RSR Calculator, a tool for the Calibration / Validation activities

Authors

  • C. Durán-Alarcón Universidad de Chile
  • A. Santamaría-Artigas Universidad de Chile
  • N. Valenzuela Universidad de Chile
  • C. Mattar Universidad de Chile

DOI:

https://doi.org/10.4995/raet.2014.3230

Keywords:

RSR Calculator, spectral signatures, convolution, wavelength, Relative Spectral Response

Abstract

The calibration/validation of remote sensing products is a key step that needs to be done before its use in different kinds of environmental applications and to ensure the success of remote sensing missions. In order to compare the measurements from remote sensors on spacecrafts and airborne platforms with in-situ data, it is necessary to perform a spectral comparison process that takes into account the relative spectral response of the sensors. This technical note presents the RSR Calculator, a new tool to estimate, through numerical convolution, the values corresponding to each spectral range of a given sensor. RSR Calculator is useful for several applications ranging from the convolution of spectral signatures of laboratory or field measurements to the parameter estimation for the calibration of sensors, such as extraterrestrial solar irradiance (ESUN) or atmospheric transmissivity (τ) per spectral band. RSR Calculator is a useful tool that allows the processing of spectral data and that it can be successfully applied in the calibration/validation remote sensing process of the optical domain.

Downloads

Download data is not yet available.

Author Biographies

C. Durán-Alarcón, Universidad de Chile

Laboratorio para el Análisis para la Biósfera (LAB), Departamento de Ciencias Ambientales y Recursos Naturales Renovables, Universidad de Chile

A. Santamaría-Artigas, Universidad de Chile

Laboratorio para el Análisis para la Biósfera (LAB), Departamento de Ciencias Ambientales y Recursos Naturales Renovables, Universidad de Chile

N. Valenzuela, Universidad de Chile

Laboratorio para el Análisis para la Biósfera (LAB), Departamento de Ciencias Ambientales y Recursos Naturales Renovables, Universidad de Chile

C. Mattar, Universidad de Chile

Laboratorio para el Análisis para la Biósfera (LAB), Departamento de Ciencias Ambientales y Recursos Naturales Renovables, Universidad de Chile

References

Baldridge, A.M., Hook, S.J., Grove, C.I., Rivera, G. 2009. The ASTER Spectral Library Version 2.0. Remote Sensing of Environment, 113(4): 711-715.http://dx.doi.org/10.1016/j.rse.2008.11.007

Barsi, J.A., Barker, J.L., Schott, J.R. 2003. An Atmospheric Correction Parameter Calculator for a Single Thermal Band Earth-Sensing Instrument. En:Proceedings of IEEE International Geoscience and Remote Sensing Symposium, 21-25 July. Toulouse, France.

Berk, A., Anderson, G.P., Acharya, P.K., Chetwynd, J.H., Bernstein, L.S., Shettle, E.P., Matthew, M.W., Adlergolden, S.M. 1999, MODTRAN4 User’s Manual. Air Force Research Laboratory, Space Vehicles Directorate, Hanscom AFB, MA 01731-3010.

Chander, G., Markham, B., Helder, D.L. 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5): 893-903.

http://dx.doi.org/10.1016/j.rse.2009.01.007

Liang, S. 2004. Quantitative Remote Sensing of Land Surfaces. New Jersey: John Wiley & Sons. Mattar, C., Santamaría-Artigas, A., Durán-Alarcón, C., Olivera-Guerra, L., Fuster, R. 2014. LAB-net the first Chilean soil moisture network for remote sensing applications. En: Proccedings of the IV Recent Advances in Quantitative Remote Sensing, 22-26 September. Torrent, Spain.

Neckel, H., Labs, D. 1984. The solar radiation between 3300 and 12500 Å. Solar Physics, 90(2): 205-258. http://dx.doi.org/10.1007/BF00173953

Rossow, W.B., Kinsella, E., Wolf, A., Gardner, L. 1985. Description of reduced resolution radiance data. WCRP/ISCCP, WMO/TD No. 58, 132 pp.

Santamaría-Artigas A, Aros, D., Olivera-Guerra, O., Durán-Alarcón, C., Mattar, C. 2013. Primera caracterización espectral de Calandrinia grandiflora. III Congreso de Flora Nativa, 5-7 de Septiembre. Santiago, Chile.

Teillet, P.M., Staenz, K., Williams, D.J. 1997. Effects of spectral, spatial, and radiometric characteristics of remote sensing vegetation indices of forested regions. Remote Sensing of Environment, 61(1): 139-149.

http://dx.doi.org/10.1016/S0034-4257(96)00248-9

Thuillier, G., Hersé, M., Simon, P.C., Labs, D., Mandel, H., Gillotay, D., Foujols, T. 1998. The visible solar spectral irradiance from 350 to 850 nm as measured by the SOLSPEC spectrometer during ATLAS I Mission. Solar Physics, 177(1-2): 41-61. http://dx.doi.org/10.1023/A:1004953215589

Thuillier, G., Hersé, M., Labs, S., Foujols, T., Peetermans, W., Gillotay, D., Simon, P.C., Mandel H. 2003. The solar spectral irradiance from 200 to 2400 nm as measured by SOLSPEC Spectrometer from the ATLAS and EURECA missions. Solar Physics, 214(1): 1-22. http://dx.doi.org/10.1023/A:1024048429145

Wehrli, C. 1985. Extraterrestrial Solar Spectrum. WRC Pub. 615.

Published

2014-12-16

Issue

Section

Practical cases