Land Surface Parameterization at Exposed Playa and Desert Region to Support Dust Emissions Estimates in Southern California, United States

Remote sensing technologies provide a unique opportunity to identify ground surfaces that are more susceptible to dust emissions at a large scale. As part of the Salton Sea Air Quality Mitigation Program (SSAQMP) of the Imperial Irrigation District (IID), efforts have been made to improve our unders...

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Veröffentlicht in:Remote sensing (Basel, Switzerland) Switzerland), 2022-02, Vol.14 (3), p.616
Hauptverfasser: Cheng, Yen-Ben, Dickey, Hank, Yimam, Yohannes T., Schmid, Brian, Paxton, Bronwyn, Schreuder, Maarten, Tran, Reed
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Sprache:eng
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Zusammenfassung:Remote sensing technologies provide a unique opportunity to identify ground surfaces that are more susceptible to dust emissions at a large scale. As part of the Salton Sea Air Quality Mitigation Program (SSAQMP) of the Imperial Irrigation District (IID), efforts have been made to improve our understanding of fugitive, wind-blown dust emissions around the Salton Sea region in Southern California, United States. Field campaigns were conducted for multiple years to evaluate surface conditions and measure the dust emissions potential in the area. Data collected during the field work were coupled with remote sensing imagery and data mining techniques to map surface characteristics that are important in identifying dust emissions potential. Around the playa domain, surface crust type, sand presence, and soil moisture were estimated. Geomorphic surface types were mapped in the desert domain. Overall accuracy ranged from 91.7% to 99.4% for the crust type mapping. Sand presence mapping showed consistent and slightly better accuracy, ranging from 96.2% to 99.7%. Soil moisture assessment agreed with precipitation records. Geomorphic mapping in the desert domain achieved accuracy above 93.5%, and the spatial pattern was consistent with previous studies. These land surface condition assessments provide important information to support dust emissions estimates in the region.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14030616