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。