Publikationen, an denen er mitarbeitet JOCHEM VERRELST - (16)

2024

  1. In-season forecasting of within-field grain yield from Sentinel-2 time series data

    International Journal of Applied Earth Observation and Geoinformation, Vol. 126

  2. Inferring global terrestrial carbon fluxes from the synergy of Sentinel 3 & 5P with Gaussian process hybrid models

    Remote Sensing of Environment, Vol. 305

2022

  1. Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data

    Remote Sensing of Environment, Vol. 273

  2. Monitoring cropland phenology on google earth engine using gaussian process regression

    Remote Sensing, Vol. 14, Núm. 1

  3. Multi-Season Phenology Mapping of Nile Delta Croplands Using Time Series of Sentinel-2 and Landsat 8 Green LAI

    Remote Sensing, Vol. 14, Núm. 8

  4. Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

    Remote Sensing, Vol. 14, Núm. 6

  5. Trends in Satellite Sensors and Image Time Series Processing Methods for Crop Phenology Monitoring

    Springer Optimization and Its Applications (Springer), pp. 199-231

2021

  1. CROP PHENOLOGY RETRIEVAL THROUGH GAUSSIAN PROCESS REGRESSION

    International Geoscience and Remote Sensing Symposium (IGARSS)

  2. Green lai mapping and cloud gap-filling using gaussian process regression in google earth engine

    Remote Sensing, Vol. 13, Núm. 3

  3. MAPPING ESSENTIAL VEGETATION VARIABLES OVER EUROPE USING GAUSSIAN PROCESS REGRESSION AND SENTINEL-3 DATA IN GOOGLE EARTH ENGINE

    International Geoscience and Remote Sensing Symposium (IGARSS)

  4. Prototyping Sentinel-2 green LAI and brown LAI products for cropland monitoring

    Remote Sensing of Environment, Vol. 255

  5. Retrieving and validating leaf and canopy chlorophyll content at moderate resolution: A multiscale analysis with the sentinel-3 olci sensor

    Remote Sensing, Vol. 13, Núm. 8

2020

  1. DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection

    Environmental Modelling and Software, Vol. 127

  2. Optimizing Gaussian process regression for image time series gap-filling and crop monitoring

    Agronomy, Vol. 10, Núm. 5

  3. Quantifying vegetation biophysical variables from the Sentinel-3/FLEX tandem mission: Evaluation of the synergy of OLCI and FLORIS data sources

    Remote Sensing of Environment, Vol. 251

2019

  1. Fusing optical and SAR time series for LAI gap fillingwith multioutput Gaussian processes

    Remote Sensing of Environment, Vol. 235