4 Near-Surface Geophysics and Geoarchaeology: Methods and Mapping

We invite abstracts that will highlight applied methodologies and mapping projects, including near-surface geophysics (e.g., GPR, resistivity, magnetometry), remote sensing (e.g., drones, LiDAR), or comparisons in GPS accuracy and precision (e.g., GNSS, N-Trip, RTK)

Monday, 9 March 2026
9:30 AM - 11:00 AM
RCC, 106

Application of ArcGIS Pro Using Image Classification Tool to Map Earthquake Induced Sand Blows and Their Verification with GPR Surveys

Paper number: 4-3
Program: Technical Sessions
Time: 10:05 AM – 10:20 AM

Authors

Abstract

Land cover classification maps are widely used in environmental and urban planning, natural resource, and disaster mitigation. Image classification is essential for accurate and efficient classification of land cover mapping with the availability of high-resolution satellite imagery. It has the potential to significantly improve the accuracy and speed of the land cover classification, leading to better decision-making and policy outcomes.

In previous research on liquefaction sites in Marianna, AR, the preliminary reconnaissance methods that were used to locate possible sand blows were Google Earth, satellite images, aerial photographs and as well as Geographical Information System (GIS). Sometimes, these did not provide accurate results when trying to verify sand blow locations in the field.

In this study, we employed (GIS) methods for mapping sand blows precisely by using ArcGIS Pro software. The image classification tool available in ArcGIS Pro can be implemented using high-resolution satellite imagery (GIS Imagery) to highlight different land cover categories.

Specifically, we used high-resolution satellite imagery such as the Arkansas Satellite Imagery which is a 30cm pixel resolution digital Ortho-imagery data. This data was published in Universal Transverse Mercator UTM Zone 15N, NAD 83, meters available to the Arkansas GIS Office.

The image classification tool in the ArcGIS Pro software was used to differentiate and map possible sand blows across the main landforms of the Marianna area. It was performed by training the software on well-known sand blows that are clearly evident on the Arkansas satellite imagery using supervised classification method, pixel-based classification type, and a specific classification schema to include different land cover categories. Then, support vector machine classifier was used to run the image classification tool with a maximum number of at least 500 samples per class. The resulting image was compiled for the entire area and numerous “sand blow” features have been identified.

Later research proved that these results were accurate by conducting Ground Penetrating Radar (GPR) surveys at several of the most promising features. Results confirmed the existence of sand blow and sand dikes at the selected sand blow sites discovered from the classified GIS map throughout the survey area.

Geological Society of America Abstracts with Programs. Vol. 58, No. 1

doi: 10.1130/abs/2026SE-411613

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