Serviço Computacional para Interpolação Espacial de Dados Meteorológicos

Abstract

The spatial interpolation is an essential technique for several fields, such as meteorology, hydrology, agricultural zoning, characterization of health risk areas, sociodemo-graphic, among others. Through interpolation, it is possible to model a surface of a spatially distributed variable from a finite set of known data points. In the case of weather data for agriculture, for instance, interpolation allows us to observe how weather variables behave on a given rural property, which could serve as input for irrigation management on this property. Due to the increasing demand for the use of spatial interpolation,this work proposed the development of a scalable service based on technologies and standards of state-of-the-art in distributed systems, for spatial interpolation of meteorological data associated with agriculture. In order to achieve this goal, we developed a web service based on three different reference evapotranspiration interpolation algorithms, namely: Inverse distance weighted (IDW), Ordinary Kriging (OK) and RandomForest (RF). The first two are widely used algorithms in the spatialization of reference evapotranspiration and they are known to produce low interpolation errors. The third algorithm is originated from Machine Learning. It has been used in recent studies as an alternative for spatial interpolation of environmental variables. This last algorithmhas also been obtaining promising results in the estimation of evapotranspiration. The spatial interpolation web service proposed was developed and its performace was evaluated through measurement. This service was deployed on a production enviromentusing Docker container and a mobile application was developed to integrate and show the main functionalities of the web service. The developed service can be applied inseveral areas. However, in this work more attention was paid to the agricultural sector,as this one is the sector to which this study is focused on. The main beneficiaries of the web service are researchers and developers, which, in turn, are able to develop studies that will benefit the farmer from the application of the service. During this work,we also sought to evaluate how the developed service could be useful for the promotion of the performance and the scalability with respect to spatial interpolation calculus and generation of spatial models. We also highlighted the importance of this software as a support tool for other researches or even for other software, such as Aquaprev, which uses, among other parameters, evapotranspiration and spatial interpolation to estimate the irrigation time of a given crop.