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...

Remote sensing-based prediction of forest fire characteristics

Forest fires are a major ecosystem disturbance at global scale, put pressure on agencies in charge of citizens and infrastructure security and cause unvaluable human losses. Fires are controlled by multiple static and dynamic drivers related to topography, land cover, climate, weather, and anthropic activity. Among these, weather is an active...

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...

Relating spatiotemporal patterns of forest fires burned area and duration to diurnal land surface temperature anomalies

Forest fires are a major source of ecosystem disturbance. Vegetation reacts to meteorological factors contributing to fire danger by reducing stomatal conductance, thus leading to an increase of canopy temperature. The latter can be detected by remote sensing measurements in the thermal infrared as a deviation of observed land surface...

Reconstruction of gap-free time series satellite observations of land surface temperature to model spectral soil thermal admittance

The soil thermal properties (soil thermal conductivity, soil heat capacity and soil diffusivity) are the main parameters in the applications that need quantitative information on soil heat transfer. Conventionally, these properties are either measured in situ or estimated by semi-empirical models using the fractions of soil constituents. The use...