Ecosystem modeling using artificial neural networks: An archaeological tool
Prediction of past Normalized Difference Vegetation Index (paleo-NDVI) in Valle de Ambato (Catamarca, Argentina) in the periods of 550–650 and 1550–1650 CE was carried out to test the efficacy of Artificial Neural Network (ANN) to predict past environments for Archaeology. This work shows that both...
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Autores principales: | , , , , , |
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Formato: | Artículo publishedVersion |
Lenguaje: | Inglés |
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Elsevier Ltd
2018
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Materias: | |
Acceso en línea: | http://hdl.handle.net/11336/63298 http://suquia.ffyh.unc.edu.ar/handle/11336/63298 |
Aporte de: |
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I10-R181-11336-63298 |
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record_format |
dspace |
institution |
Universidad Nacional de Córdoba |
institution_str |
I-10 |
repository_str |
R-181 |
collection |
Suquía - Instituto de Antropología de Córdoba (IDACOR, CONICET y UNC) |
language |
Inglés |
topic |
ARGENTINA ARTIFICIAL NEURAL NETWORK ECOSYSTEM MODELING HINDCASTING PALEO-NDVI Meteorología y Ciencias Atmosféricas Ciencias de la Tierra y relacionadas con el Medio Ambiente CIENCIAS NATURALES Y EXACTAS Historia Historia y Arqueología HUMANIDADES Otras Sociología Sociología CIENCIAS SOCIALES |
spellingShingle |
ARGENTINA ARTIFICIAL NEURAL NETWORK ECOSYSTEM MODELING HINDCASTING PALEO-NDVI Meteorología y Ciencias Atmosféricas Ciencias de la Tierra y relacionadas con el Medio Ambiente CIENCIAS NATURALES Y EXACTAS Historia Historia y Arqueología HUMANIDADES Otras Sociología Sociología CIENCIAS SOCIALES Burry, Lidia Susana Marconetto, María Bernarda Somoza, Mariano Palacio, Patricia Irene Trivi, Matilde Elena D´Antoni, Héctor Ecosystem modeling using artificial neural networks: An archaeological tool |
topic_facet |
ARGENTINA ARTIFICIAL NEURAL NETWORK ECOSYSTEM MODELING HINDCASTING PALEO-NDVI Meteorología y Ciencias Atmosféricas Ciencias de la Tierra y relacionadas con el Medio Ambiente CIENCIAS NATURALES Y EXACTAS Historia Historia y Arqueología HUMANIDADES Otras Sociología Sociología CIENCIAS SOCIALES |
description |
Prediction of past Normalized Difference Vegetation Index (paleo-NDVI) in Valle de Ambato (Catamarca, Argentina) in the periods of 550–650 and 1550–1650 CE was carried out to test the efficacy of Artificial Neural Network (ANN) to predict past environments for Archaeology. This work shows that both subtropical Yunga and xerophytic Chaqueña vegetations respond in contrasting fashion to changes in climate forcings. To predict the past an ANN perceptron multilayer model was used. Modern NDVI data and Tree-Ring data were obtained from NOAA-Paleoclimate, and other public sources. These data were used to train the model. Real data and predictions were close (Pearson correlation 0.83–0.90) and warranted the following step, hindcasting. Important paleo-NDVI fluctuations lasting 15 to 20 years were identified in both periods under study. The paleo-NDVI fluctuations in the earlier period were probably related to the unidentified eruption of 583. The fluctuations in the later period appear related to the eruption of 1600 of the Huaynaputina volcano (SW Peru). These findings suggest that the model accurately identified vegetation fluctuations in response to changes in the volcanic forcing. Hence, the ANNs may be considered as apt tools for modeling past environments in support of archaeology. |
format |
Artículo Artículo publishedVersion |
author |
Burry, Lidia Susana Marconetto, María Bernarda Somoza, Mariano Palacio, Patricia Irene Trivi, Matilde Elena D´Antoni, Héctor |
author_facet |
Burry, Lidia Susana Marconetto, María Bernarda Somoza, Mariano Palacio, Patricia Irene Trivi, Matilde Elena D´Antoni, Héctor |
author_sort |
Burry, Lidia Susana |
title |
Ecosystem modeling using artificial neural networks: An archaeological tool |
title_short |
Ecosystem modeling using artificial neural networks: An archaeological tool |
title_full |
Ecosystem modeling using artificial neural networks: An archaeological tool |
title_fullStr |
Ecosystem modeling using artificial neural networks: An archaeological tool |
title_full_unstemmed |
Ecosystem modeling using artificial neural networks: An archaeological tool |
title_sort |
ecosystem modeling using artificial neural networks: an archaeological tool |
publisher |
Elsevier Ltd |
publishDate |
2018 |
url |
http://hdl.handle.net/11336/63298 http://suquia.ffyh.unc.edu.ar/handle/11336/63298 |
work_keys_str_mv |
AT burrylidiasusana ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool AT marconettomariabernarda ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool AT somozamariano ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool AT palaciopatriciairene ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool AT trivimatildeelena ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool AT dantonihector ecosystemmodelingusingartificialneuralnetworksanarchaeologicaltool |
bdutipo_str |
Repositorios |
_version_ |
1764820398177779712 |