PlanetScope, Sentinel-2, and Sentinel-1 data integration for object-based land cover classification in Google Earth Engine

M Vizzari - Remote Sensing, 2022 - mdpi.com
PlanetScope (PL) high-resolution composite base maps have recently become available
within Google Earth Engine (GEE) for the tropical regions thanks to the partnership between …

Flood damage assessment with Sentinel-1 and Sentinel-2 data after Sardoba dam break with GLCM features and Random Forest method

B Tavus, S Kocaman, C Gokceoglu - Science of The Total Environment, 2022 - Elsevier
Accurate map** and monitoring of flooded areas are immensely required for disaster
management purposes, such as for damage assessment and mitigation. In this study, the …

[HTML][HTML] How textural features can improve SAR-based tropical forest disturbance map**

J Balling, M Herold, J Reiche - … Journal of Applied Earth Observation and …, 2023 - Elsevier
Spatially and timely accurate information about tropical forest disturbances is crucial for
tracking critical forest changes, supporting forest management, and enabling law …

Fusion of Sentinel-1 and Sentinel-2 data in map** the impervious surfaces at city scale

B Shrestha, S Ahmad, H Stephen - Environmental Monitoring and …, 2021 - Springer
Urbanization creates new development in open spaces and agricultural fields, synonymous
with increasing impervious surfaces. Such surfaces restrain the natural infiltration of water …

Sentinel 1 and Sentinel 2 for cropland map** with special emphasis on the usability of textural and vegetation indices

S Koley, J Chockalingam - Advances in Space Research, 2022 - Elsevier
Regional as well as global cropland database at a high spatial resolution like 10 m is not
available. This study aims to integrate the Sentinel-1 synthetic aperture radar (SAR) data …

Crop type classification with combined spectral, texture, and radar features of time-series Sentinel-1 and Sentinel-2 data

G Cheng, H Ding, J Yang, Y Cheng - International Journal of …, 2023 - Taylor & Francis
Crop type map** visualizes the spatial distribution pattern and proportion of planting
areas of different crop types, which is the basis for subsequent agricultural applications …

Cannabis detection from optical and RADAR data fusion: A comparative analysis of the SMILE machine learning algorithms in Google Earth Engine

L Sujud, H Jaafar, MAH Hassan, R Zurayk - Remote Sensing Applications …, 2021 - Elsevier
Accurate crop map** for agricultural monitoring requires the use of robust image
classification algorithms. Cultivation of illegal cannabis is common in the Bekaa plain …

Modeling of texture quantification and image classification for change prediction due to COVID lockdown using Skysat and Planetscope imagery

AK Shakya, A Ramola, A Vidyarthi - Modeling Earth Systems and …, 2022 - Springer
This research work models two methods together to provide maximum information about a
study area. The quantification of image texture is performed using the “grey level co …

[HTML][HTML] Quantifying irrigated winter wheat LAI in Argentina using multiple sentinel-1 incidence angles

G Caballero, A Pezzola, C Winschel, A Casella… - Remote sensing, 2022 - mdpi.com
Synthetic aperture radar (SAR) data provides an appealing opportunity for all-weather day
or night Earth surface monitoring. The European constellation Sentinel-1 (S1) consisting of …

Synergy of Sentinel-1 and Sentinel-2 time series for cloud-free vegetation water content map** with multi-output Gaussian processes

G Caballero, A Pezzola, C Winschel… - Remote Sensing, 2023 - mdpi.com
Optical Earth Observation is often limited by weather conditions such as cloudiness. Radar
sensors have the potential to overcome these limitations, however, due to the complex radar …