fadila muchsin, Liana Fibriawati, Kuncoro Adhi Pradhono


Three methods of atmospheric correction, Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) and the model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), have been applied to the level 1T Landsat-7 image Jakarta area. The atmospheric corrected image is then compared with the TOA reflectance image. The results show that there is an improvement of the spectral pattern on the TOA reflectance image by the decrease of the reflectance value of each object by (1 - 11) % after the atmospheric correction of all models for visible bands (blue, green and red). In the NIR and SWIR bands there is an increase in the spectral value of about 1% to the TOA reflectance on all objects except wetland for the LEDAPS model. The percentage of the increase and the decrease in spectral values of 6S and FLAASH models have the same tendency. Analyzes were also performed on the NDVI values of each model, where NDVI values were relatively higher after atmospheric correction. The NDVI value of rice crop on FLAASH model is the same as 6S model that is equal to 0.95 and for wetland, it has the same value between FLAASH model and LEDAPS which is 0.23. NDVI value of entire scene for FLAASH model = 0.63, LEDAPS model = 0.56 and 6S model = 0.66. Before the atmospheric correction, the TOA is 0.45.



Tiga metode koreksi atmosfer diantaranya  Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) dan model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) telah diterapkan pada citra Landsat-7 level 1T wilayah Jakarta. Citra yang telah terkoreksi atmosfer dibandingkan dengan citra reflektan TOA. Hasilnya menunjukkan bahwa terdapat perbaikan pola spektral pada citra reflektan TOA dengan adanya penurunan nilai reflektan setiap obyek sebesar (1 – 11) % setelah dilakukan koreksi atmosfer pada semua model untuk kanal-kanal visible (blue, green dan red). Pada kanal NIR dan SWIR terjadi kenaikan nilai spektral yaitu sekitar 1% terhadap reflektan TOA pada semua objek terkecuali objek lahan basah untuk model LEDAPS. Persentase kenaikan dan penurunan nilai spektral model 6S dan FLAASH memiliki kecenderungan yang sama. Analisis juga dilakukan terhadap nilai NDVI masing-masing model, dimana nilai NDVI relatif lebih tinggi setelah koreksi atmosfer. Nilai NDVI tanaman padi pada model FLAASH sama dengan model 6S yaitu sebesar 0.95 dan untuk lahan basah memiliki nilai yang sama antara model FLAASH dan LEDAPS yaitu 0.23. Nilai NDVI seluruh scene untuk model FLAASH = 0.63, model LEDAPS = 0.56 dan model 6S = 0.66. Sebelum koreksi atmosfer (TOA) adalah 0.45. 


koreksi atmosfer; FLAASH; 6S; LEDAPS; pola spektral; NDVI; atmospheric correction; spectral profile

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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 Sensing of Environment (113): 893 – 903.

ENVI, 2009. Atmospheric Correction Module: QUAC and FLAASH User’s Guide, ITT Visual Information Solutions.

Hadjimitsis, D.G., Papadavid, G., Agapiou, A., Themistocleous, K., Hadjimitsis, M.G., Retalis, A., Michaelides, S., Chrysoulakis, N., Toulious, L., Clayton, C.R.I., 2010. Atmospheris Correction for Satellite Remote Sensed Data Intended for Agricultural Application: Impact on Vegetation Indeces, Natural Hazards and Earth System Sciences (10): 89 – 95.

Kaufman, Y.J., Wald, A.E., Remer, L.A., Gao, B-C., Li, R-R., Flyn, L., 1997. The MODIS 2.1- m Channel—Correlation with Visible Reflectance for Use in Remote Sensing of Aerosol. IEEE Transaction on Geoscience and Remote Sensing 35 (5):1286-1298.

Mahiny, A.S., Turner B.J., 2007. A Comparison of Four Common Atmospheric Correction Methods, Photogramterric Engineering and Remote Sensing, Vol. 73, No.4, April 2007, 361-368.

Mathew, M.W., Adler-Golden, S.M., Berk, A., Felde, G., Anderson, G.P., Gorodetsky, D., Paswaters, S., Shippert, M., 2003. Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data, Spectral Sciences, Inc.

NASA, 2016. Landsat 7 Science Data User Handbook, National Aeronautics and Space Administration, USA.

Schmidt, G., Jenkerson, C., Masek, J., Vermote, E., Gao, F., 2013. Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) Algoritm Description, Open-File Report, U.S. Geological Survey.

Teillet, P.M., Barker, J.L., Markham, B.L., Irish, R.R., Fedosejevs G., 2001. Radiometric Cross-Calibration of the Landsat-7 ETM+ and Landsat-5 TM Sensors Based on Tandem Data Sets, Remote Sensing of Environment, Vol. 78 (39 -54).

Vermote, E.F., and Saleous, N., 2007. LEDAPS Surface Reflectance Product Description version 2.0. Technical Document, Departement of Geography, University of Maryland. USA.

Vermote, E.F., El Saleous, N.Z., Justice, C.O., 2002. Atmospheric Correction of MODIS data in Visible to Middle infrared: First Result, Remote Sensing of Environment, Vol. 83 (97 – 111).

Vermote, E.F., Tanre, D., Deuze, J.L., Herman, M., Morcrette, J-J., 1997. Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An Overview, IEE Transaction on Geoscience and Remote Sensing, Vol. 35, No. 3, May 1997, 875– 686.


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