Impacts of spectral band difference effects on radiometric cross-calibration between satellite sensors in the solar-reflective spectral domain

By P. Teillet, G. Fedosejevs, K. Thome, J. Barker. 2007

160 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/2baf5798fcbe9753c2303e6dd40e1bf91ab0c930

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. David P. Roy
2. Crystal Barker Schaaf
3. Hankui K. Zhang
4. Philip Lewis
5. Wolfgang Lucht

In Atmospheric Science

1. Crystal Barker Schaaf
2. David P. Roy
3. Jian Li
4. Philip Lewis
5. Wolfgang Lucht

In Global and Planetary Change

1. David P. Roy
2. Crystal Barker Schaaf
3. Matthew C. Hansen
4. Hankui K. Zhang
5. Philip Lewis
6. Zhe Zhu
7. Wolfgang Lucht

Citations in the corpus

• Examination of Sentinel-2A Multi-spectral Instrument (MSI) Reflectance Anisotropy and the Suitability of a General Method to Normalize MSI Reflectance to Nadir BRDF Adjusted Reflectance (2017, background): “Third, although the Sentinel-2A and MODIS bands have similar central wavelengths their bandwidths are not the same (Table 1) and it is established that reflectance derived from sensors with different bandwidths is usually different (Steven et al., 2003; Teillet et al., 2007).”
• Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data (2008, methodology): “The method is applicable to any high spatial resolution satellite data, provided the wavelengths considered, specifically the spectral response functions ( Teillet et al., 2007 ), are similar to those available from the MODIS instruments; further research work is required to quantify the impact of s”