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Improving Network Connectivity in Rural Texas Counties by Using Pandas and GeoPandas with TIGER Edge and Node Data
Performing network analysis can give insight to truck generated trips between origins and destinations. Having both urban and rural roadways identified within a file set is crucial for depicting route paths which experience heavy loading. Although OpenStreetMap (OSM) is a commonly used data source for road network analysis, our initial assessment for Menard, Schleicher, and Sutton Counties of Texas found missing edges in rural locations. This study reflects on the use of Pandas, GeoPandas, and shapely with TIGER linestring and point shapefiles to conduct snapping amongst the edges and establish a connected network, based fundamentally on hydraulic fracturing truck origin-destinations.
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