Split-Window LST Algorithms Estimation From AVHRR/NOAA Satellites (7, 9, 11, 12, 14, 15, 16, 17, 18, 19) Using Gaussian Filter Function

Autor: Nizar Ben Achhab, Mohammed Lahraoua, Naoufal Raissouni, Asaad Chahboun, Abdelilah Azyat
Rok vydání: 2012
Předmět:
Zdroj: International Journal of Information and Network Security (IJINS). 2
ISSN: 2089-3299
DOI: 10.11591/ijins.v2i1.1502
Popis: A study has been carried out using MODTRAN 4.0 radiative transfer code simulations to calculate the brightness temperatures expected at the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration NOAA satellites series (7, 9, 11, 12, 14, 15, 16, 17, 18 and 19) by using Gaussian Referential Filter (GRF) and Gaussian Filter (GF) instead of filter Normalized Filter obtained from NOAA agency. The outputs of applying MODTRAN 4.0 are values of atmospheric parameters obtained by mathematical convolution using GRF and GF Filters. A detailed analysis of the total error in LST, d Total(Ts) , in function of AVHRR/NOAA satellites, shows that the algorithms are able to estimate accurate LST between a minimum of 1.256 K and a maximum of 1.415 K with amplitude of about 0.159 K. The validations show also that the algorithms are capable to produce LST with a standard deviation lower than 1.554 K and a Root Mean Square Error (RMSE) lower than 1.558 K. This result gives the opportunity to use the filter GF instead of filter Normalized Filter obtained from NOAA agency, in other studies by creation of GF filters centered in any region of the electromagnetic.
Databáze: OpenAIRE