Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects
The presence of clouds prevents optical satellite imaging systems from obtaining useful
Earth observation information and negatively affects the processing and application of …
Earth observation information and negatively affects the processing and application of …
Cloud detection methodologies: Variants and development—A review
S Mahajan, B Fataniya - Complex & Intelligent Systems, 2020 - Springer
Cloud detection is an essential and important process in satellite remote sensing.
Researchers proposed various methods for cloud detection. This paper reviews recent …
Researchers proposed various methods for cloud detection. This paper reviews recent …
[HTML][HTML] Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion
Optical remote sensing imagery is at the core of many Earth observation activities. The
regular, consistent and global-scale nature of the satellite data is exploited in many …
regular, consistent and global-scale nature of the satellite data is exploited in many …
Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000–2019
Exploring land use structure and dynamics is critical for urban planning and management.
This study attempts to understand the Wuhan development mode since the beginning of the …
This study attempts to understand the Wuhan development mode since the beginning of the …
DABNet: Deformable contextual and boundary-weighted network for cloud detection in remote sensing images
In recent years, deep convolutional neural networks (DCNNs) have made significant
progress in cloud detection tasks, and the detection accuracy has been greatly improved …
progress in cloud detection tasks, and the detection accuracy has been greatly improved …
Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors
Cloud detection is an important preprocessing step for the precise application of optical
satellite imagery. In this paper, we propose a deep learning based cloud detection method …
satellite imagery. In this paper, we propose a deep learning based cloud detection method …
Remote sensing image spatiotemporal fusion using a generative adversarial network
H Zhang, Y Song, C Han… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Due to technological limitations and budget constraints, spatiotemporal fusion is considered
a promising way to deal with the tradeoff between the temporal and spatial resolutions of …
a promising way to deal with the tradeoff between the temporal and spatial resolutions of …
Accessing the temporal and spectral features in crop type mapping using multi-temporal Sentinel-2 imagery: A case study of Yi'an County, Heilongjiang province …
Crop type mapping visualizes the spatial distribution patterns and proportions of the
cultivated areas with different crop types, and is the basis for subsequent agricultural …
cultivated areas with different crop types, and is the basis for subsequent agricultural …
Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion
Cloud contamination is an inevitable problem in optical remote sensing images. Unlike thick
clouds, thin clouds do not completely block out background which makes it possible to …
clouds, thin clouds do not completely block out background which makes it possible to …
Estimating vertically growing crop above-ground biomass based on UAV remote sensing
The accurate estimation of crop above-ground biomass (AGB) can assist in crop growth
monitoring and grain yield prediction. Remote sensing has been widely used for AGB …
monitoring and grain yield prediction. Remote sensing has been widely used for AGB …