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Boots on the Ground at Yaxnohcah

Ground-Truthing Lidar in a Complex Tropical Landscape

Published online by Cambridge University Press:  16 January 2017

Kathryn Reese-Taylor*
Affiliation:
Department of Anthropology and Archaeology, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N1N4, Canada
Armando Anaya Hernández
Affiliation:
Centro de Investigaciones Históricas y Sociales, Universidad Autónoma de Campeche, CP 24039, San Francisco de Campeche, Campeche, México
F. C. Atasta Flores Esquivel
Affiliation:
Instituto de Investigaciones Antropológicos, Universidad Nacional Autónoma de México, México D.F.
Kelly Monteleone
Affiliation:
Department of Anthropology and Archaeology, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N1N4, Canada
Alejandro Uriarte
Affiliation:
Instituto Nacional de Antropología e Historia, Arqueología, México D.F.
Christopher Carr
Affiliation:
Department of Geography, University of Cincinnati, Cincinnati, OH 45221, US
Helga Geovannini Acuña
Affiliation:
Centro de Investigaciones Históricas y Sociales, Universidad Autónoma de Campeche, CP 24039, San Francisco de Campeche, Campeche, México
Meaghan Peuramaki-Brown
Affiliation:
University of Athabasca, Athabasca, AB T9S 3A3, Canada
Nicholas Dunning
Affiliation:
Department of Geography, University of Cincinnati, Cincinnati, OH 45221, US

Abstract

This study proposes a sampling method for ground-truthing LiDAR-derived data that will allow researchers to verify or predict the accuracy of results over a large area. Our case study is focused on a 24 km2 area centered on the site of Yaxnohcah in the Yucatan Peninsula. This area is characterized by a variety of dense tropical rainforest and wetland vegetation zones with limited road and trail access. Twenty-one 100 x 100 m blocks were selected for study, which included examples of several different vegetation zones. A pedestrian survey of transects through the blocks was conducted, recording two types of errors. Type 1 errors consist of cultural features that are identified in the field, but are not seen in the digital elevation model (DEM) or digital surface model (DSM). Type 2 errors consist of features that appear to be cultural when viewed on the DEM or DSM, but are caused by different vegetative features. Concurrently, we conducted an extensive vegetation survey of each block, identifying major species present and heights of stories. The results demonstrate that the lidar survey data are extremely reliable and a sample can be used to assess data accuracy, fidelity, and confidence over a larger area.

Este trabajo propone un método de muestreo a fin de contrastar en el terreno los datos obtenidos a partir de imágenes LiDAR, que permitan al investigador verificar y/o predecir la precisión de los resultados sobre un área mayor. El estudio de caso aquí presentado se centra en el sitio de Yaxnohcah, ubicado en la Meseta Cárstica Central de la península de Yucatán. Está área se caracteriza por presentar una variedad de densos bosques tropicales húmedos y zonas de vegetación de humedal con pocos accesos de caminos y brechas. Para este estudio se seleccionaron veintiún bloques de 100 por 100 metros del área, que comprendió una muestra estratificada del 10 por ciento, e incluyeron ejemplos de varias zonas de vegetación distinta. Se realizó un recorrido de superficie por transectos a lo largo de los bloques, registrándose dos tipos de errores. Los Errores del Tipo 1 consisten de rasgos culturales identificados en campo, pero que no aparecen en el los Modelos Digital de Elevación (MDE) o en el Modelo de Superficie Digital (MSE). Los Errores de Tipo 2 consisten en rasgos que parecen culturales en el MDE o MSE, pero que en realidad son causadas por diferentes tipos de vegetación. De manera concurrente, realizamos un extenso reconocimiento de la vegetación en cada bloque, identificando las principales especies presentes, las diferentes alturas de dosel, así como las características generales de la topografía y los suelos. Los resultados del método de contrastación en el terreno demuestran que los datos lidar son sumamente confiables y es posible utilizar una muestra a fin de evaluar la precisión, la veracidad y la certidumbre de los datos sobre un área mayor.

Type
Research Article
Copyright
Copyright © Society for American Archaeology 2016

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