Dust and Smoke Detection for Multi-Channel Imagers

Zhao, Tong; Ackerman, S. A.; Guo, Wei

doi:10.3390/rs2102347

Cited by 68 publications

(83 citation statements)

References 17 publications

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“…BTD (11-12 µm) can be applied to distinguish dust aerosols from clouds since dust particles absorb more infrared radiation at shorter wavelength while ice or liquid water particles exhibit higher absorption in longer wavelengths (Ackerman 1997;Zhao et al, 2010). Legrand (2001) …”

Section: A Short Introduction About the Methods For Dust Storm Detectionmentioning

confidence: 99%

An automated and integrated framework for dust storm detection based on ogc web processing services

Xiao

Shea

Wong

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

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Section: A Short Introduction About the Methods For Dust Storm Detectionmentioning

confidence: 99%

An automated and integrated framework for dust storm detection based on ogc web processing services

Xiao

Shea

Wong

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Many studies on Indian air quality rely on satellite observations as a result of these biases and limited availability of ground-based monitor data across India, including NO 2 from OMI aboard the Aura satellite [Lamsal et al, 2010;Ghude et al, 2013]. Satellite observations from OMI and other instruments have been previously used to evaluate emissions and surface concentrations [Lamsal et al, 2010;Lu and Streets, 2012;Lu et al, 2013;Streets et al, 2013], observe trends in air quality [Lamsal et al, 2013[Lamsal et al, , 2015Duncan et al, 2015;Krotkov et al, 2015], evaluate AOD for dust or anthropogenic pollution [King et al, 2003;Isakov et al, 2007;Zhao et al, 2010], and estimate NO X to VOC ratios in assessing O 3 regimes [Jin and Holloway, 2015]. Limitations of satellite observations include temporal availability (i.e.…”

Section: Satellite Observations For Air Quality Analysismentioning

confidence: 99%

Urban Emissions and Regional Air Quality in India

Karambelas

2017

Proc. Wisc. Space Conf.

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Satellite observations from the Ozone Monitoring Instrument are used in support of model evaluation of seasonal average results from the U.S. Environmental Protection Agency (EPA) Community Multi-scale Air Quality (CMAQ) model. Model evaluation was conducted with the purpose of identifying regional biases in model output compared to tropospheric columns. Comparison with tropospheric column NO2, an anthropogenic indicator, reveal that there are uncertainties regarding the emissions inventory input to CMAQ. Results have implications for developing accurate model inputs to produce accurate model output for relevant health impact assessments, which are increasingly important with increasing population, urbanization, and pollution in the region.

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“…For this reason, the reflectances at 0.86, 0.64 and 0.47 µm have been used to identify dust. This is often done in a ratio of one to another (e.g., Roskovensky and Liou, 2005) or as a normalized difference index (such as MNDVI or Rat 2 in Zhao et al (2010)). In the ratio tests, we square the reflectances trying to take advantage of enhanced non-linear behavior.…”

Section: Detection Criteria Over Landmentioning

confidence: 99%

“…The image-based dust detection system used in this paper was initially developed by Zhao et al (2010) for global dust and smoke detection from multi-channel satellite imagers. In this paper, we will apply the dust detection modules to Asian regions for two major purposes.…”

Section: Dust Detection Systemmentioning

confidence: 99%

“…For examples, brightness temperature difference (BTD) between 10.5 μm and 12.5 μm channels from Temperature Humidity Infrared Radiometers (THIR) had been used for dust storm detection over land in the early seventeenth of 20th century (e.g., Shenk and Curran, 1974). Thereafter, various mineral dust detection algorithms have been developed using VS and/or near IR channels (Tanré and Legrand, 1991;Kaufman et al, 2000;Miller, 2003;Qu et al, 2006) and thermal IR wavelengths (Ackerman, 1989;Legrand et al, 1989;Ackerman, 1997;Wald et al, 1998;Legrand et al, 2001;Darmenov and Sokolik, 2005;Evan et al, 2006;Verge-Depre et al, 2006;Hao and Qu, 2007) or their combinations (Roskovensky and Liou, 2005;Hansell et al, 2007;Zhao et al, 2010). Uniformity test of the scene has also been shown to be useful for discriminating homogeneous dust layers from clouds (Martins et al, 2002), especially over ocean.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

Zhao

2012

Aerosol Air Qual. Res.

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Asian dusts exert significant influences on regional air quality, weather, and climate. Detection of these highly variable aerosol events is challenging due to several factors, such as short lifetime, multiple scales, and strong interactions with local and regional surface and meteorological conditions. Since dust particles can directly alter solar and earth radiation in both visible (VS) and infrared (IR) spectral regions through scattering and absorption processes, both VS and IR remote sensing techniques can be used to detect dust plumes in the atmosphere. A dust detection system for multi-channel satellite imagers was applied in this study. The detection is based on the analysis of reflectance (or radiance) in VS channels or brightness temperature (BT) in IR channels. The magnitude of the difference in reflectance and/or BTs in selected channels due to dust is used to infer the signature of the dust particles. Descriptions of the detection system and its application for Asian dust using the Moderate-resolution Imaging Spectroradiometer (MODIS) satellite measurements are provided. The performance of the algorithm for Asian dust detection and its usefulness for monitoring the outbreaks and dispersion of Asian dust events were emphasized in the current study.

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Dust and Smoke Detection for Multi-Channel Imagers

Cited by 68 publications

References 17 publications

An automated and integrated framework for dust storm detection based on ogc web processing services

An automated and integrated framework for dust storm detection based on ogc web processing services

Urban Emissions and Regional Air Quality in India

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

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