Illumination effects on the differenced Normalized Burn Ratio's optimality for assessing fire severity. - Sander Veraverbeke; Willem W. Verstraeten; Stefaan Lhermitte; Rudi Goossens (Int. J. Appl. Earth Obs. Geoinformation, 2010)

A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT). - Sander Veraverbeke; Stefaan Lhermitte; Willem W. Verstraeten; Rudi Goossens (Int. J. Appl. Earth Obs. Geoinformation, 2011)

Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data. - Sarah Harris; Sander Veraverbeke; Simon Hook (Remote. Sens., 2011)

Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: Accounting for soil brightness variation. - Sander Veraverbeke; Ben Somers; Ioannis Z. Gitas; Thomas Katagis; Anastasia Polychronaki; Rudi Goossens (Int. J. Appl. Earth Obs. Geoinformation, 2012)

Spatio-temporal variability in remotely sensed land surface temperature, and its relationship with physiographic variables in the Russian Altay Mountains. - Ruben Van De Kerchove; Stefaan Lhermitte; Sander Veraverbeke; Rudi Goossens (Int. J. Appl. Earth Obs. Geoinformation, 2013)

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification. - Anastasia Polychronaki; Ioannis Z. Gitas; Sander Veraverbeke; Annekatrien Debien (Remote. Sens., 2013)

Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX). - Lennert Schepers; Birgen Haest; Sander Veraverbeke; Toon Spanhove; Jeroen Vanden Borre; Rudi Goossens (Remote. Sens., 2014)

Evaluating Endmember and Band Selection Techniques for Multiple Endmember Spectral Mixture Analysis using Post-Fire Imaging Spectroscopy. - Zachary Tane; Dar A. Roberts; Sander Veraverbeke; Angeles Casas; Carlos Ramirez; Susan L. Ustin (Remote. Sens., 2018)

Mapping Species at an Individual-Tree Scale in a Temperate Forest, Using Sentinel-2 Images, Airborne Laser Scanning Data, and Random Forest Classification. - Veerle Plakman; Thomas Janssen; Nienke Brouwer; Sander Veraverbeke (Remote. Sens., 2020)

Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data. - Daan van Dijk; Sorosh Shoaie; Thijs van Leeuwen; Sander Veraverbeke (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Evaluating the Differenced Normalized Burn Ratio for Assessing Fire Severity Using Sentinel-2 Imagery in Northeast Siberian Larch Forests. - Clement J. F. Delcourt; Alisha Combee; Brian Izbicki; Michelle C. Mack; Trofim Maximov; Roman Petrov; Brendan M. Rogers; Rebecca C. Scholten; Tatiana A. Shestakova; Dave van Wees; Sander Veraverbeke (Remote. Sens., 2021)

Evaluating the Near and Mid Infrared Bi-Spectral Space for Assessing Fire Severity and Comparison with the Differenced Normalized Burn Ratio. - Max J. van Gerrevink; Sander Veraverbeke (Remote. Sens., 2021)

Evaluating the Hyperspectral Sensitivity of the Differenced Normalized Burn Ratio for Assessing Fire Severity. - Max J. van Gerrevink; Sander Veraverbeke (Remote. Sens., 2021)

Forest foliage fuel load estimation from multi-sensor spatiotemporal features. - Yanxi Li 003; Rui Chen; Binbin He; Sander Veraverbeke (Int. J. Appl. Earth Obs. Geoinformation, 2022)

How Much of a Pixel Needs to Burn to Be Detected by Satellites? A Spectral Modeling Experiment Based on Ecosystem Data from Yellowstone National Park, USA. - Mats Riet; Sander Veraverbeke (Remote. Sens., 2022)

Field data synthesis accompanying "Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)". - Dave van Wees; Guido R. van der Werf; James T. Randerson; Brendan M. Rogers; Yang Chen 058; Sander Veraverbeke; Louis Giglio; Douglas C. Morton (Zenodo, 2022)

Model data for "Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)". - Dave van Wees; Guido R. van der Werf; James T. Randerson; Brendan M. Rogers; Yang Chen 058; Sander Veraverbeke; Louis Giglio; Douglas C. Morton (Zenodo, 2022)

Model code for "Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)". - Dave van Wees; Guido R. van der Werf; James T. Randerson; Brendan M. Rogers; Yang Chen 058; Sander Veraverbeke; Louis Giglio; Douglas C. Morton (Zenodo, 2022)

L-band microwave-retrieved fuel temperature predicts million-hectare-scale destructive wildfires. - Ju Hyoung Lee; Sander Veraverbeke; Brendan M. Rogers; Yann H. Kerr (Int. J. Appl. Earth Obs. Geoinformation, 2024)

Model data for "Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)". - Dave van Wees; Guido R. van der Werf; James T. Randerson; Brendan M. Rogers; Yang Chen 058; Sander Veraverbeke; Louis Giglio; Douglas C. Morton (Zenodo, 2024)

Corrigendum to "L-band microwave-retrieved fuel temperature predicts million-hectare-scale destructive wildfires" [Int. J. Appl. Earth Obs. Geoinf. 129 (2024) 103776]. - Ju Hyoung Lee; Sander Veraverbeke; Brendan M. Rogers; Yann H. Kerr (Int. J. Appl. Earth Obs. Geoinformation, 2025)