Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W4, 87-90, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2-W4/87/2015/
doi:10.5194/isprsarchives-XL-2-W4-87-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
19 Oct 2015
RETRIEVAL OF SEA SURFACE TEMPERATURE OVER POTERAN ISLAND WATER OF INDONESIA WITH LANDSAT 8 TIRS IMAGE: A PRELIMINARY ALGORITHM
M. A. Syariz1, L. M. Jaelani1, L. Subehi5, A. Pamungkas2, E. S. Koenhardono3, and A. Sulisetyono4 1Dept. of Geomatics Engineering, Faculty of Civil Engineering and Planning, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
2Dept. of Urban and Regional Planning, Faculty of Civil Engineering and Planning, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
3Dept. of Marine Engineering, Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
4Dept. of Naval Architecture and Shipbuilding Engineering, Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
5Research Centre for Limnology, Indonesian Institute of Sciences, Cibinong Science Centre, 16911, Indonesia
Keywords: Sea Surface Temperature, Algorithm, Landsat 8 TIRS, Poteran Island Water Abstract. The Sea Surface Temperature (SST) retrieval from satellites data Thus, it could provide SST data for a long time. Since, the algorithms of SST estimation by using Landsat 8 Thermal Band are sitedependence, we need to develop an applicable algorithm in Indonesian water. The aim of this research was to develop SST algorithms in the North Java Island Water. The data used are in-situ data measured on April 22, 2015 and also estimated brightness temperature data from Landsat 8 Thermal Band Image (band 10 and band 11). The algorithm was established using 45 data by assessing the relation of measured in-situ data and estimated brightness temperature. Then, the algorithm was validated by using another 40 points. The results showed that the good performance of the sea surface temperature algorithm with coefficient of determination (R2) and Root Mean Square Error (RMSE) of 0.912 and 0.028, respectively.
Conference paper (PDF, 1312 KB)


Citation: Syariz, M. A., Jaelani, L. M., Subehi, L., Pamungkas, A., Koenhardono, E. S., and Sulisetyono, A.: RETRIEVAL OF SEA SURFACE TEMPERATURE OVER POTERAN ISLAND WATER OF INDONESIA WITH LANDSAT 8 TIRS IMAGE: A PRELIMINARY ALGORITHM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W4, 87-90, doi:10.5194/isprsarchives-XL-2-W4-87-2015, 2015.

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