Sentinel-2 data for land cover/use map**: A review
The advancement in satellite remote sensing technology has revolutionised the approaches
to monitoring the Earth's surface. The development of the Copernicus Programme by the …
to monitoring the Earth's surface. The development of the Copernicus Programme by the …
A review of irrigation information retrievals from space and their utility for users
Irrigation represents one of the most impactful human interventions in the terrestrial water
cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water …
cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water …
Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery
P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover map** via a multi-source deep learning architecture
The huge amount of data currently produced by modern Earth Observation (EO) missions
has allowed for the design of advanced machine learning techniques able to support …
has allowed for the design of advanced machine learning techniques able to support …
Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale
Soil moisture has a considerable impact on the hydrological cycle, runoff generation,
drought development, and water resources management. Soil moisture products provided …
drought development, and water resources management. Soil moisture products provided …
Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands
The short revisit time of the Sentinel-2 (S2) constellation entails a large availability of remote
sensing data, but S2 data have been rarely used to predict soil organic carbon (SOC) …
sensing data, but S2 data have been rarely used to predict soil organic carbon (SOC) …
Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation map** using deep learning
Identification of flood water extent from satellite images has historically relied on either
synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to …
synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to …
Soil moisture and irrigation map** in A semi-arid region, based on the synergetic use of Sentinel-1 and Sentinel-2 data
This paper presents a technique for the map** of soil moisture and irrigation, at the scale
of agricultural fields, based on the synergistic interpretation of multi-temporal optical and …
of agricultural fields, based on the synergistic interpretation of multi-temporal optical and …
Potential of Sentinel-1 radar data for the assessment of soil and cereal cover parameters
The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data
for the estimation of soil characteristics (roughness and water content) and cereal vegetation …
for the estimation of soil characteristics (roughness and water content) and cereal vegetation …
Penetration analysis of SAR signals in the C and L bands for wheat, maize, and grasslands
This paper assesses the potential of Synthetic Aperture Radar (SAR) in the C and L bands to
penetrate into the canopy cover of wheat, maize and grasslands. For wheat and grasslands …
penetrate into the canopy cover of wheat, maize and grasslands. For wheat and grasslands …