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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Publications at this Location » Publication #385781

Research Project: Optimizing Water Use Efficiency for Environmentally Sustainable Agricultural Production Systems in Semi-Arid Regions

Location: Wind Erosion and Water Conservation Research

Title: Combining optical and radar satellite imagery to investigate the surface properties and evolution of the Lordsburg Playa, New Mexico, USA

item EIBEDINGIL, IUASU - University Of Texas - El Paso
item GILL, THOMAS - University Of Texas - El Paso
item Van Pelt, Robert - Scott
item TONG, DANIEL - George Mason University

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/2021
Publication Date: 8/27/2021
Citation: Eibedingil, I.G., Gill, T.E., Van Pelt, R.S., Tong, D.Q. 2021. Combining optical and radar satellite imagery to investigate the surface properties and evolution of the Lordsburg Playa, New Mexico, USA. Remote Sensing. 13(17):3402.

Interpretive Summary: Periodically dry playa lakebeds are potent sources of dust in semi-arid and arid regions globally. One such dry lakebed, Lordsburg Playa in southwestern New Mexico, is bisected by an interstate highway and dust emanating from the dry lakebed has caused visibility-related crashes that have claimed dozens of lives since the highway was built 50 years ago. Periodically dry lakebeds are complicated landscapes that change over time and the sources of dust also change over time. Local rainfall events may fill the channels of certain streams that terminate on the lakebed while other watersheds, missed by the rainstorms, remain dry. Thus, when the lakebed is inundated, it may be inundated in only small areas while others remain dry. University personnel from The University of Texas at El Paso and George Mason University, along with a USDA ARS scientist used historical remote sensing from Landsat 5 and 8 along with newer remote sensing from Europe’s Sentinel satellite and Interferometric Synthetic Aperture Radar (InSAR) to study the evolution of the dry lakebed’s surface for the 35-year period from 1984 to 2019. The use of the InSAR improved the usefulness of the remotely sensed images because it can offer details about the surface even when clouds obscure the surface from satellite-mounted cameras. This technique offers land managers a new tool to remotely monitor and manage landscapes that may prove a hazard to commerce and human health.

Technical Abstract: Driven by erodible soil, hydrological stresses, land use/land cover (LULC) changes, and meteorological parameters, dust events initiated from Lordsburg Playa, New Mexico, United States, threaten public safety and health through low visibility and exposure to dust emissions. Combining optical and radar satellite imagery products can provide invaluable benefits in characterizing surface properties of desert playas – a potent landform for wind erosion. The optical images provide a long-term data record and radar images deliver information about the land surface irrespective of clouds, darkness, and precipitation. In this study, the fractional abundance of soil, vegetation, and water endmembers were determined from pixel mixtures using linear spectral unmixing model in Google Earth Engine (GEE) for Lordsburg Playa. Landsat 5 and 8 images at 30 meters spatial resolution and Sentinel-2 images at 10-20 meters spatial resolution were used. Employing Interferometric Synthetic Aperture Radar (InSAR) techniques, the playa’s land surface changes and possible sinks for sediment loading from the surrounding catchment area were identified. The combination of optical and radar images significantly improved the effort to identify long-term changes of the playa and locations within the playa susceptible to hydrological stresses and LULC changes. The linear spectral unmixing algorithm addressed the limitation of Landsat and Sentinel-2 images related to their moderate spatial resolutions. The application of GEE facilitated the study by minimizing the time required for acquisition, processing, and analysis of images, and storage required for the big satellite data.