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PACO：基于Python的大气校正

PACO: Python-Based Atmospheric COrrection.

作者信息

de Los Reyes Raquel, Langheinrich Maximilian, Schwind Peter, Richter Rudolf, Pflug Bringfried, Bachmann Martin, Müller Rupert, Carmona Emiliano, Zekoll Viktoria, Reinartz Peter

机构信息

German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Photogrammetry and Image Analysis, Oberpfaffenhofen, 82234 Wessling, Germany.

German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Photogrammetry and Image Analysis, 12489 Berlin, Germany.

出版信息

Sensors (Basel). 2020 Mar 5;20(5):1428. doi: 10.3390/s20051428.

DOI:10.3390/s20051428
PMID:32151105
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7085641/
Abstract

The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric correction software, capable of processing data acquired by many different optical satellite sensors. Based on this well established algorithm, a new Python-based atmospheric correction software has been developed to generate L2A products of Sentinel-2, Landsat-8, and of new space-based hyperspectral sensors such as DESIS (DLR Earth Sensing Imaging Spectrometer) and EnMAP (Environmental Mapping and Analysis Program). This paper outlines the underlying algorithms of PACO, and presents the validation results by comparing L2A products generated from Sentinel-2 L1C images with in situ (AERONET and RadCalNet) data within VNIR-SWIR spectral wavelengths range.

摘要

基于辐射传输计算的卫星图像大气校正是许多遥感应用的前提条件。德国航空航天中心（DLR）开发的软件包ATCOR是一款多功能大气校正软件，能够处理许多不同光学卫星传感器获取的数据。基于这一成熟的算法，已开发出一种基于Python的新型大气校正软件，用于生成哨兵-2号、陆地卫星-8号以及诸如DESIS（DLR地球传感成像光谱仪）和EnMAP（环境制图与分析计划）等新型天基高光谱传感器的L2A产品。本文概述了PACO的基础算法，并通过比较哨兵-2号L1C图像在可见光-近红外-短波红外光谱波长范围内生成的L2A产品与现场（AERONET和RadCalNet）数据，展示了验证结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/90ed0139556f/sensors-20-01428-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/f1b431cf31c5/sensors-20-01428-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/173e5db920b8/sensors-20-01428-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/65b805f8fc94/sensors-20-01428-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/faf8a4c23079/sensors-20-01428-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/85d76d87dff2/sensors-20-01428-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/0e07c8ff8ccf/sensors-20-01428-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/353b1e146778/sensors-20-01428-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/90ed0139556f/sensors-20-01428-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/f1b431cf31c5/sensors-20-01428-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/173e5db920b8/sensors-20-01428-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/65b805f8fc94/sensors-20-01428-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/faf8a4c23079/sensors-20-01428-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/85d76d87dff2/sensors-20-01428-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/0e07c8ff8ccf/sensors-20-01428-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/353b1e146778/sensors-20-01428-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4450/7085641/90ed0139556f/sensors-20-01428-g008.jpg

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本文引用的文献

1
Atmospheric Correction Inter-comparison eXercise.大气校正相互比较实验
Remote Sens (Basel). 2018 Feb;10(2):352. doi: 10.3390/rs10020352. Epub 2018 Feb 24.
2
A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring.一个长达30多年的高级甚高分辨率辐射计陆地表面反射率气候数据记录及其在小麦产量监测中的应用。
Remote Sens (Basel). 2017 Mar 21;Volume 9(Iss 3). doi: 10.3390/rs9030296.
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Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS).数据产品，DLR 地球感应成像光谱仪（DESIS）的质量和验证。
Sensors (Basel). 2019 Oct 15;19(20):4471. doi: 10.3390/s19204471.
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Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space.用于从太空对海洋颜色进行高光谱遥感的大气校正算法。
Appl Opt. 2000 Feb 20;39(6):887-96. doi: 10.1364/ao.39.000887.
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