activity
20192025
most citedDaily Land Surface Temperature Reconstruction in Landsat Cross-Track Areas Using Deep Ensemble Learning With Uncertainty Quantification

12 citations · 23 across the 5 of their papers we have counts for

collaborators

7 papers

astro-ph.IM20252 cited

Spectroscopic study of the light-polluted night sky in Hong Kong

Chu Wing So, Chun Shing Jason Pun, Shengjie Liu

Spectroscopic study of the night sky has been a common way to assess the impacts of artificial light at night at remote astronomical observatories. However, the spectroscopic prope…

cs.CV2025

Uncertainty-Aware Hourly Air Temperature Mapping at 2 km Resolution via Physics-Guided Deep Learning

Shengjie Kris Liu, Siqin Wang, Lu Zhang

Near-surface air temperature is a key physical property of the Earth's surface. Although weather stations offer continuous monitoring and satellites provide broad spatial coverage,…

eess.IV2025

Resolution Revolution: A Physics-Guided Deep Learning Framework for Spatiotemporal Temperature Reconstruction

Shengjie Liu, Lu Zhang, Siqin Wang

Central to Earth observation is the trade-off between spatial and temporal resolution. For temperature, this is especially critical because real-world applications require high spa…

astro-ph.IM2025

Natural experiments from Earth Hour reveal urban night sky being drastically lit up by few decorative buildings

Chu Wing So, Chun Shing Jason Pun, Shengjie Liu +4

Light pollution, a typically underrecognized environmental issue, has gained attention in recent years. While controlling light pollution requires sustained efforts, Earth Hour off…

cs.CV2025

Daily Land Surface Temperature Reconstruction in Landsat Cross-Track Areas Using Deep Ensemble Learning With Uncertainty Quantification

Shengjie Liu, Siqin Wang, Lu Zhang

Many real-world applications rely on land surface temperature (LST) data at high spatiotemporal resolution. In complex urban areas, LST exhibits significant variations, fluctuating…

cs.CV2024

Deep Feature Gaussian Processes for Single-Scene Aerosol Optical Depth Reconstruction

Shengjie Liu, Lu Zhang

Remote sensing data provide a low-cost solution for large-scale monitoring of air pollution via the retrieval of aerosol optical depth (AOD), but is often limited by cloud contamin…