Intersectando Geoestatística com Modelagem da Demanda por Transportes: um Levantamento Bibliográfico

Marques, Samuel de França; Pitombo, Cira Souza

doi:10.14393/rbcv72nespecial50anos-56467

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…[24] stated that geostatistics is one of the procedures for analyzing space-time data that takes into account the existing interactions between spatial and temporal components, allowing interpolations in time and space. Among the advantages of using geostatistics, according to [25], is the fact that it is a tool that can use as much information as is available with respect to the variable of interest-which is difficult to collect-to estimate its values in non-sampled locations through the generation of a continuous surface of estimated points.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Body Surface Temperature in Pigs Using Geostatistics

et al. 2023

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This paper explores the potential of infrared thermography and geostatistics in animal production and presents the results of the application of the combination of these techniques, contributing significantly to efforts to obtain animals’ responses to the environments in which they are located and thereby ensuring improvements in productivity and animal welfare. The objective was to verify the variability in surface temperature in pigs submitted to different climate control systems using geostatistics. Three growing animals per stall were selected. Dry bulb temperature (Tbd, °C), relative humidity (RH, %) and thermal images were recorded at 08:00 and 12:00 h. To analyze the data, semivariograms were made, the theoretical model was validated and kriging maps were constructed. The mean temperature of the pigs in the pen with adiabatic evaporative cooling (AEC) ranged from 32.40 to 36.25 °C; for the pigs in the forced ventilation (FV) pen, the range of variation was from 32.51 to 36.81 °C. In the control group (Con), with natural ventilation, the average temperature was 37.51 to 38.45 °C. The geostatistical analysis provided a mathematical model capable of illustrating the variation in temperature in the caudal–dorsal regions of the pigs according to the environments to which the animals were subjected.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Body Surface Temperature in Pigs Using Geostatistics

et al. 2023

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“…The lack of data on travel demand variables, which are usually spatially discrete, has led to an increasing number of geostatistical applications to travel demand modeling, with results that represent an important contribution to the planning and operation of transport systems (Gomes et al, 2018;Lindner and Pitombo, 2019;Marques and Pitombo, 2021a;Yang et al, 2018;Zhang and Wang, 2014). Several studies using Geostatistics for spatially estimate travel demand variables can be found in the bibliographic review by Marques and Pitombo (2020). Along these studies, the spatial dependence of travel demand variables is confirmed by the wellstructured variograms calculated in the geostatistical modeling step.…”

Section: Introductionmentioning

confidence: 99%

Should We Account for Network Distances or Anisotropy in the Spatial Estimation of Missing Traffic Data?

Marques¹,

Favero

Pitombo

2023

TRANSPORTES

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In light of the unavailability of traffic volume data for all road segments, the scientific literature proposes estimating this variable using spatial interpolators. However, most of the methods found use the Euclidean distance between the database points as a proximity measure, in addition to ignoring the anisotropy of the phenomenon. Thus, the objective of the present study was to apply Ordinary Kriging (OK) with network distances and anisotropic OK in traffic volume data on highways in the state of São Paulo (Brazil), comparing its results to the traditional isotropic approach with Euclidean distances. Goodness-of-fit measures confirmed the good performance and better suitability of OK with network distances over the analyses that use Euclidean distances. Addressing the anisotropy of the traffic volume data also helped to improve the results. The proposed method can effectively support estimating traffic volume in segments without flow data.

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Transit Ridership Modeling at the Bus Stop Level: Comparison of Approaches Focusing on Count and Spatially Dependent Data

Marques

Pitombo

2022

Appl. Spatial Analysis

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Boarding and alighting modeling at the bus stop level is an important tool for operational planning of public transport systems, in addition to contributing to transit-oriented development. The interest variables, in this case, present two particularities that strongly influence the performance of proposed estimates: they demonstrate spatial dependence and are count data. Moreover, in most cases, these data are not easy to collect. Thus, the present study proposes a comparison of approaches for transit ridership modeling at the bus stop level, applying linear, Poisson, Geographically Weighted and Geographically Weighted Poisson (GWPR) regressions, as well as Universal Kriging (UK), to the boarding and alighting data along a bus line in the city of São Paulo, Brazil. The results from goodness-of-fit measures confirmed the assumption that adding asymmetry and spatial autocorrelation, isolated and together, to the transportation demand modeling, contributes to a gradual improvement in the estimates, highlighting the GWPR and UK spatial estimation techniques. Moreover, the spatially varying relationships between the variables of interest (boardings and alightings) and their predictors (land use and transport system features around the bus stops), shown in the present study, may support land use policies toward transit-oriented development. In addition, by using an approach with little information, the good results achieved proved that satisfactory boarding and alighting modeling can be done in regions where there is a lack of travel demand data, as in the case of emerging countries.

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Intersectando Geoestatística com Modelagem da Demanda por Transportes: um Levantamento Bibliográfico

Cited by 4 publications

References 24 publications

Evaluation of Body Surface Temperature in Pigs Using Geostatistics

Evaluation of Body Surface Temperature in Pigs Using Geostatistics

Should We Account for Network Distances or Anisotropy in the Spatial Estimation of Missing Traffic Data?

Transit Ridership Modeling at the Bus Stop Level: Comparison of Approaches Focusing on Count and Spatially Dependent Data

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