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Rodents and satellites: Predicting mice abundance and distribution with Sentinel-2 data

Authors :
Alfred Stein
Cecilia Provensal
Diana Brito Hoyos
Verónica Andreo
Frank B. Osei
Mariana Belgiu
Department of Earth Observation Science
UT-I-ITC-ACQUAL
Faculty of Geo-Information Science and Earth Observation
Source :
Ecological informatics, 51, 157-167. Elsevier
Publication Year :
2019
Publisher :
Elsevier BV, 2019.

Abstract

Remote sensing data is widely used in numerous ecological applications. The Sentinel-2 satellites (S2 A and B), recently launched by the European Spatial Agency´s (ESA), provide at present the best revisit time, spatial and spectral resolution among the freely available remote sensing optical data. In this study, we explored the potential of S2 enhanced spectral and spatial resolution to explain and predict mice abundances and distribution in border habitats of agroecosystems. We compared the predictive ability of different vegetation and water indices derived from S2 and Landsat 8 (L8) imagery. Our analyses revealed that the best predictor of mice abundance was L8-derived Enhanced Vegetation Index (EVI). S2-based indices, however, outperformed those computed from L8 bands for indices estimated simultaneously to mice trappings and for mice distribution models. Furthermore, indices including S2 red-edge bands were the best predictors of the distribution of the two most common rodent species in the ensemble. The findings of this study can be used as guidelines when selecting the sensors and vegetation variables to be included in more complex models aimed at predicting the distribution and risk of various vector-borne diseases, and especially rodents in other agricultural landscapes. Fil: Andreo, Verónica Carolina. University Of Twente; Países Bajos. Ministerio de Salud. Instituto Nacional de Medicina Tropical; Argentina. Universidad Nacional del Nordeste; Argentina Fil: Belgiu, Mariana. University Of Twente; Países Bajos Fil: Brito Hoyos, Diana Marcela. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Osei, Frank. University Of Twente; Países Bajos Fil: Provensal, María Cecilia. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales; Argentina Fil: Stein, Alfred. University Of Twente; Países Bajos

Details

ISSN :
15749541
Volume :
51
Database :
OpenAIRE
Journal :
Ecological Informatics
Accession number :
edsair.doi.dedup.....b2a9c0571fea4c498fa2d6ff797b097a
Full Text :
https://doi.org/10.1016/j.ecoinf.2019.03.001