rapanui_mulching

Archaeological Remote Sensing Study of Lithic Mulch Gardening on Rapa Nui (Easter Island), Chile

General Information

Title:

Data and Code for "Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island)"

Author Information:

• Principal Investigators: Dylan S. Davis

• Co-Investigators: Robert J. DiNapoli, Gina Pakarati, Terry L. Hunt, and Carl P. Lipo

Date of data collection/creation:

2023 January

Geographic location of data collection:

Rapa Nui, Chile

Funders and sponsors of data collection:

National Science Foundation (BCS-1841420, BCS-2218602), National Geographic Society’s Enduring Impacts: Archaeology of Sustainability Program (NGS-85450R-21) DSD is supported by a National Science Foundation SBE Fellowship (SMA-2203789).

Sharing/Access Information

License & restrictions on data reuse:

Recommended citation for the data:

suggested: Davis, D. S., R. J. DiNapoli, G. Pakarati, T. L. Hunt, and C. P. Lipo (2023). Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island). Retrieved from https://github.com/d-davis/rapanui_mulching

Related publications:

Davis, D. S., R. J. DiNapoli, G. Pakarati, T. L. Hunt, and C. P. Lipo (2024). Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island). Science Advances. In Press. https://doi.org/10.1126/sciadv.ado1459

Data & File Overview

File list:

-- Supplemental_Document.pdf - R-markdown file of machine learning script developed to identify lithic mulching features from WorldView-3 satellite imagery.

-- Supplemental_Code.R - R script contained in the Markdown file.

-- Mulch_Estimation.zip -- zip folder containing a raster dataset with cleaned lithic mulching estimations for Rapa Nui. Data was produced using a Maximum Entropy algorithm and was manually evaluated to remove errors.

-- Training_Data.zip -- zip folder containing shapefiles with training data used for machine learning classification of WorldView-3 satellite images.

Additional notes:

ESRI. (2020). ArcGIS (10.8.1). Environmental Systems Research Institute, Inc.

R Core Team. (2020). R: A language and environment for statistical computing (4.0.2). R Foundation for Statistical Computing. http://www.R-project.org/

Methodological Information

See published manuscript for methodological information.