Spectral signatures for the identification of dry forest using sentinel-2 images over the lower basin of the chira river, piura region

Aldana C.; Revilla M.; Gonzales J.; Saavedra Y.; Moncada W.; Maicelo J. · Revista de Teledeteccion (2020) · DOI: 10.4995/raet.2020.14110

Resumen

El Niño phenomenon, droughts and the warm climate directly influence the good ecological state of the forests in the Piura Region. The objective is to relate the spectral signatures evaluated in the Sentinel-2 satellite images with the spectral signatures measured with the FieldSpec4 spectroradiometer, for the identification of dry forest in the lower basin of the Chira River, Piura región. The Sentinel-2 images corresponding to the 17MNR, 17MPR, 17MMQ, 17MNQ and 17MPQ tiles are pre-processed, mosaicked, resampled and cut with the SNAP software. Stacking of bands 2, 3, 4, 5, 6, 7, 8, 9, 11 and 12 generates a raster whose pixel reflectance values are related to their wavelengths. The classification of dry forest areas is done with the spectral signature measured with the FieldSpec4 spectroradiometer. The validation of the results is carried out by applying the non-parametric ANOVA and Mann-Whitney-Wilcoxon tests at four sampling points. The surface area of dry forest in the lower basin of the Chira River is 129 113.06 ha, which represents 3.8% of the total area of dry forest in northern Peru.

Instituciones: Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas; Universidad Nacional de San Cristóbal de Huamanga; Universidad Nacional de Frontera