التفاصيل البيبلوغرافية
| العنوان: |
An Operational Atmospheric Correction Framework for Multi-Source Medium-High-Resolution Remote Sensing Data of China. |
| المؤلفون: |
Zhang, Hao, Yan, Dongchuan, Zhang, Bing, Fu, Zhengwen, Li, Baipeng, Zhang, Shuning |
| المصدر: |
Remote Sensing; Nov2022, Vol. 14 Issue 21, p5590, 25p |
| مصطلحات موضوعية: |
REMOTE sensing, PARALLEL programming, CLOUD computing, REFLECTANCE |
| مصطلحات جغرافية: |
CHINA |
| مستخلص: |
Land surface reflectance (LSR) data form the basis of quantitatively remotely sensed applications. For accurate LSR retrieval, atmospheric correction has been investigated by many researchers and implemented in typical processing systems, including common atmospheric correction software for various types of datasets and automatic operating systems for application to certain individual data sources. In recent years, China has launched multiple medium–high-resolution satellites but has not provided standard LSR products partly because of the lack of an appropriate operational system. In this paper, a multi-source remote sensing LSR product system for medium- and high-resolution data is proposed, called the "Operational Atmospheric Correction Framework for multi-source Medium-high-resolution Remote Sensing data of China" (ACFrC). The AC algorithm, processing flow, and design of the multi-source LSR system were described in detail. A practical atmospheric correction algorithm was proposed specially for data in only the visible and near-infrared (VNIR) bands. The entire processing chain was divided into modules for multi-source data ingestion, apparent reflectance calculation, cloud and water identification, atmospheric correction, and standard LSR product generation. To date, most types of multi-source data have been tested using the ACFrC system, with reasonable results being obtained. From the preliminary results, the 313 scenes of LSR products from the GaoFen-2 (GF-2) satellite over China for the period from 2015 to 2018 were cross-compared with Landsat-8 LSR acquired on the same day, showing an overall uncertainty less than 0.112 × LSR + 0.0112. Further, the ACFrC data processing efficiency was found to be suitable for automatic operation. System improvement is ongoing and future refinements will include online cloud parallel computing functionality and services, more robust algorithms, and other radiometric processing functions. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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