Modelling and Remote Sensing of Land Surface Temperature in Turkey
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Date
2012
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26-45A degrees E and 36-42A degrees N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, EskiAYehir, A degrees stanbul, A degrees zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LSTANN) and Becker and Li temperature(LSTB-L) method values have been found as 0.077 K and 0.091 K (training stations), 0.045 K and 0.003 K (testing stations), respectively.
Description
Keywords
Generalized regression neural network, Land surface temperature, Satellite data
Journal or Series
Journal of The Indian Society of Remote Sensing
WoS Q Value
Q4
Scopus Q Value
Q1
Volume
40
Issue
3
