SciELO - Scientific Electronic Library Online

 
 número65Estimación del impacto potencial de la contaminación difusa por métodos simplificados en el Área de Protección de Flora y Fauna, Pico de Tancítaro, Michoacán, MéxicoEfectos del cambio climático en la distribución del bosque de Oyamel índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay articulos similaresSimilares en SciELO

Compartir


Revista Geográfica de América Central

versión On-line ISSN 2215-2563versión impresa ISSN 1011-484X

Resumen

MEDEIROS-FEITOSA, Jose Reginaldo  y  OLIVEIRA, Carlos Wagner. Comparative study of precipitation data from the TRMM satellite and pluviometric stations in the state of Ceará, Brazil. Rev. Geog. Amer. Central [online]. 2020, n.65, pp.239-262. ISSN 2215-2563.  http://dx.doi.org/10.15359/rgac.65-2.10.

The Northeast of Brazil is characterized by a semi-arid climate and irregular rainfall over time, which jeopardize agriculture production, public supply and other sectors. In this sense, research activities that promote Sustainable Development provide subsidies for the implementation of new public policies aimed at water sustainability in the region. The purpose of the present research was to compare rainfall data obtained from pluviometric stations of the Fundación Cearense de Metrología y Recursos Hídricos (FUNCEME) (translated as Cearense Foundation of Meteorology and Water Resources), with precipitation estimates obtained by means of the Tropical Rainfall Measuring Mission (TRMM) satellite, from January 1, 1998 to December 31, 2017, totaling twenty years of analysis for the entire state of Ceará, Brazil. In its first part, the research employed the techniques of comparing pixel to point (A and B), point to pixel (C), and pixel to pixel (D) along with inverse distance weighted (IDW) interpolation; in the second stage, data were analyzed by accuracy evaluation metrics: mean absolute error (MAE), root-mean-square error (RMSE) and the correlation coefficient (r). Analyzes results indicated TRMM satellite imagery to be a good alternative with 16.46 mm MAE, 26.78 mm RMSE and a correlation coefficient of 0.96.

Palabras clave : Water Resources; Rainfall; Remote Sensing..

        · resumen en Español | Portugués     · texto en Portugués     · Portugués ( pdf )