@inproceedings{508165b8a6e74f568dd67fadf5acb03f,
title = "Remote sensing inversion of PM10 based on spark platform",
abstract = "With the continuous growth of remote sensing data and the application of fast and effective atmosphere remote sensing inversion algorithm, this paper proposes a PM10 fast inversion approach based on Spark platform which uses Apache Spark as the analytics engine and integrates with the traditional atmospheric remote sensing inversion algorithm. We first store aerosol data which is MYD04_3K from NASA into HDFS. Then the inversion algorithm is combined with Spark via the function interface to realise rapid atmospheric remote sensing inversion. The experimental results based on Spark platform are compared with those obtained from the traditional physical hardware. The results prove that the proposed atmospheric remote sensing inversion method based on Spark has high efficiency.",
keywords = "Atmospheric remote sensing inversion, big data, HDFS, Spark",
author = "Zhenyu Yu and Zhibao Wang and Lu Bai and Liangfu Chen and Jinhua Tao",
year = "2021",
month = oct,
day = "12",
doi = "10.1109/IGARSS47720.2021.9554323",
language = "English",
isbn = "9781665447621",
series = "IEEE International Geoscience and Remote Sensing Symposium: Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1685--1688",
booktitle = "Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021",
address = "United States",
note = "IEEE International Geoscience and Remote Sensing Symposium 2021, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",
}