Test to build a program to adjust the effect of terrain on satellite images - case for Landsat-8 imagery on the Google Earth Engine platform
Keywords:
Terrain correction,, Google Earth Engine,, landsat-8,, SRTM DEMAbstract
Adjusting terrain on a satellite image is adjusting of the spectral reflection value of the image channel in the areas affected by the terrain shadow caused by the slope and lighting conditions of the sun. In this study, the authors inherited and analyzed models commonly applied to adjust the terrain on satellite imagery from which to select representative models to build a program to adjust through programming on Google Earth Engine. The programs were developed to test to adjust Landsat-8 images in Lak district, Dak Lak province. Adjusting results by different models were compared by visualized analysis and statistical analysis in order to select a suitable model for terrain adjusting in the area. The results have selected 4 models, including: cosine model, C model, solar sensor model (SCS) + C and experimental model to test and build an adjusting program, in which the experimental model was evaluated as the most suitable for adjusting the terrain in the area, the second one is model C or model (SCS) + C. Using the adjusting program built by experimental models to adjust the terrain on Landsat-8 images in Cao Phong District, Hoa Binh Province; Ba Che district, Quang Ninh province; Nhu Thanh district, Thanh Hoa province; Tan Phu district, Dong Nai province showed relatively suitable adjusting results allowing the application of this adjusting program to adjust the terrain on Landsat-8 images in Vietnam.
References
1. Asner, G.P, 2003. Canopy shadow in IKONOS satellite observations of tropical forests and savannas. Remote Sens. Environ, 87, 521-533.
2. Chander, G.; Markham, B.L.; Helder, D.L, 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM + , and EO-1 ALI sensors. Remote Sens. Environ, 113, 893-903.
3. Gao, Y.N.; Zhang, W.C, 2009. A simple empirical topographic correction method for ETM + imagery. Int. J. Remote Sens, 20, 2259-2275.
4. Gu, D.; Gillespie, A, 1998. Topographic normalization of Landsat TM images of forest based on subpixel SunCanopy-Sensor geometry. Remote Sens. Environ, 64, 166-175.
5. Hantson, S.; Chuvieco, E, 2011. Evaluation of different topographic correction methods for Landsat imagery. Int. J. Appl. Earth Obs, 13, 691-700.
6. Irons, J.R; Dwyer, J.L; Barsi, J.A, 2012. The next Landsat satellite: The Landsat data continuity mission. RemoteSens. Environ, 122, 11-21.
7. Li, F.Q.; David, L.B.; Jupp, M.T.; Leo, L.; Norman, M.; Lewis, A.; Held, A, 2012. A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sens. Environ, 124, 756-770.
8. Pimple, U.; Sitthi, A.; Simonetti, D.; Pungkul, S.; Leadprathom, K.; Chidthaisong, A, 2017. Topographic correction of Landsat TM-5 and Landsat OLI-8 imagery to improve the performance of forest classification in the mountainous terrain of Northeast Thailand. Sustainability, , 9, 258.
9. Soenen, S.A; Peddle, D.R; Coburn, C.A; Hall, R.J; Hall, F.G, 2008. Improved topographic correction of forest image data using a 3-D canopy reflectance model in multiple forward mode. Int. J. Remote Sens. 2008, No 29, pp 1007-1027.
10. Soenen, S.A.; Peddle, D.R.; Coburn, C.A. SCS + C, 2005. A modified Sun-Canopy-Sensor topographic correction in forested terrain. IEEE Trans. Geosci. Remote Sens, 43, 2148-2159.
12. Szantoi, Z.; Simonetti, D, 2013. Fast and robust topographic correction method for medium resolution satellite imagery using a stratified approach. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens, 6, 1921-1932.
13. Tan, B.; Jeffrey, G.; Masek, R.W.; Gao, F.; Huang, C.; Eric, F.; Vermote, J.; Sexton, O.; Ederer, G, 2013. Improved forest change detection with terrain illumination corrected Landsat images. Remote Sens. Environ, 136, 469-483.
14. Teillet, P.M.; Guindon, B.; Goodenough, D.G, 1982. On the slope-aspect correction of multispectral scanner data. Can. J. Remote Sens, 8, 84-106.
15. Vanonckelen, S.; Lhermitte, S.; Ronpaey, A.V, 2013. The effect of atmospheric and topographic correction methods on land cover classification accuracy. Int. J. Appl. Earth Obs, 24, 9-21.