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 …
[HTML][HTML] Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model
Leaf area index (LAI) is a terrestrial essential climate variable that is required in a variety of
ecosystem and climate models. The Global LAnd Surface Satellite (GLASS) LAI product has …
ecosystem and climate models. The Global LAnd Surface Satellite (GLASS) LAI product has …
Cloudy-sky land surface temperature from VIIRS and MODIS satellite data using a surface energy balance-based method
Land surface temperature (LST) has been effectively retrieved from thermal infrared (TIR)
satellite measurements under clear-sky conditions. However, TIR satellite data are often …
satellite measurements under clear-sky conditions. However, TIR satellite data are often …
Simultaneous retrieval of land surface temperature and emissivity from the FengYun-4A advanced geosynchronous radiation imager
This paper extends a new temperature and emissivity separation (TES) algorithm for
retrieving land surface temperature and emissivity (LST and LSE) to the Advanced …
retrieving land surface temperature and emissivity (LST and LSE) to the Advanced …
[HTML][HTML] Comprehensive assessment of five global daily downward shortwave radiation satellite products
The downward shortwave radiation (DSR) is a critical parameter of the surface radiation
budget. Several DSR satellite products have been developed in recent years. In this study …
budget. Several DSR satellite products have been developed in recent years. In this study …
Transferring Deep Models for Cloud Detection in Multisensor Images via Weakly Supervised Learning
Recently, deep learning has been widely used for cloud detection in satellite images;
however, due to radiometric and spatial resolution differences in images from different …
however, due to radiometric and spatial resolution differences in images from different …
A priori land surface reflectance synergized with multiscale features convolution neural network for MODIS imagery cloud detection
N Ma, L Sun, C Zhou, Y He, C Dong… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Moderate resolution imaging spectrometer (MODIS) images are widely used in land, ocean,
and atmospheric monitoring, due to their wide spectral coverage, high temporal resolution …
and atmospheric monitoring, due to their wide spectral coverage, high temporal resolution …
Variation of intra-daily instantaneous FAPAR estimated from the geostationary Himawari-8 AHI data
The fraction of absorbed photosynthetically active radiation (FAPAR) quantifies the efficiency
of light absorption by vegetation. The intra-daily variation in FAPAR is important for …
of light absorption by vegetation. The intra-daily variation in FAPAR is important for …
Landsat snow-free surface albedo estimation over sloping terrain: Algorithm development and evaluation
Surface albedo plays a key role in global climate modeling as a factor controlling the energy
budget. Satellite observations were utilized to estimate surface albedo at global and …
budget. Satellite observations were utilized to estimate surface albedo at global and …
Simultaneous estimation of five temporally regular land variables at seven spatial resolutions from seven satellite data using a multi-scale and multi-depth …
Various satellite sensors have provided a huge amount of observations of Earth's
environment at variable spatial and temporal resolutions. Many global coarse-resolution …
environment at variable spatial and temporal resolutions. Many global coarse-resolution …