Conversion study on multi-spectral information of remote sensing images GF-1 WFV, Landsat-8 OLI and Sentinel-2A MSI

YANG Tian-peng; YAN Wen-jia; ZHANG Yuan

doi:10.3969/j.issn.1000-5641.2017.06.013

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Nov. 2017

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Article Navigation > Journal of East China Normal University (Natural Sciences) > 2017 > (6): 136-146

YANG Tian-peng, YAN Wen-jia, ZHANG Yuan. Conversion study on multi-spectral information of remote sensing images GF-1 WFV, Landsat-8 OLI and Sentinel-2A MSI[J]. Journal of East China Normal University (Natural Sciences), 2017, (6): 136-146. doi: 10.3969/j.issn.1000-5641.2017.06.013

Citation:

YANG Tian-peng, YAN Wen-jia, ZHANG Yuan. Conversion study on multi-spectral information of remote sensing images GF-1 WFV, Landsat-8 OLI and Sentinel-2A MSI[J]. Journal of East China Normal University (Natural Sciences), 2017, (6): 136-146. doi: 10.3969/j.issn.1000-5641.2017.06.013

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Conversion study on multi-spectral information of remote sensing images GF-1 WFV, Landsat-8 OLI and Sentinel-2A MSI

doi: 10.3969/j.issn.1000-5641.2017.06.013

YANG Tian-peng^{1,2
,},
YAN Wen-jia^1,2,
ZHANG Yuan^{1,2
,
,}

1.
Key Laboratory of Geographic Information Science(Ministry of Education), East China Normal University, Shanghai 200241, China
2.
School of Geographic Sciences, East China Normal University, Shanghai 200241, China

Received Date: 2017-01-13
Publish Date: 2017-11-25

Abstract

Abstract

Owing to the restrictions in weather conditions and revisit cycle of satellites, single satellite can't successively acquire effective optical RS data for long-term monitoring the terrestrial environments. Therefore, it is crucial important to analyze the multi-spectral information of multi-source RS data. In this study, two groups of clear RS images (GF-1 and Landsat-8, GF-1 and Sentinel-2A), in along with ground survey data, were respectively acquired on identical date. Four bands, blue, green, red and near infrared (NIR), were selected to compare their spectral characteristics. At the same time, conversion equation for reflectance of four corresponding spectral bands was derived respectively via statistical regression method. The result shows that each pair of bands in the two comparing groups has a strong correlation. And, these conversion equations can effectively converse spectral information in between each band of two comparing groups with a better precision. This study provides a useful technological approach for the identical date information integration and syngeneic application of multi-spectral RS data from the same day, as well as quantitatively monitoring the long-term dynamics in environments and resources at regional scale.
- GF-1,
- Landsat-8,
- Sentinel-2A,
- remote sensing,
- sensor,
- reflectance,
- conversion equation

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References(13)

References

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