OSMnx is a Python package to retrieve, model, analyze, and visualize street networks from OpenStreetMap.
OpenStreetMap (OSM) is a collaborative mapping project that provides a free and publicly editable map of the world.
OpenStreetMap provides a valuable crowd-sourced database of raw geospatial data for constructing models of urban street networks for scientific analysis
The utility network is the main component users will work with when managing utility and telecom networks within ArcGIS.
The utility network combined with a transaction model, attribute rules, editing tools, and more allows users to completely model and analyze their complex network systems for water, gas, electric, telecom, sewer, stormwater, and other utilities.
utility networks such as sewer and water systems; rivers and streams
Elements on the network have no choice in travel decision. Flow direction is determined by the network characteristics alone
Fundamentals of Remote Sensing - Introduction
What is Remote Sensing?
So, what exactly is remote sensing? For the purposes of this tutorial, we will use the following definition:
"Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information."
In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. This is exemplified by the use of imaging systems where the following seven elements are involved. Note, however that remote sensing also involves the sensing of emitted energy and the use of non-imaging sensors.
The utility network is the main component users will work with when managing utility and telecom networks within ArcGIS.
The utility network combined with a transaction model, attribute rules, editing tools, and more allows users to completely model and analyze their complex network systems for water, gas, electric, telecom, sewer, stormwater, and other utilities.
utility networks such as sewer and water systems; rivers and streams
Elements on the network have no choice in travel decision. Flow direction is determined by the network characteristics alone
Fundamentals of Remote Sensing - Introduction
What is Remote Sensing?
So, what exactly is remote sensing? For the purposes of this tutorial, we will use the following definition:
"Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information."
In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. This is exemplified by the use of imaging systems where the following seven elements are involved. Note, however that remote sensing also involves the sensing of emitted energy and the use of non-imaging sensors.
Government has huge amounts of information but how can this be effectively managed and delivered through the web? This session will ‘lift the lid’ on web mapping technology and identify some of the key issues that must be addressed to achieve a successful outcome.
The NSW government SIX Viewer web mapping portal will be used as a case study to demonstrate how terabytes of data can be integrated and delivered via the Internet.
What is GIS ?
Dimensions Modeling in GIS ?
GIS Models real word(Raster, Vector)
GIS Challenges ? Data and Tech.
GIS Functionality
Building information modeling (BIM) ?
GIS Components
Spatial Data
This Seminar presentation is made by Shrikrishna Kesharwani
1ST YEAR, Transportation engineering student
NIT WARANGAL
FOLLOW ME ON INSTAGRAM
@SHRIKRISHNAKESHARWANI
A network is a system of interconnected elements, such as edges (lines) and connecting junctions (points), that represent possible routes from one location to another.
Here I explained introduction to the network analysis in GIS.
An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.
The idea of smart village in the present day seen more important as there is a limit of growth of cities which is required in development of urban jungles where the population ratio per km of land is greater than the given norm. Smart village is very essential for the development. To stopping the movement of people towards the urban areas it is just not to develop the village but also it is a practice of the internal bonding between the people. A smart village should be interactive with the all multi-functional organization and there is to be increase active participation of people in various activities.
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Study of influence towards on transport network and usage of land in urban ar...ramakrishnark019
An urban transportation system is crucial to a city's overall development. Having an effective transportation system is crucial to raising the standard of living in urban areas. Effective utilization is crucial due to the transportation network's enormous development costs. Reaching optimal utilization necessitates appropriate connectivity and orientation. Urbanization has led to massive population growth and related activities in many developing countries. Inadequate transportation options and associated travel problems are the result of this. Therefore, developing ways to increase the transport network's efficiency requires a parameter-based evaluation of the network. It involves determining the variables that affect travel as well as the instruments and methods for defining urban features including the land use and transportation system. Research gaps are determined using the literature review as a guide. By recognizing the influences of land use on networks, networks on land use, networks on travel, and once again, networks on travel, the current study offers a paradigm for developing urban transportation networks. Information about land use, zonal boundaries, and the road network was gathered from the appropriate organizations. GIS was used to convert these to digital format.
Government has huge amounts of information but how can this be effectively managed and delivered through the web? This session will ‘lift the lid’ on web mapping technology and identify some of the key issues that must be addressed to achieve a successful outcome.
The NSW government SIX Viewer web mapping portal will be used as a case study to demonstrate how terabytes of data can be integrated and delivered via the Internet.
What is GIS ?
Dimensions Modeling in GIS ?
GIS Models real word(Raster, Vector)
GIS Challenges ? Data and Tech.
GIS Functionality
Building information modeling (BIM) ?
GIS Components
Spatial Data
This Seminar presentation is made by Shrikrishna Kesharwani
1ST YEAR, Transportation engineering student
NIT WARANGAL
FOLLOW ME ON INSTAGRAM
@SHRIKRISHNAKESHARWANI
A network is a system of interconnected elements, such as edges (lines) and connecting junctions (points), that represent possible routes from one location to another.
Here I explained introduction to the network analysis in GIS.
An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.
The idea of smart village in the present day seen more important as there is a limit of growth of cities which is required in development of urban jungles where the population ratio per km of land is greater than the given norm. Smart village is very essential for the development. To stopping the movement of people towards the urban areas it is just not to develop the village but also it is a practice of the internal bonding between the people. A smart village should be interactive with the all multi-functional organization and there is to be increase active participation of people in various activities.
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Study of influence towards on transport network and usage of land in urban ar...ramakrishnark019
An urban transportation system is crucial to a city's overall development. Having an effective transportation system is crucial to raising the standard of living in urban areas. Effective utilization is crucial due to the transportation network's enormous development costs. Reaching optimal utilization necessitates appropriate connectivity and orientation. Urbanization has led to massive population growth and related activities in many developing countries. Inadequate transportation options and associated travel problems are the result of this. Therefore, developing ways to increase the transport network's efficiency requires a parameter-based evaluation of the network. It involves determining the variables that affect travel as well as the instruments and methods for defining urban features including the land use and transportation system. Research gaps are determined using the literature review as a guide. By recognizing the influences of land use on networks, networks on land use, networks on travel, and once again, networks on travel, the current study offers a paradigm for developing urban transportation networks. Information about land use, zonal boundaries, and the road network was gathered from the appropriate organizations. GIS was used to convert these to digital format.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Presented at the 46th Society of Cartographers Summer School in Manchester on September 10 2010. The abstract for the talk was as follows: "OpenStreetMap is coming of age, but as it starts to be used more in the mainstream, the age-old questions of quality and completeness are coming to the fore. A range of data sources have been used to build up the map in the UK, from GPS traces to aerial imagery, historic mapping, NaPTAN and the OS Open Data release, each with their own benefits and limitations. This talk looks at a number of studies and tools developed to quantify, compare and address accuracy and coverage of the project in the UK, in an attempt to answer the key questions - is it complete yet and just how good is it?"
DEEP LEARNING NEURAL NETWORK APPROACHES TO LAND USE-DEMOGRAPHIC- TEMPORAL BA...civejjour
Land use and transportation planning are inter-dependent, as well as being important factors in forecasting urban development. In recent years, predicting traffic based on land use, along with several other variables, has become a worthwhile area of study. In this paper, it is proposed that Deep Neural Network Regression (DNN-Regression) and Recurrent Neural Network (DNN-RNN) methods could be used to predict traffic. These methods used three key variables: land use, demographic and temporal data. The proposed methods were evaluated with other methods, using datasets collected from the City of Calgary, Canada. The proposed DNN-Regression focused on demographic and land use variables for traffic prediction. The study also predicted traffic temporally in the same geographical area by using DNN-RNN. The DNN-RNN used long short-term memory to predict traffic. Comparative experiments revealed that the proposed DNN-Regression and DNN-RNN models outperformed other methods.
Deep Learning Neural Network Approaches to Land Use-demographic- Temporal bas...civejjour
Land use and transportation planning are inter-dependent, as well as being important factors in
forecasting urban development. In recent years, predicting traffic based on land use, along with several
other variables, has become a worthwhile area of study. In this paper, it is proposed that Deep Neural
Network Regression (DNN-Regression) and Recurrent Neural Network (DNN-RNN) methods could be used
to predict traffic. These methods used three key variables: land use, demographic and temporal data. The
proposed methods were evaluated with other methods, using datasets collected from the City of Calgary,
Canada. The proposed DNN-Regression focused on demographic and land use variables for traffic
prediction. The study also predicted traffic temporally in the same geographical area by using DNN-RNN.
The DNN-RNN used long short-term memory to predict traffic. Comparative experiments revealed that the
proposed DNN-Regression and DNN-RNN models outperformed other methods.
The Design of a Simulation for the Modeling and Analysis of Public Transporta...CSCJournals
Vehicular ad-hoc networks, when combined with wireless sensor networks, are used in a variety of solutions for commercial, urban, and metropolitan areas, including emergency response, traffic, and environmental monitoring. In this work, we model buses in the Washington, DC Metropolitan Area Transit Authority (WMATA) as a network of vehicular nodes equipped with wireless sensors. A simulation tool was developed, using the actual WMATA schedule, to determine performance metrics such as end-to-end packet delivery delay. In addition, a web-based front-end was developed, using the Google Maps API, to provide a user-friendly display and control of the network map, input parameters, and simulated results. This application will provide users with a simplified method for modifying network parameters to account for a number of parameters and conditions, including inclement weather, traffic congestion, and more.
New Approaches in Cognitive Radios using Evolutionary Algorithms IJECEIAES
Cognitive radio has claimed a promising technology to exploit the spectrum in an ad hoc network. Due many techniques have become a topic of discussion on cognitive radios, the aim of this paper was developed a contemporary survey of evolutionary algorithms in Cognitive Radio. According to the art state, this work had been collected the essential contributions of cognitive radios with the particularity of base they research in evolutionary algorithms. The main idea was classified the evolutionary algorithms and showed their fundamental approaches. Moreover, this research will be exposed some of the current issues in cognitive radios and how the evolutionary algorithms will have been contributed. Therefore, current technologies have matters presented in optimization, learning, and classification over cognitive radios where evolutionary algorithms can be presented big approaches. With a more comprehensive and systematic understanding of evolutionary algorithms in cognitive radios, more research in this direction may be motivated and refined.
The realistic mobility evaluation of vehicular ad hoc network for indian auto...ijasuc
In recent years, continuous progress in wireless communication has opened a new research field in
computer networks. Now a day’s wireless ad-hoc networking is an emerging research technology that
needs attention of the industry people and the academicians. A vehicular ad-hoc network uses vehicles as
mobile nodes to create mobility in a network.
It’s a challenge to generate realistic mobility for Indian networks as no TIGER or Shapefile map is
available for Indian Automotive Networks.
This paper simulates the realistic mobility of the Vehicular Ad-hoc Networks (VANETs). The key feature of
this work is the realistic mobility generation for the Indian Automotive Intelligent Transport System (ITS)
and also to analyze the throughput, packet delivery fraction (PDF) and packet loss for realistic scenario.
The experimental analysis helps in providing effective communication for safety to the driver and
passengers.
Community detection of political blogs network based on structure-attribute g...IJECEIAES
Complex networks provide means to represent different kinds of networks with multiple features. Most biological, sensor and social networks can be represented as a graph depending on the pattern of connections among their elements. The goal of the graph clustering is to divide a large graph into many clusters based on various similarity criteria’s. Political blogs as standard social dataset network, in which it can be considered as blog-blog connection, where each node has political learning beside other attributes. The main objective of work is to introduce a graph clustering method in social network analysis. The proposed Structure-Attribute Similarity (SAS-Cluster) able to detect structures of community, based on nodes similarities. The method combines topological structure with multiple characteristics of nodes, to earn the ultimate similarity. The proposed method is evaluated using well-known evaluation measures, Density, and Entropy. Finally, the presented method was compared with the state-of-art comparative method, and the results show that the proposed method is superior to the comparative method according to the evaluations measures.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Student information management system project report ii.pdf
Graph Centric Analysis of Road Network Patterns for CBD’s of Metropolitan Cities in India
1. Graph Centric Analysis of Road Network Patterns
for CBD’s of Metropolitan Cities in India
Presented by
Punit Hirdilal Sharnagat
Reg.No.: 2020TR10
M.Tech.(Transportation)
MOTILAL NEHRU NATIONAL INSTITUTE OF TECHNOLOGY ALLAHABAD
PRAYAGRAJ 211004, INDIA
Department of Civil Engineering
3. Introduction
• Cities worldwide comprises a variety of street network patterns and configurations that
affect human mobility, equity, health, and livelihoods.
• Street networks organize and structure human spatial dynamics and flows in a city.
• Street network analysis has become an important bridge between graph theory and
urban morphology and planning.
• Different street structures result in varying levels of efficiency, accessibility, and usage
of the transportation infrastructure.
• These structural properties have uncovered unique characteristics of different cities as
well as demonstrated hidden statistical commonalities manifested as scale invariant
patterns across different urban context.
4. Introduction
• With the availability of crowd sourced OpenStreetMap (OSM) Dataset, study of
network patterns is increasingly becoming focus area to understand the road patterns
and deficits related to transportation network development.
• With the advent of OSM dataset, new tools have been developed to derive the new
parameters like degrees of street junctions, lengths of road and network centrality that
can reveal the region wise road patterns.
5. Introduction
• To Study number
Tool Focus Type Language OS License Reference
Urban Network
Analysis toolbox
Network analysis
ArcMap plug-in,
Rhino3D plug-in
Python Windows
CC BY-NC-SA
3.0
Sevtsuk (2018); Sevtsuk
and Mekonnen (2012)
Metropolitan Form
Analysis toolbox
City footprint,
land use
ArcMap plug-in Python Windows CC BY-ND 4.0
Amindarbari and Sevtsuk,
2013
Multiple Centrality
Assessment
Network analysis Standalone Python Cross-platform unknown Gasser and Caillet (2013)
depthmapX Network analysis
Standalone, QGIS
plug-in, CLI, R
API
C++, R Cross-platform CC-GNU GPL
depthmapX Development
Team (2017); Turner, 2021
Place Syntax Tool Network analysis
QGIS plug-in,
MapInfo plug-in
C++,
Python
Cross-platform GPL-3.0
Ståhle Marcus and
Karlström (2005)
AwaP-IC Permeability QGIS plug-in Python Cross-platform GPL-3.0 Majic and Pafka (2019)
Continuity in Street
Networks
Network analysis QGIS plug-in, CLI Python Cross-platform MIT Tripathy et al. (2020)
sDNA Network analysis
QGIS plug-in,
ArcGIS plug-in,
AutoCAD plug-in,
CLI, Python API
C++,
Python
Cross-
platform/
Windows
GPL-3.0
Cooper and Chiaradia,
2020
OSMnx Network analysis Python package Python Cross-platform MIT Boeing (2017)
momepy
General purpose
morphometrics
Python package Python Cross-platform MIT Fleischmann (2019)
foot Building footprints R package R Cross-platform GPL-3.0 Jochem and Tatem, 2021
6. • OSMnx is a Python package to retrieve, model, analyze, and visualize street networks from
OpenStreetMap.
• Users can download and model walkable, drivable, or bikeable urban networks with a single line
of Python code, and then easily analyze and visualize them.
• With OSMnx, user can easily download and work with amenities/points of interest, building-
footprints, elevation data, street bearings/orientations, and network routing.
• OSMnx contributes five primary capabilities for researchers and practitioners.
1. It enables automated and on-demand downloading of political boundary geometries,
building footprints, and elevations.
2. It can automate and customize the downloading of street networks from OpenStreetMap
and construct them into multidigraphs.
3. It can correct and simplify network topology.
4. It can save/load street networks to/from disk in various file formats.
5. OSMnx has built-in functions to analyze street networks, calculate routes, project and
visualize networks, and quickly and consistently calculate various metric and topological
measures.
Introduction
7. OpenStreetMap
• OpenStreetMap (OSM) is a collaborative mapping project that provides a free and publicly
editable map of the world.
• OpenStreetMap provides a valuable crowd-sourced database of raw geospatial data for
constructing models of urban street networks for scientific analysis.
• OpenStreetMap uses a topological data structure, with four core elements (also known as
data primitives):
1. Nodes are points with a geographic position, stored as coordinates (pairs of a latitude
and a longitude).
2. Ways are ordered lists of nodes, representing a polyline, or possibly a polygon if they
form a closed loop.
3. Relations are ordered lists of nodes, Relations are used for representing the relationship
of existing nodes and ways.
4. Tags are key-value pairs.They are used to store metadata about the map objects.
8. S.N. Authors
Name
Title Dataset Model or
Method
Description
1. Geoff Boeing,
July 2017.
OSMnx: New Methods
for Acquiring,
Constructing,
Analyzing, and
VisualizingComplex
Street Networks
OpenStreetMap
Data
OSMnx • This study introduced OSMnx, a new
tool to make the collection of data and
creation and analysis of street
networks.
• This study addresses the limitations of
data availability, consistency, and
technology which made researchers’
work gratuitously difficult.
2. Zhao, Fangxia
et al.,
March 2016.
Analysis of Road
Network Pattern
Considering Population
Distribution and Central
Business District
Transit Network
data for Beijing
Relative
Neighborhoo
d Graph
• This paper proposes a road network
growing model with the consideration
of population distribution and central
business district (CBD) attraction.
• In this paper , the relative
neighborhood graph (RNG) is
introduced as the connection
mechanism to capture the
characteristics of road network
topology.
Literature review
9. S.N. Author
Name
Title Dataset Model / Method Description
3. Geoff Boeing,
Aug 2017 .
The Morphology
and Circuity of
Walkable and
Drivable Street
Networks
walkable and
drivable
networks for 40
US cities through
OSMnx
OSMnx • This study examines the relative circuity
of walkable and drivable urban
circulation networks by simulating
routes using OpenStreetMap data and
the OSMnx software.
• Study found that in most cities, driving
networks tend to produce more
circuitous routes than walking
networks.
4. Strano et al.,
Nov 2012.
Urban Street
Networks, a
Comparative
Analysis ofTen
European Cities
Street network
data from City
Councils
planning offices
and Ordnance
Survey maps
GIS Environment • In this paper, authors compared the
structural properties of the street
networks of ten different European
cities.
• They investigated the geometric
properties of network and highlighted
differences and similarities between
cities.
10. S.N
.
Author Name Title Dataset Model / Method Description
5. Giacomin,
David &
Levinson ,
Nov 2015
Road network
circuity in
metropolitan areas.
Metropolitan
statistical area
(MSAs) census
data
Circuity • This study measures the circuity for 51
villages in USA for 1990, 2000 and 2010.
• This study examines how circuity varies
with the length of origin–destination
pairs (OD pairs), estimating a measure
of distance decay for circuity.
6. Geoff Boeing,
January 2020.
Street Network
Models and
Indicators for Every
Urban Area in the
World.
OSM data OpenStreetMap • This study models and analyzes the
street networks of every urban area in
the world, using boundaries derived
from the Global Human Settlement
Layer.
• this study models over 160 million
OpenStreetMap street network nodes
and over 320 million edges across 8,914
urban areas in 178 countries, and
attaches elevation and grade data.
11. S.N. Author Name Title Model / Method Description
7. Ahmadzai et al.,
Nov 2018
Assessment and
modelling of urban road
networks using Integrated
Graph of Natural Road
Network (a GIS-based
approach)
Centrality,
Integrated Graph
of Natural Road
Network (IGNRN)
• In this study road networks are
modelled and assessed using Integrated
Graph of Natural Road Network
(IGNRN) method.
• Authors assess network using three
classes of centrality, namely, closeness,
betweenness and straightness.
8. Coimbra et al.,
April 2021
An analysis of the graph
processing landscape
- • In this study author provided an
overview of different aspects of the
graph processing landscape.
9. Beineke et al.
2000
The average connectivity
of a graph
- • In this paper, authors investigated the
average connectivity, as a new measure
of global connectedness.
12. Objectives
• To assess the road network structure, its pattern and shape , connectivity and
accessibility by applying graph theory.
• To identify the individual nodal characteristics of connectivity, accessibility and
nodal efficiency.
• To conduct comparative analysis of road network characteristics of CBD area of
metropolitan cities in India and selected cities of other countries.
13. Literature
search and
understanding
of rationale
Identification of
key unknowns
and research
questions
Identification of
objectives of
thesis
Leaning basics of python
and morphological
characteristics of transit
network
Data collection,
capture and
preparation
Analyzing street
network data for
cities using OSMnx
Comparative study
of city transit
network
Analyzing
results
Conclusions
and future
scope
Methodology
14. SOFTWARES
DATASET
Python
(Anaconda)
JupyterLab (IDE)
OSMnx
QGIS
Python Libraries
Road Network data
is obtained from
OpenStreetMap
using OSMnx • pandas
• geopandas
• momepy
• pyproj
• libpysal
• Shapely
• Spaghetti
15.
16. • OSMnx geocodes the query “Delhi, India" to retrieve the
place boundaries of that city from the NominatimAPI,
retrieves the drivable street network data within those
boundaries from the Overpass API, constructs a graph
model, then simplifies its topology such that nodes
represent intersections and dead-ends and edges represent
the street segments linking them.
• OSMnx models all networks as NetworkX MultiDiGraph
objects,Which are convertible to :
i. undirected MultiGraphs
ii. DiGraphs : without (possible) parallel edges
iii. GeoPandas node/edge GeoDataFrames
17. a. Not Simplified Network
Nodes = 270908, Edges = 593385
b. Simplified Network
Nodes = 61091, Edges = 208757
18. Network attributes
Values
Delhi Chennai Hongkong
Total No. of Nodes (n) 130357 29113 2979
Total No. of Edges (m) 347738 78646 5542
total edge length 28542820.251 5861122.264 717319.193
average edge length 82.1 74.525 129.433
average streets per node 2.819 2.84 2.89
Intersection count 107751 24684 2598
total street length 15658852.55 3133730.073 513674.88
Street segment count 183526 41156 4331
Average Street length 85.322 76.142 118.604
Average circuity 1.0468 1.0360 1.1315
Self loop proportion 0.0009262 0.000583 0.003232
Clean intersection count 59956 16832 1546
Node density (sq. km) 73.840 155.364 30.436
Intersection density (sq. km) 61.03 131.728 26.543
Edge density (sq. km) 16168.035 31278.512 7327.614
19. S.N. Type of road Total no. S.N. Type of road Total no. S.N. Type of road Total no.
1 Residential 287606 14 Road 70 27 Primary link, secondary 2
2 Tertiary 19635 15 Living street, unclassified 50 28 Motorway, trunk 2
3 Living street 14303 16 Motorway link 49 29 Motorway link, motorway 2
4 Unclassified 12418 17 Residential , tertiary 40 30 Trunk link, secondary 2
5 Secondary 8569 18 Tertiary, residential 38 31 Road, unclassified 2
6 Primary 1843 19 Motorway 33 32 Road, residential 2
7 Secondary link 677 20 Tertiary, secondary 19 33 Residential, road 2
8 Trunk 639 21 Tertiary, unclassified 15 34 Primary link, tertiary 1
9 Tertiary link 564 22 Secondary link, secondary 6 35 Primary link, primary 1
10 Primary link 537 23 Primary, secondary 4 36 Trunk link, tertiary 1
11 Residential , living street 228 24 Secondary link, residential 4 37 Secondary, unclassified 1
12 Trunk link 214 25 Trunk link, trunk 3 38 Primary, trunk 1
13 Residential , unclassified 151 26 Tertiary link, tertiary 3 39 Primary, trunk link 1
20.
21. b) Shortest path w.r.toTravelTime
a) Shortest path w.r.to Length
22. • Isochrone maps, also known as travel
time maps, are maps that show all
reachable locations within a specified
time limit by a specified mode of
transport.
• The isochrone below joins up all points
within a 30, 60 and 180 minutes of drive
with Travel speed of 5 KMPH from the
origin point (77.1837538, 28.5913494).
23.
24. Cities
Circuity
Walk Drive
Delhi, India 1.053 1.046
Mumbai, India 1.083 1.066
Chennai, India 1.047 1.036
Kolkata, India 1.069 1.064
Hongkong, China 1.142 1.131
Los Angeles, US 1.074 1.047
Frankfurt, Germany 1.048 1.061
7. Circuity of different cities for walkable and drivable network :
City
Walk Drive
Nodes Edges Nodes Edges
Delhi 156162 441526 130357 247738
Frankfurt 55060 157576 9402 19977
30. • Area of a tessellation cell
• Covered area ratio
• Area of a building footprint
• Length of a perimeter wall
• Building adjacency
• Mean neighbor distance between buildings
• Linearity of a street segment
• Width of a street profile
• Width deviation of a street profile
• Openness of a street profile
• Meshedness of a street network
• Connected components in a spatial network
31. • Network analysis for set of Central Business District (CBDs) and important
transit locations using OSMnx for cities.
• Network-constrained spatial autocorrelation for aggregate transit locations.
34. Activity
3rd Semester 4th Semester
Sep
2021
Oct
2021
Nov
2021
Dec
2021
Jan
2022
Feb
2022
March
2022
April
2022
May
2022
Literature Review
Identification of project
objectives and Development of
methodology
Basics of python and
characteristics of transit
network
Acquisition transit
Analysis of transit network data
for cities
Comparative study and analysis
of results
Paper writing
Submission of Report