Version 1
: Received: 3 January 2024 / Approved: 4 January 2024 / Online: 4 January 2024 (11:25:23 CET)
Version 2
: Received: 6 January 2024 / Approved: 8 January 2024 / Online: 8 January 2024 (11:35:45 CET)
Ghezzi, I.; Kościuk, J.; Church, W.; VanValkenburgh, P.; Ćmielewski, B.; Kucera, M.; Dąbek, P.B.; Contreras, J.; Mori, N.; Righetti, G.; Serafini, S.; Rojas, C. Assessing Conservation Conditions at La Fortaleza de Kuelap, Peru, Based on Integrated Close-Range Remote Sensing and Near-Surface Geophysics. Remote Sens.2024, 16, 1053.
Ghezzi, I.; Kościuk, J.; Church, W.; VanValkenburgh, P.; Ćmielewski, B.; Kucera, M.; Dąbek, P.B.; Contreras, J.; Mori, N.; Righetti, G.; Serafini, S.; Rojas, C. Assessing Conservation Conditions at La Fortaleza de Kuelap, Peru, Based on Integrated Close-Range Remote Sensing and Near-Surface Geophysics. Remote Sens. 2024, 16, 1053.
Ghezzi, I.; Kościuk, J.; Church, W.; VanValkenburgh, P.; Ćmielewski, B.; Kucera, M.; Dąbek, P.B.; Contreras, J.; Mori, N.; Righetti, G.; Serafini, S.; Rojas, C. Assessing Conservation Conditions at La Fortaleza de Kuelap, Peru, Based on Integrated Close-Range Remote Sensing and Near-Surface Geophysics. Remote Sens.2024, 16, 1053.
Ghezzi, I.; Kościuk, J.; Church, W.; VanValkenburgh, P.; Ćmielewski, B.; Kucera, M.; Dąbek, P.B.; Contreras, J.; Mori, N.; Righetti, G.; Serafini, S.; Rojas, C. Assessing Conservation Conditions at La Fortaleza de Kuelap, Peru, Based on Integrated Close-Range Remote Sensing and Near-Surface Geophysics. Remote Sens. 2024, 16, 1053.
Abstract
In this article, we combine datasets from multiple research projects and remote sensing tech-nologies to evaluate the conservation conditions of La Fortaleza de Kuelap, a pre-Hispanic monument in Peru’s northeastern Andes that suffered significant damage during historically high seasonal rains in April 2022. Our analyses seek to identify the main causes of the collapse and locate places where the monument is likely at risk of further deterioration. To do so, we model surface hydrology using a digital elevation model (DEM) derived from drone LiDAR data, re-construct a history of previous collapses, and calculate the volume of the most recent by fusing terrestrial LiDAR and photogrammetric datasets. In addition, we examine subsurface water ac-cumulation through electrical resistivity data, reconstruct the stratification of the monument from seismic refraction data, and analyze vegetation loss and ground moisture accumulation using high resolution satellite imagery. Our results point to water accumulation as the most significant source of risk for La Fortaleza’s perimeter walls. Combined with adverse contemporary conser-vation interventions and natural conditions, this led to the collapse of April 2022. This integration of analytical results demonstrates how multi-scalar and multi-instrumental approaches provide comprehensive and timely assessments of conservation needs.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.