Detection of Asian Dust Storm Using MODIS Measurements
Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remo...
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doaj-2ba97d3c27014e9aa9b3a1a037090c392020-11-25T00:16:49ZengMDPI AGRemote Sensing2072-42922017-08-019886910.3390/rs9080869rs9080869Detection of Asian Dust Storm Using MODIS MeasurementsYong Xie0Wenhao Zhang1John J. Qu2School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaInstitute of Remote Sensing and digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaEnvironmental Science and Technology Center (ESTC) and Department of Geography and GeoInformation Science (GGS), George Mason University, Fairfax, VA 22030, USAEvery year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS) reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI) and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP). The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas.https://www.mdpi.com/2072-4292/9/8/869Asian dust stormMODISdetection algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yong Xie Wenhao Zhang John J. Qu |
spellingShingle |
Yong Xie Wenhao Zhang John J. Qu Detection of Asian Dust Storm Using MODIS Measurements Remote Sensing Asian dust storm MODIS detection algorithm |
author_facet |
Yong Xie Wenhao Zhang John J. Qu |
author_sort |
Yong Xie |
title |
Detection of Asian Dust Storm Using MODIS Measurements |
title_short |
Detection of Asian Dust Storm Using MODIS Measurements |
title_full |
Detection of Asian Dust Storm Using MODIS Measurements |
title_fullStr |
Detection of Asian Dust Storm Using MODIS Measurements |
title_full_unstemmed |
Detection of Asian Dust Storm Using MODIS Measurements |
title_sort |
detection of asian dust storm using modis measurements |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2017-08-01 |
description |
Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS) reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI) and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP). The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas. |
topic |
Asian dust storm MODIS detection algorithm |
url |
https://www.mdpi.com/2072-4292/9/8/869 |
work_keys_str_mv |
AT yongxie detectionofasianduststormusingmodismeasurements AT wenhaozhang detectionofasianduststormusingmodismeasurements AT johnjqu detectionofasianduststormusingmodismeasurements |
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