[HTML][HTML] Landslide failures detection and map** using Synthetic Aperture Radar: Past, present and future

AC Mondini, F Guzzetti, KT Chang, O Monserrat… - Earth-Science …, 2021 - Elsevier
Landslides are geomorphological processes that shape the landscapes of all continents,
dismantling mountains and contributing sediments to the river networks. Caused by …

[HTML][HTML] Sentinel-1 interferometric coherence as a vegetation index for agriculture

A Villarroya-Carpio, JM Lopez-Sanchez… - Remote Sensing of …, 2022 - Elsevier
In this study, the use of Sentinel-1 interferometric coherence data as a tool for crop
monitoring has been explored. For this purpose, time series of images acquired by Sentinel …

Retrieval of digital elevation models from Sentinel-1 radar data–open applications, techniques, and limitations

A Braun - Open Geosciences, 2021 - degruyter.com
With the launch of Sentinel-1 in 2014, a new era of openly accessible spaceborne radar
imagery was begun, and its potential has been demonstrated throughout all fields of …

Global seasonal Sentinel-1 interferometric coherence and backscatter data set

J Kellndorfer, O Cartus, M Lavalle, C Magnard, P Milillo… - Scientific Data, 2022 - nature.com
This data set is the first-of-its-kind spatial representation of multi-seasonal, global C-band
Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter …

Time-series of Sentinel-1 interferometric coherence and backscatter for crop-type map**

A Mestre-Quereda, JM Lopez-Sanchez… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The potential use of the interferometric coherence measured with Sentinel-1 satellites as
input feature for crop classification is explored in this study. A one-year time-series of …

Mowing detection using Sentinel-1 and Sentinel-2 time series for large scale grassland monitoring

M De Vroey, L de Vendictis, M Zavagli… - Remote Sensing of …, 2022 - Elsevier
Managed grasslands cover about one third of the European utilized agricultural area.
Appropriate grassland management is key for balancing trade-offs between provisioning …

An interpretable attention-based deep learning method for landslide prediction based on multi-temporal InSAR time series: A case study of **

Q Zhao, Q **e, X Peng, K Lai, J Wang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
This study investigates the application of coherence and backscattering, derived from time-
series Sentinel-1 synthetic aperture radar imagery of a crop season (18 scenes with a 12 …

[HTML][HTML] Grassland mowing detection using sentinel-1 time series: Potential and limitations

M De Vroey, J Radoux, P Defourny - Remote Sensing, 2021 - mdpi.com
Grasslands encompass vast and diverse ecosystems that provide food, wildlife habitat and
carbon storage. Their large range in land use intensity significantly impacts their ecological …

NDVI estimation using Sentinel-1 data over wheat fields in a semiarid Mediterranean region

E Ayari, Z Kassouk, Z Lili-Chabaane… - GIScience & Remote …, 2024 - Taylor & Francis
Annual crop monitoring is a key parameter for managing agricultural strategies. Several
studies have relied on remote sensing products such as the normalized difference …