利用高分五号AHSI 载荷的高分辨率XCH4 异常探测方法研究

大气与环境光学学报 ›› 2022, Vol. 17 ›› Issue (6): 670-678.

• “新型卫星载荷大气遥感及应用” 专辑 • 上一篇下一篇

利用高分五号AHSI 载荷的高分辨率XCH4 异常探测方法研究

杨可意1;2, 韩舸1∗, 毛慧琴3, 董燕妮2, 马昕4, 李四维1, 龚威5

1 武汉大学遥感信息工程学院, 湖北武汉430079; 2 中国地质大学(武汉) 地球物理与空间信息学院, 湖北武汉430074; 3 生态环境部卫星环境应用中心, 北京100094; 4 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉430079; 5 武汉大学电子信息学院, 湖北武汉430079

收稿日期:2022-05-23 修回日期:2022-07-31 出版日期:2022-11-28 发布日期:2022-12-14
通讯作者: E-mail: udhan@whu.edu.cn E-mail:udhan@whu.edu.cn
作者简介:杨可意(2000 - ), 内蒙古巴彦淖尔人, 硕士研究生, 主要从事温室气体遥感反演方面的研究。E-mail: yangky@cug.edu.cn
基金资助:
Supported by National Natural Science Foundation of China (国家自然科学基金, 41971283, 41801261, 41827801, 4191274, 41971352)

High-resolution XCH4 anomaly detection method using GF-5 AHSI payload

YANG Keyi1;2, HAN Ge1∗, MAO Huiqin3, DONG Yanni2, MA Xin4, LI Siwei1, GONG Wei5

1 School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; 2 Institute of Geophysics & Geomatics, China University of Geosciences (Wuhan), Wuhan 430074, China; 3 Satellite Application Center for Ecology and Environment, Beijing 100094, China; 4 State Key Laboratory of Information Engineering in Surveying , Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China; 5 Electronic Information School, Wuhan University, Wuhan 430079, China

Received:2022-05-23 Revised:2022-07-31 Published:2022-11-28 Online:2022-12-14

摘要/Abstract

摘要： 煤矿开采是最重要的甲烷排放源, 然而其排放清单的准确性很低, 一个关键的原因在于缺乏精准识别和定位该类排放源的能力。近年来, 前沿研究表明可以利用卫星高光谱数据反演高分辨率的甲烷异常, 从而帮助识别排放源。但是, 在地表类型复杂地区该算法会完全失效。针对这一问题, 率先提出一种基于L1 重加权和迭代收缩阈值算法(ISTA) 匹配滤波器的算法。利用高分五号(GF-5) 数据在山西地区的实验表明, 该方法性能显著优于现有的其他方法。实验中, 本方法识别出23 个甲烷强点源, 这些点源全部位于TROPOMI 的甲烷高值区内, 且高分辨遥感影像显示这些点源处存在典型的煤矿开采设施。该方法的提出为利用GF-5 卫星数据在世界范围实现甲烷点源排查奠定了技术基础。

关键词: 甲烷柱浓度异常探测, 基于L1 重加权和迭代收缩阈值算法的匹配滤波器算法, 高分五号可见光短波红外高光谱相机数据

Abstract: Coal mining is the most important methane emission source, yet a key reason for the low accuracy of its emission inventories is the lack of capability to accurately identify and locate this type of emission source. In recent years, cutting-edge research has shown that it is possible to use satellite hyperspectral data to invert high-resolution methane anomalies and thus help to identify emission sources. However, this algorithm will fail completely in areas with complex surface types. To address this problem, the paper proposes the L1 reweighted iterative shrinkage thresholding algorithm (ISTA) matched filter algorithm for the first time. Experiments in Shanxi region using GF- 5 advanced hyperspectral imager (AHSI) data show that the performance of the modified method is significantly better than that of the other existing methods. In the experiments, this method identifies 23 strong methane point sources, all of which are located in the methane high value area of TROPOMI, and the high-resolution remote sensing images also show the presence of typical coal mining facilities at these point sources. This method has laid a technical foundation for the worldwide implementation of methane point source identification using GF-5 AHSI data.

Key words: XCH4 anomaly detection, L1 reweighted iterative shrinkage thresholding algorithm matched filter; GF-5 visible-shortwave infrared advanced hyperspectral imager data

中图分类号:

杨可意, 韩舸∗, 毛慧琴, 董燕妮, 马昕, 李四维, 龚威. 利用高分五号AHSI 载荷的高分辨率XCH4 异常探测方法研究[J]. 大气与环境光学学报, 2022, 17(6): 670-678.

YANG Keyi, HAN Ge∗, MAO Huiqin, DONG Yanni, MA Xin, LI Siwei, GONG Wei. High-resolution XCH4 anomaly detection method using GF-5 AHSI payload[J]. Journal of Atmospheric and Environmental Optics, 2022, 17(6): 670-678.

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利用高分五号AHSI 载荷的高分辨率XCH4 异常探测方法研究

High-resolution XCH4 anomaly detection method using GF-5 AHSI payload

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