Review: Geographic Information Systems: Developments and Applications, Landlords and Property: Social Relations in the Private Rented Sector, Reducing Regional Inequalities, Imagined Country: Society, Culture, and Environment, Planning and Urban Growth in Nordic Countries, towards a Green Architecture: Six Practical Case Studies, Handling Geographical Information: Methodology and Potential Applications, Urban Goods Movement: A Guide to Policy Planning

1992 ◽  
Vol 19 (3) ◽  
pp. 359-370
Author(s):  
M Kuijpers-Linde ◽  
A D H Crook ◽  
A E Green ◽  
D Cosgrove ◽  
R H Williams ◽  
...  
Keyword(s):  
Social Relations ◽  
Urban Growth ◽  
Geographical Information ◽  
Practical Case ◽  
Policy Planning ◽  
Regional Inequalities ◽  
Green Architecture ◽  
Goods Movement ◽  
Potential Applications ◽  
Urban Goods Movement

scholarly journals Analyzing the Spatiotemporal Uncertainty in Urbanization Predictions

2021 ◽  
Vol 13 (3) ◽  
pp. 512
Author(s):  
Jairo Alejandro Gómez ◽  
ChengHe Guan ◽  
Pratyush Tripathy ◽  
Juan Carlos Duque ◽  
Santiago Passos ◽  
...  
Keyword(s):  
Urban Growth ◽  
Geographical Information Systems ◽  
Growth Models ◽  
A Priori ◽  
Remote Sensing Data ◽  
Public Utility ◽  
Town Planning ◽  
Geographical Information ◽  
New Town ◽  
Spatiotemporal Uncertainty

With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make investments, design infrastructure, extend public utility networks, plan housing solutions, and mitigate adverse environmental impacts. Despite its importance, urban growth models often discard the spatiotemporal uncertainties in their prediction estimates. In this paper, we analyzed the uncertainty in the urban land predictions by comparing the outcomes of two different growth models, one based on a widely applied cellular automata model known as the SLEUTH CA and the other one based on a previously published machine learning framework. We selected these two models because they are complementary, the first is based on human knowledge and pre-defined and understandable policies while the second is more data-driven and might be less influenced by any a priori knowledge or bias. To test our methodology, we chose the cities of Jiaxing and Lishui in China because they are representative of new town planning policies and have different characteristics in terms of land extension, geographical conditions, growth rates, and economic drivers. We focused on the spatiotemporal uncertainty, understood as the inherent doubt in the predictions of where and when will a piece of land become urban, using the concepts of certainty area in space and certainty area in time. The proposed analyses in this paper aim to contribute to better urban planning exercises, and they can be extended to other cities worldwide.

scholarly journals Impacts of Urbanization on Land Use Pattern and Environment: A Case Study of Ajmer City, Rajasthan

2019 ◽  
Vol 8 (1) ◽  
pp. 87-91
Author(s):  
Bhanu Priya Chouhan ◽  
Monika Kannan
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Land Degradation ◽  
Satellite Images ◽  
Agricultural Land ◽  
Population Pressure ◽  
Geographical Information ◽  
Land Use Patterns ◽  
Use Patterns ◽  
The Impact

The world is undergoing the largest wave of urban growth in history. More than half of the world’s population now lives in towns and cities, and by 2030 this number will swell to about 5 billion. ‘Urbanization has the potential to usher in a new era of wellbeing, resource efficiency and economic growth. But due to increased population the pressure of demand also increases in urban areas’ (Drakakis-Smith, David, 1996). The loss of agricultural land to other land uses occasioned by urban growth is an issue of growing concern worldwide, particularly in the developing countries like India. This paper is an attempt to assess the impact of urbanization on land use and land cover patterns in Ajmer city. Recent trends indicate that the rural urban migration and religious significance of the place attracting thousands of tourists every year, have immensely contributed in the increasing population of city and is causing change in land use patterns. This accelerating urban sprawl has led to shrinking of the agricultural land and land holdings. Due to increased rate of urbanization, the agricultural areas have been transformed into residential and industrial areas (Retnaraj D,1994). There are several key factors which cause increase in population here such as Smart City Projects, potential for employment, higher education, more comfortable and quality housing, better health facilities, high living standard etc. Population pressure not only directly increases the demand for food, but also indirectly reduces its supply through building development, environmental degradation and marginalization of food production (Aldington T, 1997). Also, there are several issues which are associated with continuous increase in population i.e. land degradation, pollution, poverty, slums, unaffordable housing etc. Pollution, formulation of slums, transportation congestion, environmental hazards, land degradation and crime are some of the major impacts of urbanization on Ajmer city. This study involves mapping of land use patterns by analyzing data and satellite imagery taken at different time periods. The satellite images of year 2000 and 2017 are used. The change detection techniques are used with the help of Geographical Information System software like ERDAS and ArcGIS. The supervised classification of all the three satellite images is done by ERDAS software to demarcate and analyze land use change.

scholarly journals Independent Retailer Restocking Choices in Urban Goods Movement and Interaction Effects with Traditional Markets

2021 ◽  
Author(s):  
Taufiq Suryo Nugroho ◽  
Chandra Balijepalli ◽  
Anthony Whiteing
Keyword(s):  
Discrete Choice Models ◽  
Positive Influence ◽  
Transport Service ◽  
Vehicle Ownership ◽  
Traditional Markets ◽  
Goods Movement ◽  
Local Supply ◽  
Urban Goods Movement ◽  
Service Choice ◽  
Retrospective Questionnaire

AbstractTraditional markets play a key role in local supply chains in many countries, often influencing retailer decisions due to their inherent attractiveness. In contrast to restocking choices for retailers as part of large chains, choices of independent retailers driven by local traditional markets have not been widely researched and are not well understood. This paper analyses the factors influencing independent retailer restocking choices and investigates the interplay between the presence of traditional markets and retailer choices. Bandung city in Indonesia is chosen for the study where independent retailers are prevalent, and where a number of traditional markets are thriving. A retrospective questionnaire was used to capture independent retailer restocking behaviour and generation models were calibrated to arrive at the trip propensity. Discrete choice models were estimated to explain the retailer preferences for supplier location and transport service choice. Results indicate that trips generated by independent retailers are explained by the presence of traditional markets and retailers’ vehicle ownership, in addition to the standard variables such as number of persons employed, weekly goods demand and average shipment weight. As for restocking location choice, retailers are more likely to choose suppliers within a traditional market where the number of wholesaler units is larger. Furthermore, the choice of traditional markets has a positive influence on whether retailers choose to use their own vehicle to restock their shops.

scholarly journals Predicting Commercial Vehicle Parking Duration using Generative Adversarial Multiple Imputation Networks

2020 ◽  
Vol 2674 (9) ◽  
pp. 820-831
Author(s):  
Raymond Low ◽  
Zeynep Duygu Tekler ◽  
Lynette Cheah
Keyword(s):  
Regression Model ◽  
Multiple Imputation ◽  
Traffic Congestion ◽  
Dwell Time ◽  
Complex Nature ◽  
Negative Externalities ◽  
Commercial Vehicles ◽  
Goods Movement ◽  
Lack Of Information ◽  
Urban Goods Movement

As the world rapidly urbanizes in pace with economic growth, the rising demand for products and services in cities is putting a strain on the existing road infrastructure, leading to traffic congestion and other negative externalities. To mitigate the impacts of freight movement within commercial areas, city planners have begun focusing their attention on the parking behaviors of commercial vehicles. Unfortunately, there is a general lack of information on such activities because of the heterogeneity of practices and the complex nature of urban goods movement. Furthermore, field surveys and observations of truck parking behavior are often faced with significant challenges, resulting in the collection of sparse and incomplete data. The objective of this study is to develop a regression model to predict the parking duration of commercial vehicles at the loading bays of retail malls and identify significant factors that contribute to this dwell time. The dataset used in this study originates from a truck parking and observation survey conducted at the loading bays of nine retail malls in Singapore, containing information about the trucks’ and drivers’ activities. However, because of the presence of incomplete fields found in the dataset, the authors propose the use of a generative adversarial multiple imputation networks algorithm to impute the incomplete fields before developing the regression model using the imputed dataset. Through the parking duration model, the activity type, parking location, and volume of goods delivered (or picked up) were identified as significant features influencing vehicle dwell time, corroborating with findings in the literature.

From the Last Mile to the Last 800 ft

2017 ◽  
Vol 2609 (1) ◽  
pp. 85-92 ◽  
Author(s):  
Polina Butrina ◽  
Gabriela Del Carmen Girón-Valderrama ◽  
José Luis Machado-León ◽  
Anne Goodchild ◽  
Pramod C. Ayyalasomayajula
Keyword(s):  
Freight Transportation ◽  
Holistic Approach ◽  
Pickup And Delivery ◽  
Public And Private ◽  
Urban Freight ◽  
Customer Expectations ◽  
Goods Movement ◽  
Last Mile ◽  
Increasing Demand ◽  
Urban Goods Movement

Pickup and delivery operations are an essential part of urban goods movements. However, rapid urban growth, increasing demand, and higher customer expectations have amplified the challenges of urban freight movement. In recent years, the industry has emphasized improving last-mile operations with the intent of focusing on what has been described as the last leg of the supply chain. In this paper, it is suggested that solving urban freight challenges requires an even more granular scale than the last mile, that is, the last 800 ft. The necessary operations in the last 800 ft require integration of diverse stakeholders, public and private infrastructure, and a diverse set of infrastructure users with multiple, varied objectives. That complexity has led to a gap in the needs of delivery operations and the characteristics of receiving facilities (i.e., unloading and loading facilities and pickup–drop-off locations). This paper focuses on accessibility for pickup and dropoff operations, taking a closer look at urban goods movement in the last 800 ft from the final customer. The paper presents and analyzes previously documented approaches and measures used to study the challenges at the proposed scale. Finally, it proposes a more holistic approach to address accessibility for urban pickup–delivery operations at the microscale to help develop more comprehensive urban freight transportation planning.

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