Banco de dados pluviométricos integrados por dados da plataforma TRMM e estações pluviométricas nos estados de Goiás e Distrito Federal - Morais, Lidiane Batista de (2014)
In developed countries it is common the use of rainfall estimatives by using tools like Remote Sensing, but in technically less advanced countries, like in Brazil, this usage still limited. The study area focuses on the center-west of the country, which has a restricted network of rainfall stations. The State of Goiás and Distrito Federal has a wide area and its network of rainfall stations available is distributed irregularly, having distances, producing only point data, which can cause the use of inadequate information in the region, committing the management of stormwater in urban and rural areas. With the advent of technology, data from the Tropical Rainfall Measuring Mission satellite - (TRMM) has provided more consistency in relation to rainfall data, because it uses a global coverage, eliminating the effects of prior data points. This work has as main objective to develop a database of rainfall from the TRMM satellite (3B42 algorithm - version 7) and rainfall data measured in the field (rainfall stations), on the interval of 1998 to 2011. From this data was possible the development of rainfall data bank consisting of four bands: Band 1, which was composed by maps of rainfall stations; Band 2, represented by maps of rainfall from TRMM; Band 3 consists on maps of rainfall product, which is to merge the data from rainfall stations with TRMM data, and finally the database was represented by the Band 4, which is the metadata; this map is the pixel values used in band 3 The results of this study showed that there is an agreement between the data of rainfall stations (band 1) and TRMM (band 2) in periods of low rainfall frequency, unlike the rainy season, where the TRMM tends to overestimate the values of rainfall stations, showing correlation of maximum 94.09% in 2005, and at least 25.52% registered in the year 2006. When analyzing the composition of the (band 3), it was observed that during the dry period, a total of up to 100% of data from maps of rainfall stations was used, and in the rainy season it was used by 30% of data from the TRMM rainfall maps, which can be proven by the band 4. These maps resulted in a considerable solution for use mainly in the rainy seasons, where the rainfall stations do not always manage to capture the total precipitation. The TRMM represented 30% of the data in the rainy seasons, covering possible errors of rainfall stations.