Quantile technique to precipitation, rainfall anomaly index and biophysical parameters by remote sensing in Serra Talhada, Pernambuco
DOI :
https://doi.org/10.29150/jhrs.v7.6.p334-344Mots-clés :
Extreme Events, Surface Albedo, NDVI, MeteorologyRésumé
The occurrence of extreme events is a current reality that causes socioeconomic and environmental damages in the world. Increasingly, the occurrence of these events and their relation to anthropic actions are being investigated. Several methods have been used to identify and characterize extreme events to precipitation, mainly the quantile technique and the rainfall anomaly index (RAI). The objective of this paper was to identify years with extreme events to precipitation and to evaluate biophysical parameters to the surface by remote sensing through the use of orbital images. Parameters such as surface albedo, Normalized Difference Vegetation Index (NDVI) for years with extreme events were estimated using the ERDAS IMAGINE® 9.1 Software, from the implementation of the SEBAL algorithm. The study area is located in the municipality of Serra Talhada, Pernambuco. The thematic maps of the region were generated from the ArcGIS® 10.2.2 Software. For the Quantile of the years 1993, 1998, 2012, 2016 were classified as very dry, and for RAI the years 1993, 1998, 2012 were classified as extremely dry. The main differences between albedo and NDVI were observed through descriptive statistics. Quantile technique allowed the classification of annual precipitations, showing the interannual rainfall variability in the years 2011 and 2012, also confirming that the average for the normal years is characteristic of the semi-arid region. RAI allowed to identify the largest extreme events of precipitation in the years 1989 and 1998. The surface albedo had little variation due to the spatial and temporal analysis of the images, as did the NDVI. However, both the rainfall anomaly index and the Quantile technique are relevant and effective tools for rainfall classification and the remote sensing techniques as a tool to investigate the use and occupation of the soil, proved to be of great importance, helping the management and conservation of the soil.
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© Journal of Hyperspectral Remote Sensing 2018

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