Geostatistics For Engineers And Earth Scientists

Kriging method application and traffic behavior profiles from local radar network database: A proposal to support traffic solutions and air pollution control strategies

Shared mobility and transit-dependent population: A new equity opportunity or issue?

Os objetivos deste trabalho foram identificar e quantificar o uso da terra na Bacia Hidrografica do Corrego do Bezerro Vermelho no Municipio de Tangara da Serra, MT, por meio das imagens Landsat TM dos anos 1984 e 2011. As imagens foram georreferenciadas, classificadas e processadas no software Spring e as classes tematicas, quantificadas e editadas no software Arcgis. O grau de antropizacao foi verificado atraves do Indice de Transformacao Antropica. Foram identificadas cinco classes, cobertura florestal, vegetacao secundaria, agricultura, pastagem e lâmina de agua. Os resultados indicaram diminuicao nos percentuais das classes: de 35,35% na cobertura florestal, de 11,78% em pastagens e de 100% na vegetacao secundaria, decrescimos esses relacionados ao aumento de 248,75% da agricultura. Portanto, este trabalho evidenciou alteracao drastica da paisagem e, por meio do Indice de Transformacao Antropica, verificou-se aumento de 4,75 para 5,88 entre os anos 1984 e 2011, ou seja, a area de estudo encontrava-se na classe regular e passou a ser degradada, fato esse decorrente, sobretudo, das atividades antropicas, associadas a expansao da agricultura.

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Aplicação do indíce de transformação antrópica na análise multitemporal da bacia do córrego do Bezerro Vermelho em Tangará da Serra-MT

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 important to recognize that alternative approaches have been developed in recent years. Traditional methods, besides considering different explanatory variables, are appropriate to make estimates exclusively on previously surveyed households. On the other hand, recent studies have addressed spatial statistical concerns in the field of travel demand forecasting. The aim of this paper is to spatially estimate motorized travel mode choice probabilities in a continuous map using an Origin-Destination Survey database, conducted in the Sao Paulo Metropolitan Area in Brazil in 2007. Values were estimated in both sampled and non-sampled coordinates. This paper proposes a conjoint approach that combines the traditional procedure of travel demand forecasting (multiple logistic regression) with a spatial statistical method (ordinary kriging). A comparison is made with the one-step spatial method—indicator kriging (IK). Conjoint studies of spatial statistics and traditional methods are thriving in transportation analysis, giving rise to a travel mode choice surface in a confirmatory way. It is concluded that the proposed method can be used for future predictions of travel mode choices, unlike IK.

A Conjoint Approach of Spatial Statistics and a Traditional Method for Travel Mode Choice Issues

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 models seems reasonable. The main objective of this paper is to estimate transit trip production using Factorial Kriging with External Drift (FKED) through an aggregated data case study of Traffic Analysis Zones in Sao Paulo city, Brazil. The method consists of a sequential application of Principal Components Analysis (PCA) and Kriging with External Drift (KED). The traditional Linear Regression (LR) model was adopted with the aim of validating the proposed method. The results show that PCA summarizes and combines 23 socioeconomic variables using 4 components. The first component is introduced in KED, as secondary information, to estimate transit trip production by public transport in geographic coordinates where there is no prior knowledge of the values. Cross-validation for the FKED model presented high values of the...

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2016.1260811

Estimation of transit trip production using Factorial Kriging with External Drift: an aggregated data case study

This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at Sao Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.

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Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting

OBJECTIVE To carry out a spatial analysis of the occurrence of acts of violence (specifically robberies) in public transportation, identifying the regions of greater incidence, using geostatistics, and possible causes with the aid of a multicriteria analysis in the Geographic Information System. METHODS The unit of analysis is the traffic analysis zone of the survey named Origem-Destino, carried out in Salvador, state of Bahia, in 2013. The robberies recorded by the Department of Public Security of Bahia in 2013 were located and made compatible with the limits of the traffic analysis zones and, later, associated with the respective centroids. After determining the regions with the highest probability of robbery, we carried out a geographic analysis of the possible causes in the region with the highest robbery potential, considering the factors analyzed using a multicriteria analysis in a Geographic Information System environment. RESULTS The execution of the two steps of this study allowed us to identify areas corresponding to the greater probability of occurrence of robberies in public transportation. In addition, the three most vulnerable road sections (Estrada da Liberdade, Rua Pero Vaz, and Avenida General San Martin) were identified in these areas. In these sections, the factors that most contribute with the potential for robbery in buses are: F1 - proximity to places that facilitate escape, F3 - great movement of persons, and F2 - absence of policing, respectively. CONCLUSIONS Indicator Kriging (geostatistical estimation) can be used to construct a spatial probability surface, which can be a useful tool for the implementation of public policies. The multicriteria analysis in the Geographic Information System environment allowed us to understand the spatial factors related to the phenomenon under analysis.

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Violence in public transportation: an approach based on spatial analysis

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 combines the semivariogram deconvolution and Kriging with External Drift (KED). The method consists of initially assuming a disaggregated systematic sample from aggregate data. Subsequently, KED was applied to estimate the primary variable, considering the population as a secondary input. This research assesses two types of information related to the city of Salvador (Bahia, Brazil): an origin-destination dataset based on a home-interview survey carried out in 1995 and the 2010 census data. Besides standing out for the application of Geostatistics in the field of transportation planning, this paper introduces the concepts of semivariogram deconvolution applied to aggregated travel data. Thus far these aspects have not been explored in the research area. In this way, this paper mainly presents three contributions: 1) estimating urban travel data in unsampled spatial locations; 2) obtaining the values of the variable of interest deriving out of other variables; and 3) introducing a simple semivariogram deconvolution procedure, considering that disaggregated data are not available to maintain the confidentiality of individual data.

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Proposal of a geostatistical procedure for transportation planning field

Este artigo apresenta uma analise da evolucao do uso do solo na regiao de Barreiras. Utilizou-se imagens de satelite Landsat-5 (1984 e 2008) e imagens SRTM, processadas no programa Spring. Foram considerados a implantacao do agronegocio na regiao e aspectos do meio fisico. A declividade predominante e inferior a 5%, exceto nas bordas dos planaltos; a altitude esta em torno de 500-700 metros. A introducao do agronegocio trouxe mudancas espaciais na area, com crescimento da area urbana e alteracoes na distribuicao da vegetacao, com importante da area agricola e reducao da vegetacao de cerrado.

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Samille Santos Rocha

Papers

Estimation of transit trip production using Factorial Kriging with External Drift: an aggregated data case study

Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting

Violence in public transportation: an approach based on spatial analysis

Proposal of a geostatistical procedure for transportation planning field

Evolução do uso do solo e agronegócio na região oeste do Estado da Bahia.