The main objective of this study is to estimate variables related to transportation planning, in
particular transit trip production, by proposing a geostatistical procedure. The procedure …

Traditional methods for travel demand estimation are often built on socioeconomic and
travel information. The information required to conduct such studies is costly and rarely …

Travel demand models have been developed and refined over the years to consider a
characteristic normally found in travel data: spatial autocorrelation. Another important feature …

Studies in transportation planning routinely use data in which location attributes are an
important source of information. Thus, using spatial attributes in urban travel forecasting …

Urban dynamics can be characterized more effectively by considering spatial aspects in
studies. This paper, using a synthetic spatially correlated data set, aims to model the spatial …

Conventional analysis of transportation demand is usually carried out using socioeconomic,
travel, and land use attributes. Despite the effectiveness on travel demand forecasting, it is …

Considering the importance of spatial issues in transport planning, the main objective of this
study was to analyze the results obtained from different approaches of spatial regression …

Using spatial statistics techniques is a way to improve the forecast of travel demand
variables considering their spatial dependence. The semivariogram is a proper geostatistic …

These issues are timely in that they follow another special issue entitled" Celebrating 40
Years of Scientific Impacts by Cliff and Ord." Andrew Cliff and Keith Ord's (1969) paper," The …

Meteorological data are used in many studies, especially in planning, disaster management,
water resources management, hydrology, agriculture and environment. Analyzing changes …