Multi-Site Cross Calibration on the LAPAN-A3/IPB Satellite Multispectral Camera with One-Dimensional Kalman Filter Optimization
Multispectral cameras on remote sensing satellites must have good radiometric quality due to their wide range of applications. One type of radiometric calibration that can be performed while the satellite is in orbit is cross-calibration. This research focuses on cross-calibration because it has adv...
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| Veröffentlicht in: | International journal of advanced computer science & applications 2024, Vol.15 (10) |
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| creator | Salaswati, Sartika Saputro, Adhi Harmoko Hasbi, Wahyudi Amin, Deddy El Hakim, Patria Rachman Fani, Silmie Vidiya Wahyudiono, Agung Anggari, Ega Asti |
| description | Multispectral cameras on remote sensing satellites must have good radiometric quality due to their wide range of applications. One type of radiometric calibration that can be performed while the satellite is in orbit is cross-calibration. This research focuses on cross-calibration because it has advantages, including being cost-effective and capable of frequent execution. We proposed a multi-site cross-calibration method with two reference cameras using six calibration sites in 2023. The LISA LAPAN-A3 (LA3) camera serves as the target camera, while the OLI LANDSAT-8 (OL8) and MSI SENTINEL-2 (MS2) cameras act as the reference cameras. The calibration process results in numerous calibration coefficients for each channel, thus requiring optimization to produce a single calibration coefficient. The optimization process uses a one-dimensional Kalman filter to reduce measurement noise. The results show that the one-dimensional Kalman filter can reduce noise in the calibration coefficient data, making LA3 radiance values closer to the reference radiance values. Additionally, this study demonstrates that LA3 calibration results with MS2 as the reference camera are better than those with OL8 as the reference. |
| doi_str_mv | 10.14569/IJACSA.2024.0151068 |
| format | Article |
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One type of radiometric calibration that can be performed while the satellite is in orbit is cross-calibration. This research focuses on cross-calibration because it has advantages, including being cost-effective and capable of frequent execution. We proposed a multi-site cross-calibration method with two reference cameras using six calibration sites in 2023. The LISA LAPAN-A3 (LA3) camera serves as the target camera, while the OLI LANDSAT-8 (OL8) and MSI SENTINEL-2 (MS2) cameras act as the reference cameras. The calibration process results in numerous calibration coefficients for each channel, thus requiring optimization to produce a single calibration coefficient. The optimization process uses a one-dimensional Kalman filter to reduce measurement noise. The results show that the one-dimensional Kalman filter can reduce noise in the calibration coefficient data, making LA3 radiance values closer to the reference radiance values. Additionally, this study demonstrates that LA3 calibration results with MS2 as the reference camera are better than those with OL8 as the reference.</description><identifier>ISSN: 2158-107X</identifier><identifier>EISSN: 2156-5570</identifier><identifier>DOI: 10.14569/IJACSA.2024.0151068</identifier><language>eng</language><publisher>West Yorkshire: Science and Information (SAI) Organization Limited</publisher><subject>Calibration ; Cameras ; Computer science ; Kalman filters ; Landsat satellites ; Noise measurement ; Optimization ; Radiance ; Remote sensing ; Satellites</subject><ispartof>International journal of advanced computer science & applications, 2024, Vol.15 (10)</ispartof><rights>2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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Additionally, this study demonstrates that LA3 calibration results with MS2 as the reference camera are better than those with OL8 as the reference.</description><subject>Calibration</subject><subject>Cameras</subject><subject>Computer science</subject><subject>Kalman filters</subject><subject>Landsat satellites</subject><subject>Noise measurement</subject><subject>Optimization</subject><subject>Radiance</subject><subject>Remote sensing</subject><subject>Satellites</subject><issn>2158-107X</issn><issn>2156-5570</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotkE1Lw0AQhoMoWGr_gYcFz2l3s8lucozRarXaQhW8hUmc0C2bD3e3iF7866Zph4EZmHfeGR7Pu2Z0ysJIJLPFU5pt0mlAg3BKWcSoiM-8UcAi4UeRpOdDH_uMyo9Lb2LtjvbBk0DEfOT9vey1U_5GOSSZaa0lGWhVGHCqbUifbotkma7TVz_ls8X6lmzAodYH_bBqOyydAd3v1WiAfCu3JasG_TtVY2N7l372DLqGhsyVdmjIqnOqVr_DiSvvogJtcXKqY-99fv-WPfrL1cMiS5d-yVgS-wGjFIUAWQlRMFZiwEOQICpkgjIaiLCUGPOQUplUiZQxSqhi-ASsCigi4GPv5ujbmfZrj9blu3Zv-t9szhlnMRcy5L0qPKrKAwqDVd4ZVYP5yRnNB9r5kXZ-oJ2faPN_gWNyuA</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Salaswati, Sartika</creator><creator>Saputro, Adhi Harmoko</creator><creator>Hasbi, Wahyudi</creator><creator>Amin, Deddy El</creator><creator>Hakim, Patria Rachman</creator><creator>Fani, Silmie Vidiya</creator><creator>Wahyudiono, Agung</creator><creator>Anggari, Ega Asti</creator><general>Science and Information (SAI) Organization Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>2024</creationdate><title>Multi-Site Cross Calibration on the LAPAN-A3/IPB Satellite Multispectral Camera with One-Dimensional Kalman Filter Optimization</title><author>Salaswati, Sartika ; 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One type of radiometric calibration that can be performed while the satellite is in orbit is cross-calibration. This research focuses on cross-calibration because it has advantages, including being cost-effective and capable of frequent execution. We proposed a multi-site cross-calibration method with two reference cameras using six calibration sites in 2023. The LISA LAPAN-A3 (LA3) camera serves as the target camera, while the OLI LANDSAT-8 (OL8) and MSI SENTINEL-2 (MS2) cameras act as the reference cameras. The calibration process results in numerous calibration coefficients for each channel, thus requiring optimization to produce a single calibration coefficient. The optimization process uses a one-dimensional Kalman filter to reduce measurement noise. The results show that the one-dimensional Kalman filter can reduce noise in the calibration coefficient data, making LA3 radiance values closer to the reference radiance values. 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| subjects | Calibration Cameras Computer science Kalman filters Landsat satellites Noise measurement Optimization Radiance Remote sensing Satellites |
| title | Multi-Site Cross Calibration on the LAPAN-A3/IPB Satellite Multispectral Camera with One-Dimensional Kalman Filter Optimization |
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