikaein, P Lopez-Dekker… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
In this article, our aim is to estimate synthetic aperture radar (SAR) observables, such as
backscatter in VV and VH polarizations, as well as the VH/VV ratio, cross ratio, and …

Implementing the European Space Agency's SentiNel Application Platform's Open-Source Python Module for Differential Synthetic Aperture Radar Interferometry …

M Occhipinti, F Carboni, S Amorini, N Paltriccia… - Remote Sensing, 2023 - mdpi.com
Differential SAR Interferometry is a largely exploited technique to study ground
deformations. A key application is the detection of the effects promoted by earthquakes …

[HTML][HTML] Assessing the vertical displacement of the grand Ethiopian renaissance dam during its filling using DInSAR technology and its potential acute consequences …

H El-Askary, A Fawzy, R Thomas, W Li, N LaHaye… - Remote Sensing, 2021 - mdpi.com
The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is
currently under construction and has been filling at a fast rate without sufficient known …