13 citations as recorded by crossref.

1. Significant discrepancies of land surface daily net radiation among ten remotely sensed and reanalysis products X. Yin et al. 10.1080/17538947.2023.2253211
2. QIENet: Quantitative irradiance estimation network using recurrent neural network based on satellite remote sensing data L. Nie et al. 10.1016/j.jag.2023.103584
3. Multispectral Assessment of Net Radiations Using Comprehensive Multi-Satellite Data M. Arshad et al. 10.3390/w16233378
4. Impacts of climatic zones on urban heat island: Spatiotemporal variations, trends, and drivers in China from 2001–2020 X. Geng et al. 10.1016/j.scs.2022.104303
5. Evolution of Meteosat Solar and Infrared Spectra (2004–2022) and Related Atmospheric and Earth Surface Physical Properties J. Fernández & C. Georgiev 10.3390/atmos14091354
6. LandBench 1.0: A benchmark dataset and evaluation metrics for data-driven land surface variables prediction Q. Li et al. 10.1016/j.eswa.2023.122917
7. The Hi-GLASS all-wave daily net radiation product: Algorithm and product validation B. Jiang et al. 10.1016/j.srs.2023.100080
8. Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data S. Li et al. 10.1080/17538947.2022.2130460
9. High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites D. Rains et al. 10.5194/essd-16-567-2024
10. Estimating Land Surface All-Wave Daily Net Radiation From VIIRS Top-of-Atmosphere Data X. Yin et al. 10.1109/LGRS.2024.3412731
11. An assessment of land energy balance over East Asia from multiple lines of evidence and the roles of the Tibet Plateau, aerosols, and clouds Q. Wang et al. 10.5194/acp-22-15867-2022
12. Recent progress on evaluating and analysing surface radiation and energy budget datasets B. Jiang et al. 10.1080/17538947.2023.2286030
13. Generating 5 km resolution 1981–2018 daily global land surface longwave radiation products from AVHRR shortwave and longwave observations using densely connected convolutional neural networks J. Xu et al. 10.1016/j.rse.2022.113223