Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms

Samantha T Arundel,Gaurav Sinha

doi:10.1007/978-3-319-63946-8_3

Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms

Samantha T Arundel, Gaurav Sinha

https://doi.org/10.1007/978-3-319-63946-8_3

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Publication Date: Sep 16, 2017

Affiliation: Ohio University

#Geographic Object Based Image Analysis #Geographic Names Information System + Show 8 more

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Abstract

Landform objects extracted from Geographic Object Based Image Analysis (GEOBIA) based terrain segmentation to locations are overlaid and compared to feature types of landforms mapped in the USGS maintained Geographic Names Information System (GNIS) topographic database. GEOBIA terrain objects were found to statistically related to GNIS feature classes. Comparison of GNIS feature classes and GEOBIA landform classes suggests that GEOBIA landform class semantics correspond well with naive geographic conceptualizations reflected in GNIS feature types.

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