Remote sensing applications in sugarcane cultivation: A review
A large number of studies have been published addressing sugarcane management and
monitoring to increase productivity and production as well as to better understand landscape …
monitoring to increase productivity and production as well as to better understand landscape …
Synthetic aperture radar (SAR) for ocean: A review
Oceans cover approximately 71% of the Earth's surface and provide numerous services to
the environment and humans. Precise, real-time, and large-scale monitoring of the …
the environment and humans. Precise, real-time, and large-scale monitoring of the …
Flood detection in urban areas using satellite imagery and machine learning
Urban flooding poses risks to the safety of drivers and pedestrians, and damages
infrastructures and lifelines. It is important to accommodate cities and local agencies with …
infrastructures and lifelines. It is important to accommodate cities and local agencies with …
A novel intelligence approach based active and ensemble learning for agricultural soil organic carbon prediction using multispectral and SAR data fusion
Monitoring agricultural soil organic carbon (SOC) has played an essential role in
sustainable agricultural management. Precise and robust prediction of SOC greatly …
sustainable agricultural management. Precise and robust prediction of SOC greatly …
Rice crop detection using LSTM, Bi-LSTM, and machine learning models from Sentinel-1 time series
H Crisóstomo de Castro Filho… - Remote Sensing, 2020 - mdpi.com
The Synthetic Aperture Radar (SAR) time series allows describing the rice phenological
cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel …
cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel …
[HTML][HTML] Large-scale flood modeling and forecasting with FloodCast
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model
parameters as well as incurring a high computational cost. This limits their ability to …
parameters as well as incurring a high computational cost. This limits their ability to …
Flood inundation map**-Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine
Flood inundation maps provide valuable information towards flood risk preparedness,
management, communication, response, and mitigation at the time of disaster, and can be …
management, communication, response, and mitigation at the time of disaster, and can be …
[HTML][HTML] Comparing sentinel-1 surface water map** algorithms and radiometric terrain correction processing in southeast asia utilizing google earth engine
Satellite remote sensing plays an important role in the monitoring of surface water for
historical analysis and near real-time applications. Due to its cloud penetrating capability …
historical analysis and near real-time applications. Due to its cloud penetrating capability …
Deep-learning-based burned area map** using the synergy of Sentinel-1&2 data
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 …
health of ecosystems and leaving a trail of destruction. Accurate information over burned …
Flood hazard and risk map** by applying an explainable machine learning framework using satellite imagery and GIS data
G Antzoulatos, IO Kouloglou, M Bakratsas… - Sustainability, 2022 - mdpi.com
Flooding is one of the most destructive natural phenomena that happen worldwide, leading
to the damage of property and infrastructure or even the loss of lives. The escalation in the …
to the damage of property and infrastructure or even the loss of lives. The escalation in the …