Highway Freight Flow Assignment in Massachusetts Using Geographic Information Systems

1998 ◽  
Vol 1625 (1) ◽  
pp. 156-164 ◽  
Author(s):  
Venkatesh Krishnan ◽  
Kathleen L. Hancock
Keyword(s):  
Urban Areas ◽  
Economic Indicator ◽  
Data Sources ◽  
Flow Data ◽  
Indicator Variable ◽  
Commodity Flow ◽  
Goods Movement ◽  
Flow Assignment ◽  
Freight Flow ◽  
Quantitative Procedure

Goods movement is an important aspect of the transportation system. Freight flow, complemented with the much-researched passenger movement, provides a way for understanding the complete vehicle flow scenario on the highways. Commodity movement prediction has not received much attention because of the lack of sufficient and easily accessible data sources. Most data sources give aggregated commodity movements and, because of the heterogeneity of freight, accurate predictions of truck flows have not been possible. A methodology for calculating the truck flows on the various highways in Massachusetts from interstate commodity flow data is presented. Freight tons originating and ending in Massachusetts have been converted to truck numbers by using a quantitative procedure and distributed to different areas in the state by using employment as an economic indicator variable. The truck flow is assigned to the important highways and validated against existing survey counts. On comparison, a large percentage of the roads show the estimated truck counts are within a tolerable error margin. The research also shows that statewide analyses need to be refined near urban areas because of a variety of complexities involved.

Developing a Commodity Flow Database from Transearch Data

2003 ◽  
Vol 1855 (1) ◽  
pp. 14-21 ◽  
Author(s):  
Dike N. Ahanotu ◽  
Michael J. Fischer ◽  
Hugh W. Louch
Keyword(s):  
Geographic Area ◽  
Data Sources ◽  
State Agencies ◽  
Distribution Centers ◽  
Commodity Flow ◽  
Additional Information ◽  
Goods Movement ◽  
Portland Metropolitan Area ◽  
Area Of Concern ◽  
Data Elements

A procedure is described for analyzing Reebie Transearch data to create a commodity flow database that is useful for transportation planning purposes. Several elements of the procedure were recently applied as part of the development of a commodity flow database for the Portland metropolitan area. The procedure begins with an overview of the robustness of various Transearch data elements. For less robust data elements, specific processes are described to improve on the Transearch data. This process generally includes acquiring additional data from federal and state agencies, acquiring additional information from primary industry sources, and applying these data to the geographic area of concern for the commodity flow database. A methodology for estimating the commodity distribution for goods movement that originates in warehouses and distribution centers is also described. Supplemental freight data sources are identified, and elements of these data sources that can be used to verify and refine the Transearch data are highlighted. In the case of discrepancies between the Transearch data and other freight data sources, a process is described to determine potential sources of the discrepancy and further improve on the Transearch data toward the creation of a full commodity flow database.

scholarly journals Mapping poverty using mobile phone and satellite data

2017 ◽  
Vol 14 (127) ◽  
pp. 20160690 ◽  
Author(s):  
Jessica E. Steele ◽  
Pål Roe Sundsøy ◽  
Carla Pezzulo ◽  
Victor A. Alegana ◽  
Tomas J. Bird ◽  
...  
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
Data Sources ◽  
Human Potential ◽  
Public And Private ◽  
Middle Income ◽  
Mobile Data ◽  
Poverty Measures ◽  
Urban And Rural Areas

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r 2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.

Exploring change in urban areas using GIS: data sources, linkages and problems

Annals of GIS ◽  
2012 ◽  
Vol 18 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Christopher D. Lloyd ◽  
Ian N. Gregory ◽  
Ian G. Shuttleworth ◽  
Keith D. Lilley
Keyword(s):  
Urban Areas ◽  
Data Sources ◽  
Gis Data

scholarly journals End consumer goods movement generation in French medium urban areas

2010 ◽  
Vol 2 (3) ◽  
pp. 6189-6204 ◽  
Author(s):  
Jesus Gonzalez-Feliu ◽  
Florence Toilier ◽  
Jean-Louis Routhier
Keyword(s):  
Consumer Goods ◽  
Urban Areas ◽  
Goods Movement

scholarly journals Association Between Happiness and Objective/Subjective Economic Status Among Older Adults in Myanmar

2020 ◽  
Author(s):  
Yuri Sasaki ◽  
Yugo Shobugawa ◽  
Ikuma Nozaki ◽  
Daisuke Takagi ◽  
Yuiko Nagamine ◽  
...  
Keyword(s):  
Older Adults ◽  
Rural Areas ◽  
Urban Areas ◽  
Economic Status ◽  
Wealth Index ◽  
Economic Indicator ◽  
Sampling Procedure ◽  
Household Asset ◽  
Face To Face ◽  
Urban And Rural Areas

Abstract BackgroundFew studies have examined whether objective or subjective economic status (ES) has a greater effect on the happiness of older adults in developing countries with ageing populations. This study examined whether objective/subjective economic status (ES) is associated with happiness in older adults in Myanmar.MethodA multistage, random sampling procedure and face-to-face interviews were conducted in urban and rural areas in Myanmar. The happiness of 1,200 participants aged 60+ was evaluated using a single happiness score of 0 (very unhappy) to 10 (very happy). The wealth index, used as an objective economic indicator, was calculated from household asset items. Subjective economic status was assessed by asking “Which of the following best describes your current financial situation in light of general economic conditions?” The possible responses ranged from (1) very difficult to (5) very comfortable. ResultsThe mean happiness score was lower among participants with low objective and subjective ES than among those with medium or high objective ES (6.24 versus 6.80 points, p < 0.001) and average or higher subjective ES (5.62 versus 6.83 points, p < 0.001), respectively. Both low objective and subjective ES were negatively associated with happiness after adjusting for confounding variables (B: -0.41, 95% confidence interval [CI]: -0.69, -0.13 and B: -0.71, 95% CI: -1.00, -0.42, respectively) and stratification by region (low objective ES, urban: B: -0.52, 95% CI: -1.03, -0.02; low subjective ES, urban: B: -0.50, 95% CI: -0.96, -0.03; low objective ES, rural: B: -0.37, 95% CI: -0.73, -0.02; and low subjective ES, rural: B: -0.80, 95% CI: -1.18, -0.41). ConclusionsIn Myanmar, both objective and subjective ES might influence happiness among older adults. Although they had a similar impact on happiness in urban areas, subjective ES had a stronger impact in rural areas. Interventions for promoting happiness in older adults should consider differences in how objective/subjective ES impacts happiness in different regions, and focus should be placed not only on improving objective ES but also subjective ES in society.

scholarly journals Demographic and functional evaluation of urban areas in Vojvodina region

2014 ◽  
pp. 593-605
Author(s):  
Vlasta Kokotovic ◽  
Aleksandra Spalevic
Keyword(s):  
Urban Areas ◽  
Total Population ◽  
Population Change ◽  
Functional Evaluation ◽  
Demographic Development ◽  
Active Population ◽  
Aging Index ◽  
Urban Settlements ◽  
Demographic Processes ◽  
Quantitative Procedure

The article illustrates the procedure of quantitative demographic and functional evaluation of urban areas in Vojvodina region. Evaluation is based on seven indicators such as total population, population change index, aging index, the share of employees in primary sector, the share of employees in total population, the share of economically active population (noncommuters) and the share of commuters in economically active population of all urban settlements in Vojvodina region. Quantitative procedure of demographic and functional valorization of urban areas is based on a rank method. According to the results of applied procedure, the categories of urban areas are determined. Each category demonstrates a level of demographic development and correlation between demographic potential and suitable geographical and traffic position. The article is an attempt to perceive better the demographic processes in settlements. Moreover, we pay attention to a different approach in the research of urban settlements network in Vojvodina region.

scholarly journals Flood inundation forecasts using validation data generated with the assistance of computer vision

2018 ◽  
Vol 21 (2) ◽  
pp. 240-256 ◽  
Author(s):  
Punit Kumar Bhola ◽  
Bhavana B. Nair ◽  
Jorge Leandro ◽  
Sethuraman N. Rao ◽  
Markus Disse
Keyword(s):  
Computer Vision ◽  
Urban Areas ◽  
Water Surface ◽  
Goodness Of Fit ◽  
Water Levels ◽  
Data Sources ◽  
Flood Inundation ◽  
Validation Data ◽  
Detection Techniques ◽  
Recent Developments

Abstract Forecasting flood inundation in urban areas is challenging due to the lack of validation data. Recent developments have led to new genres of data sources, such as images and videos from smartphones and CCTV cameras. If the reference dimensions of objects, such as bridges or buildings, in images are known, the images can be used to estimate water levels using computer vision algorithms. Such algorithms employ deep learning and edge detection techniques to identify the water surface in an image, which can be used as additional validation data for forecasting inundation. In this study, a methodology is presented for flood inundation forecasting that integrates validation data generated with the assistance of computer vision. Six equifinal models are run simultaneously, one of which is selected for forecasting based on a goodness-of-fit (least error), estimated using the validation data. Collection and processing of images is done offline on a regular basis or following a flood event. The results show that the accuracy of inundation forecasting can be improved significantly using additional validation data.

Northern Plains Grain Farm Truck Marketing Patterns

2015 ◽  
Author(s):  
Kimberly Vachal
Keyword(s):  
Asset Management ◽  
Travel Demand ◽  
Northern Plains ◽  
Policy Makers ◽  
Commodity Flow ◽  
Flow Models ◽  
Farm Operators ◽  
Grain Marketing ◽  
Freight Flow ◽  
On Farm

A survey of farm operators in the Northern Plains Region was conducted to gather information about on-farm storage and truck markets. The objective of the study is to provide information about farm truck grain marketing patterns in the Northern Plains. There is no other source for this information. It should be complementary to other farm-to-market information and national commodity flow publications. Farmers may use the results for their own investment and productivity assessments. Local and regional planners and policy makers can use the information in calibrating travel demand and freight flow models for investment and asset management choices.

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