The Impact of Digital Data Ecosystems on Our Understanding of the Greater Chacoan Cultural Landscape: Assessing Geospatial Information, Remote Sensing, and Aggregating Roads Data

Heitman, Carrie; Field, Sean

doi:10.5876/9781646421701.c014

Cited by 1 publication

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“…Strong matches represent sample profiles that strongly resemble the composite profile. Even among roads that are very similar to the composite, not all sections can be expected to match strongly due to the effects of erosion and land use (Friedman et al 2017;Heitman and Field 2021;Kincaid et al 1983), as well as the general variability of roads that are built over long distances. Therefore, to determine how often ground-truthed roads should be expected to match the composite, the K-S test was first conducted for all profiles of the North and South Roads.…”

Section: The Methodsmentioning

confidence: 99%

“…There are at least several hundred kilometers of Chaco roads, of which only a small number have been studied on the ground (Kincaid et al 1983). Furthermore, many roads are degrading as a result of modern land practices (Friedman et al 2017;Heitman and Field 2021). Consequently, rapid, effective methods for studying Chaco roads from both ground-and aerial-based perspectives are needed.…”

Section: Chaco Roadsmentioning

confidence: 99%

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Lidar-Derived Road Profiles

Field

2023

Adv. archaeol. pract.

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Despite considerable developments in the archaeological application of lidar for detecting roads, less attention has been given to studying road morphology using lidar. As a result, archaeologists are well equipped to locate but not thoroughly study roads via lidar data. Here, a method that visualizes and statistically compares road profiles using elevation values extracted from lidar-derived digital elevation models is presented and illustrated through a case study on Chaco roads, located in the US Southwest. This method is used to establish the common form of ground-truthed Chaco roads and to measure how frequently this form is across non-ground-truthed roads. This method is an addition to the growing suite of tools for documenting and comparing roads using remotely sensed data, and it can be particularly useful in threatened landscapes where ground truthing is becoming less possible.

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Section: The Methodsmentioning

confidence: 99%

Section: Chaco Roadsmentioning

confidence: 99%