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Comparison of Some Split-window Algorithms to Estimate Land Surface Temperature from AVHRR Data in Southeastern Tehran, Iran.
- Source :
-
Desert (2008-0875) . Dec2009, Vol. 14 Issue 2, p157-161. 5p. 2 Charts, 2 Graphs. - Publication Year :
- 2009
-
Abstract
- Land surface temperature (LST) is a significant parameter for many applications. Many studies have proposed various algorithms, such as the split-window method, for retrieving surface temperatures from two spectrally adjacent thermal infrared bands of satellite data. Each algorithm is developed for a limited study area and application. In this paper, as part of developing an optimal split-window method in the southeast of Tehran province, Iran, four commonly applied algorithms to retrieve the LST from AVHRR were compared. This study was carried out in a wheat farm site located in the Pakdasht Agricultural Region. Measurements of LST over the farm were made with a manual infrared radiometer at the time of NOAA overpass for 18 days of May to June 2004. These days were cloud free over the study area. A total of 18 NOAA images were acquired for the days that LST measurements were made. The temperatures derived by the different split-window algorithms were compared to ground truth measurements. The performance of the split window algorithms was checked with three statistical indices: root mean square error (RMSE), mean bias error (MBE) and coefficient of determination (R2). The results showed that the Ulivieri split-window algorithm produced the lowest value of RMSE and MBE (2.71 and 0.26 K, respectively) and its highest value of R2 (0.92) gave more accurate results than the other algorithms. [ABSTRACT FROM AUTHOR]
- Subjects :
- *TEMPERATURE
*ALGORITHMS
*WHEAT
*FARMS
*RADIOMETERS
*ERRORS
*ALGEBRA
Subjects
Details
- Language :
- English
- ISSN :
- 20080875
- Volume :
- 14
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Desert (2008-0875)
- Publication Type :
- Academic Journal
- Accession number :
- 48995992