珠海一号高光谱数据辐射质量评价
Quality evaluation of Orbita hyperspectral images
- 2023年27卷第8期 页码:1925-1935
纸质出版日期: 2023-08-07
DOI: 10.11834/jrs.20230516
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纸质出版日期: 2023-08-07 ,
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张立福,王飒,颜军,张强,刘少杰,纪婵,刘森,童庆禧.2023.珠海一号高光谱数据辐射质量评价.遥感学报,27(8): 1925-1935
Zhang L F,Wang S,Yan J,Zhang Q,Liu S J,Ji C,Liu S and Tong Q X. 2023. Quality Evaluation of Orbita hyperspectral Images. National Remote Sensing Bulletin, 27(8):1925-1935
“珠海一号”02组和03组高光谱卫星分别于2018年4月26日和2019年9月19日发射成功。数据辐射质量评价是遥感数据应用的基础之一,针对珠海一号高光谱卫星数据,基于辐射精度、清晰度、信噪比和信息熵4个客观指标,对珠海高光谱L1B级数据辐射质量进行评价,并与GF-5高光谱遥感数据相同谱段(440—1000 nm)数据辐射质量进行对比。结果表明:GF-5高光谱数据的辐射精度和清晰度均优于珠海高光谱数据,并且珠海高光谱数据的清晰度为GF-5数据清晰度的54.5%左右;在信息熵方面,两者能力近似,均在6—10;在信噪比方面,珠海高光谱数据的信息熵为GF-5数据信息熵的86.5%左右。因此,珠海高光谱数据和GF-5高光谱数据在一定程度上可以补充使用,同时珠海高光谱数据可通过提高量化级数、降低光谱分辨率和优化传感器探元响应提高数据辐射质量。
Orbita Hyperspectral (OHS)-2 and 3 satellites were successfully launched on April 26
2018 and September 19
2019
respectively. While data quality evaluation serves as the basis of remote sensing data applications
no systematic evaluations or studies on the radiation quality evaluation of OHS have been conducted thus far.
OHS products have 32 bands
hence consuming much manpower
material resources
and time when these products are evaluated by using a subjective evaluation method. To address this problem
this study explored the use of an objective evaluation method in assessing the radiation quality of OHS level 1B images. The radiation qualities of OHS-2 and OHS-3 images were evaluated at the same time by applying the objective evaluation method on those regions covered by representative features. On the basis of four objective indexes
namely
radiation accuracy
image definition (EVA)
Signal-to-Noise Ratio (SNR)
and entropy
the radiation qualities of OHS level 1B images were evaluated
and the radiation qualities of OHS and GF-5 (440—1000 nm) images were compared.
Results show that the radiation quality and EVA of GF-5 are higher than those of OHS
the EVA of OHS is about 54.5% of that of GF-5
and the entropy of OHS ranges from 6 to 10
which is about 91.5% of that of GF-5. Meanwhile
the SNR of OHS is about 86.5% of that of GF-5. Therefore
OHS and GF-5 data can be supplemented
and the OHS can improve the data radiation quality by improving the quantitative series of spectral resolution
reducing the spectral resolution
and optimizing the sensor response.
This study provides a data quality reference for the applications of OHS images. The radiation qualities of OHS-2C and OHS-3B were evaluated by using four objective indexes
namely
radiation accuracy
EVA
SNR
and entropy. The radiation quality of GF-5 was also compared with that of OHS. Although the radiation quality of OHS is lower than that of GF-5 due to the restriction of spectral resolution and the SNR and EVA of GF-5 are obviously better than those of OHS
the entropies of OHS and GF-5 are very similar. Due to the high revisit cycle of OHS (6 days for a single-star network and 2 days for a 4-star network) and their high spatial resolution (10 m)
OHS images can complement GF-5 images to a certain degree in remote sensing applications. In the future
we plan to study the spectral quality and atmospheric correction of OHS in terms of quantitative remote sensing and water quality monitoring.
遥感珠海一号高光谱辐射精度清晰度信噪比信息熵
remote sensingOrbita hyper spectralradiation accuracyimage definitionsignal to noise ratioshannon entropy
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