American Journal of Applied Sciences

A Linear Model for Moving Measurements Estimation in Urban Climate Studies

Claudia Cotrim Pezzuto, Lucila Chebel Labaki, Lia Toledo Moreira Mota and Alexandre Alexandre de Assis Mota

DOI : 10.3844/ajassp.2011.685.690

American Journal of Applied Sciences

Volume 8, Issue 7

Pages 685-690

Abstract

Problem statement: Several methods can be adopted to study the variations in urban climate. The mobile measurement method is one of them, involving information provided by moving measurements of air temperature, that are taken in points defined along pre-established routes and also data from fixed-point temperature recording stations. Because moving measurements are made in different times along the measurement process, adjustments must be made in order to adequately analyze the air temperature measurements. Approach: Mobile measurements were taken in an urban area and contextualized in the domain of some fixed-point temperature recording stations. Therefore, a linear model proposed to investigate and represent the variables that influence moving measurements estimation in the urban context. Results: All proposed variables in the linear model were considered relevant, because all coefficients of the determined model were non null. Also, the identified model presents a good fit to the field data, as indicated by the resulting coefficient of determination (R2) that is 90.3%. Conclusion/Recommendations: The linear model described in this work is easy to apply, requiring few input variables. It is important to emphasize that the model was developed to estimate moving measurements as a function of fixed measurements and presents the potential to identify new input variables based on moving measurements, as shown by the fit among fixed and moving temperature measurements, in order to provide insight about other possible models of late time adjustment.

Copyright

© 2011 Claudia Cotrim Pezzuto, Lucila Chebel Labaki, Lia Toledo Moreira Mota and Alexandre Alexandre de Assis Mota. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.