A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform

Spatiotemporal residual noise in terrestrial earth observation products, often caused by unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to use gap-filled remote sensing products with time series reconstruction (TSR) algorithms. Applying currently available implementations of TSR to large-volume...

Lanthanide-Doped Nanoprobes as Orthogonal NIR-II Fluorescence Channels for In Vivo Information Storage

Information storage in vivo will lead to next-generation identification and security authentication. Here, an information storage method was proposed for in vivo application by using a pair of lanthanide-doped nanoprobes (NdNPs and ErNPs) with orthogonal emissions in the second near-infrared window. The information is stored in different...

Quantifying the Uncertainty of Short-Term Vegetation Anomalies Detection Using Eo-Based Coarse-Resolution Vegetation Products

Satellite-based Earth Observation systems archived a variety of vegetation products during the last 50 years, which can reveal regional to global ecosystem dynamics across diverse spatiotemporal scales. The anomaly metrics such as Vegetation Condition Index (VCI) defined by comparing the current vegetation growth condition to historical...

Optimal Estimate of Global Biome: Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method

Terrestrial remote sensing data products retrieved from radiometric measurements in the optical and thermal infrared spectrum such as vegetation spectral indices can be heavily contaminated by atmospheric conditions, including cloud and aerosol layers. This contamination results in gaps or noisy observations. The harmonic analysis of time series...