Urban Development Scenarios and Probability Mapping for Greater Dublin Region: The MOLAND Model Applications
Harutyun Shahumyan, Laura Petrov, Brendan Williams, Sheila Convery,
Michael Brennan - University College Dublin Urban Institute Ireland
Roger White - Memorial University of Newfoundland Canada
Gisand Remote Sensing Applied To Land Use ChangeOf The Prefecture Of CASABLAN...IJERA Editor
The population and urbanization of Morocco are increasing very rapidly. They have risenin large cities due to heavy immigration rate from rural areas to accessjob opportunities, better education, and better health facilities. Casablanca has the most affected land use changes in Morocco because of the immigration. This paper presents anintegrated study of land use change in this city from 1986 until 2011 using topographic map sheets (1986) and satellite image (2011). The layers of landuse map (1986) were obtainedby digitization technique in ARCGIS 9.3 software. Supervised classification methodology has been employed using maximum likelihood technique in ERDAS IMAGINE (2011) to extract from the satellite image four classes which were categorized into, built-up area, public green spaces, agricultural land and water bodies. The totalarea of each class was estimated by using geometry tools of ArcGISsoftware to compare land use changes between 1986 and 2011.
Improving the calibration of the MOLAND urban growth model with land-use info...Beniamino Murgante
Improving the calibration of the MOLAND urban growth model with land-use information derived from a time-series of medium resolution remote sensing data - Tim Van de Voorde, Johannes van der Kwast, Inge Uljee
Guy Engelen, Frank Canters
Gisand Remote Sensing Applied To Land Use ChangeOf The Prefecture Of CASABLAN...IJERA Editor
The population and urbanization of Morocco are increasing very rapidly. They have risenin large cities due to heavy immigration rate from rural areas to accessjob opportunities, better education, and better health facilities. Casablanca has the most affected land use changes in Morocco because of the immigration. This paper presents anintegrated study of land use change in this city from 1986 until 2011 using topographic map sheets (1986) and satellite image (2011). The layers of landuse map (1986) were obtainedby digitization technique in ARCGIS 9.3 software. Supervised classification methodology has been employed using maximum likelihood technique in ERDAS IMAGINE (2011) to extract from the satellite image four classes which were categorized into, built-up area, public green spaces, agricultural land and water bodies. The totalarea of each class was estimated by using geometry tools of ArcGISsoftware to compare land use changes between 1986 and 2011.
Improving the calibration of the MOLAND urban growth model with land-use info...Beniamino Murgante
Improving the calibration of the MOLAND urban growth model with land-use information derived from a time-series of medium resolution remote sensing data - Tim Van de Voorde, Johannes van der Kwast, Inge Uljee
Guy Engelen, Frank Canters
Application of remote sensing,population identificationSATISH KUMAR
GIS
Remote Sensing
POPULATION IDENTIFICATION-REMOTE SENSING
Application of remote sensing
Statistical Modelling of Population
Dasymetric Mapping of Population
Cape cod example
Consideration of adjustments to density
Urban areas are the centres of various activities which have multiple and diverse pollutant sources, emitting all kinds of air pollutants. In order to maintain a healthy air environment, availability of fine resolution air quality data and ability to visualize it at a neighborhood scale, is very much crucial. This paper presents how real-time sensor-based air quality monitors are best suitable to generate high spatial resolution pollution maps. Pollution maps develop the understanding of spatial distribution and extent of pollution and also enables hotspot identification. Real-time monitoring provides an opportunity to capture air quality fluctuations and also aids in spotting sudden changes in pollutant concentration to follow up with action. Collaboration and integration with various platforms enables data-driven problem solving in a multidisciplinary manner.
Adapting to the consequences of climate change in urbanised regions are of increasing importance in most parts of the world. This PhD study contributes with methods and knowledge regarding how planning of urban areas can be used as a tool to reduce impacts from transportation. The research focus on the development of land use and transportation models, that will be used to illustrate how different paths of future urban development can reduce transportation demands and thereby the related impacts on the climate and environment.
The demands for transportation are generated from a many different human activities. Modelling where people locate themselves in urban areas in relation to the placement of their opportunities (works, shopping etc.), is important part of describing how the impacts from transportation will evolve. The work conducted focus on three future pathways from the PASHMINA project, where different future development strategies are proposed. The methodologies applied vary from different GIS analysis, to land use change simulations conducted with in the ‘Land Use Change Impact Analysis’ (LUCIA) Cellular automata model, highlighting the consequences of future planning strategies
The results from this PhD study shows of how spatial planning can utilize advanced GIS techniques to gain valuable insight into the outcomes of different planning strategies. The results illustrate the potential improvements on sustainability that could be achieved, if planning practice where to change from the current patterns. Amongst others, factors such as urban proximity, public transportation accessibility and job proximity have been evaluated in the work with the scenarios. Furthermore well as methodologies for traffic impact analysis and population density measures that have been suggested, all demonstrating that the potential gains from rethinking the urban landscape through planning strategy.
VHR Thematic Maps from Aerospace for Regional and Provincial Urban PlanningPlanetek Italia Srl
Planetek Italia s.r.l. has defined off-the-shelf added value products, named Preciso® Land, based on the integration of Very High Resolution (VHR) Earth Observation data (namely WorldView-2) with traditional cartographic data.
The challenge has been to design value-added mapping products and standardized procedure to derive objective environmental indicators, useful for the decision-making process. Preciso® Land is appreciated as the most promising source for the derivation of an important territory indicator: the Soil Loss Index.
Computer Science
Active and Programmable Networks
Active safety systems
Ad Hoc & Sensor Network
Ad hoc networks for pervasive communications
Adaptive, autonomic and context-aware computing
Advance Computing technology and their application
Advanced Computing Architectures and New Programming Models
Advanced control and measurement
Aeronautical Engineering,
Agent-based middleware
Alert applications
Automotive, marine and aero-space control and all other control applications
Autonomic and self-managing middleware
Autonomous vehicle
Biochemistry
Bioinformatics
BioTechnology(Chemistry, Mathematics, Statistics, Geology)
Broadband and intelligent networks
Broadband wireless technologies
CAD/CAM/CAT/CIM
Call admission and flow/congestion control
Capacity planning and dimensioning
Changing Access to Patient Information
Channel capacity modelling and analysis
Civil Engineering,
Cloud Computing and Applications
Collaborative applications
Communication application
Communication architectures for pervasive computing
Communication systems
Computational intelligence
Computer and microprocessor-based control
Computer Architecture and Embedded Systems
Computer Business
Computer Sciences and Applications
Computer Vision
Computer-based information systems in health care
Computing Ethics
Computing Practices & Applications
Congestion and/or Flow Control
Content Distribution
Context-awareness and middleware
Creativity in Internet management and retailing
Cross-layer design and Physical layer based issue
Cryptography
Data Base Management
Data fusion
Data Mining
Data retrieval
Data Storage Management
Decision analysis methods
Decision making
Digital Economy and Digital Divide
Digital signal processing theory
Distributed Sensor Networks
Drives automation
Drug Design,
Drug Development
DSP implementation
E-Business
E-Commerce
E-Government
Electronic transceiver device for Retail Marketing Industries
Electronics Engineering,
Embeded Computer System
Emerging advances in business and its applications
Emerging signal processing areas
Enabling technologies for pervasive systems
Energy-efficient and green pervasive computing
Environmental Engineering,
Estimation and identification techniques
Evaluation techniques for middleware solutions
Event-based, publish/subscribe, and message-oriented middleware
Evolutionary computing and intelligent systems
Expert approaches
Facilities planning and management
Flexible manufacturing systems
Formal methods and tools for designing
Fuzzy algorithms
Fuzzy logics
GPS and location-based app
We use the Georeferenced results of the 2010 Census in Mexico to train machine learning algorithms to detect growth in cities and contribute new information to estimate the total population.
Sharing the experience and results of using georeferenced 2010 Census data in Mexico and EO to train algorithms in order to detect urban growth and generate useful information for estimating population for non-census years.
How to create attribute table in open source gisMrinmoy Majumder
Map Window 5 is an open-source GIS software that has the capability to digitize maps, create a geodatabase, convert raster to vector, interactive maps, georeferencing of images, etc. The current tutorial demo the way you can create an attribute table with the help of MapWindow 5.
Application of remote sensing,population identificationSATISH KUMAR
GIS
Remote Sensing
POPULATION IDENTIFICATION-REMOTE SENSING
Application of remote sensing
Statistical Modelling of Population
Dasymetric Mapping of Population
Cape cod example
Consideration of adjustments to density
Urban areas are the centres of various activities which have multiple and diverse pollutant sources, emitting all kinds of air pollutants. In order to maintain a healthy air environment, availability of fine resolution air quality data and ability to visualize it at a neighborhood scale, is very much crucial. This paper presents how real-time sensor-based air quality monitors are best suitable to generate high spatial resolution pollution maps. Pollution maps develop the understanding of spatial distribution and extent of pollution and also enables hotspot identification. Real-time monitoring provides an opportunity to capture air quality fluctuations and also aids in spotting sudden changes in pollutant concentration to follow up with action. Collaboration and integration with various platforms enables data-driven problem solving in a multidisciplinary manner.
Adapting to the consequences of climate change in urbanised regions are of increasing importance in most parts of the world. This PhD study contributes with methods and knowledge regarding how planning of urban areas can be used as a tool to reduce impacts from transportation. The research focus on the development of land use and transportation models, that will be used to illustrate how different paths of future urban development can reduce transportation demands and thereby the related impacts on the climate and environment.
The demands for transportation are generated from a many different human activities. Modelling where people locate themselves in urban areas in relation to the placement of their opportunities (works, shopping etc.), is important part of describing how the impacts from transportation will evolve. The work conducted focus on three future pathways from the PASHMINA project, where different future development strategies are proposed. The methodologies applied vary from different GIS analysis, to land use change simulations conducted with in the ‘Land Use Change Impact Analysis’ (LUCIA) Cellular automata model, highlighting the consequences of future planning strategies
The results from this PhD study shows of how spatial planning can utilize advanced GIS techniques to gain valuable insight into the outcomes of different planning strategies. The results illustrate the potential improvements on sustainability that could be achieved, if planning practice where to change from the current patterns. Amongst others, factors such as urban proximity, public transportation accessibility and job proximity have been evaluated in the work with the scenarios. Furthermore well as methodologies for traffic impact analysis and population density measures that have been suggested, all demonstrating that the potential gains from rethinking the urban landscape through planning strategy.
VHR Thematic Maps from Aerospace for Regional and Provincial Urban PlanningPlanetek Italia Srl
Planetek Italia s.r.l. has defined off-the-shelf added value products, named Preciso® Land, based on the integration of Very High Resolution (VHR) Earth Observation data (namely WorldView-2) with traditional cartographic data.
The challenge has been to design value-added mapping products and standardized procedure to derive objective environmental indicators, useful for the decision-making process. Preciso® Land is appreciated as the most promising source for the derivation of an important territory indicator: the Soil Loss Index.
Computer Science
Active and Programmable Networks
Active safety systems
Ad Hoc & Sensor Network
Ad hoc networks for pervasive communications
Adaptive, autonomic and context-aware computing
Advance Computing technology and their application
Advanced Computing Architectures and New Programming Models
Advanced control and measurement
Aeronautical Engineering,
Agent-based middleware
Alert applications
Automotive, marine and aero-space control and all other control applications
Autonomic and self-managing middleware
Autonomous vehicle
Biochemistry
Bioinformatics
BioTechnology(Chemistry, Mathematics, Statistics, Geology)
Broadband and intelligent networks
Broadband wireless technologies
CAD/CAM/CAT/CIM
Call admission and flow/congestion control
Capacity planning and dimensioning
Changing Access to Patient Information
Channel capacity modelling and analysis
Civil Engineering,
Cloud Computing and Applications
Collaborative applications
Communication application
Communication architectures for pervasive computing
Communication systems
Computational intelligence
Computer and microprocessor-based control
Computer Architecture and Embedded Systems
Computer Business
Computer Sciences and Applications
Computer Vision
Computer-based information systems in health care
Computing Ethics
Computing Practices & Applications
Congestion and/or Flow Control
Content Distribution
Context-awareness and middleware
Creativity in Internet management and retailing
Cross-layer design and Physical layer based issue
Cryptography
Data Base Management
Data fusion
Data Mining
Data retrieval
Data Storage Management
Decision analysis methods
Decision making
Digital Economy and Digital Divide
Digital signal processing theory
Distributed Sensor Networks
Drives automation
Drug Design,
Drug Development
DSP implementation
E-Business
E-Commerce
E-Government
Electronic transceiver device for Retail Marketing Industries
Electronics Engineering,
Embeded Computer System
Emerging advances in business and its applications
Emerging signal processing areas
Enabling technologies for pervasive systems
Energy-efficient and green pervasive computing
Environmental Engineering,
Estimation and identification techniques
Evaluation techniques for middleware solutions
Event-based, publish/subscribe, and message-oriented middleware
Evolutionary computing and intelligent systems
Expert approaches
Facilities planning and management
Flexible manufacturing systems
Formal methods and tools for designing
Fuzzy algorithms
Fuzzy logics
GPS and location-based app
We use the Georeferenced results of the 2010 Census in Mexico to train machine learning algorithms to detect growth in cities and contribute new information to estimate the total population.
Sharing the experience and results of using georeferenced 2010 Census data in Mexico and EO to train algorithms in order to detect urban growth and generate useful information for estimating population for non-census years.
How to create attribute table in open source gisMrinmoy Majumder
Map Window 5 is an open-source GIS software that has the capability to digitize maps, create a geodatabase, convert raster to vector, interactive maps, georeferencing of images, etc. The current tutorial demo the way you can create an attribute table with the help of MapWindow 5.
Sumit Dugar, Practical Action Consulting | Nepal Session | SotM Asia 2017Kathmandu Living Labs
State of the Map Asia (SotM-Asia) is the annual regional conference of OpenStreetMap (OSM) organized by OSM communities in Asia. First SotM-Asia was organized in Jakarta, Indonesia in 2015, and the second was organized in Manila, Philippines in 2016. This year’s conference, third in the series, was organized in Kathmandu, Nepal on September 23 – 24, 2017 at Park Village Resort, Budhanilkantha, Kathmandu, Nepal.
We brought nearly 200 Open Mapping enthusiasts from Asia and beyond to this year’s SotM-Asia. The event provided an opportunity to share knowledge and experience among mappers; expand their network; and generate ideas to expand map coverage and effective use of OSM data in Asian continent. We chose ‘from creation to use of OSM data’ as the theme of this year’s conference, emphasizing on the effective use of OSM data. We also brought together a government panel from four different countries in this year’s SotM-Asia. We believe this event will deepen the bond and enhance collaboration among OSM communities across Asia.
More information about the conference can be found on: http://stateofthemap.asia.
Computational Model for Urban Growth Using Socioeconomic Latent ParametersPiyush Yadav
The work was presented at European Conference of Machine Learning (ECML-PKDD), 2018 and focused on modelling and predicting urban growth using remote sensing and socioeconomic data.
Land Use Growth Simulation and Optimization for Achieving a Sustainable Urban...TELKOMNIKA JOURNAL
Urban areas have been perceived as the source of environmental problems. To avoid improper land use allocation, negative sprawl effects, and other sources of environmental degradation, city planners need tools for simulating and optimizing their proposed plans. This study proposed a “what-if” analysis model that could help the planners in assessing and simulating their urban plans in Bekasi City, Indonesia. As part of Jakarta Metropolitan Area which exhibited a “post-suburbanization” phenomenon, this city faces many problems because of its high urban growth. Since the urban area has higher land use density than the rural area, especially on built-up class, it needs more consideration when allocating this kind of land use. Because each type of built-up class influences another type, it is difficult to allocate manually. Therefore, this study proposed a land-use optimization application to help planners finding the appropriate land use. This study showed that a model with simulation and optimization can be used to handle urban growth.
What to do with the existing spatial data in planningKarel Charvat
Spatial planning acts between all levels of government so planners face important challenges in the development of territorial frameworks and concepts every day.
Spatial planning systems, the legal situation and spatial planning data management are completely different and fragmented throughout Europe.
Nevertheless, planning is a holistic activity.
All tasks and processes must be solved comprehensively with
input from various sources.
It is necessary to make inputs interoperable because it allows the user to search data from different sources, view them, download them and use them with help of geoinformation technologies (GIT).
The ever-increasing availability of linked open geospatial data provides an unprecedented source of geo-information to describe urban environments. This wealth of data should be turned into actionable knowledge: for example, open data could be used as a proxy or substitute for closed or expensive information. The successful employment of linked open geospatial data can pave the way for innovative solutions to smart city problems. We illustrate a set of experiments that, starting from linked open geospatial data, execute a knowledge discovery process to predict urban semantics. More specifically, we leverage geo-information about points of interests as input in a classification model of land use at a moderate spatial resolution (250 meters) over wide urban areas in Europe. We replicate our experiments in different European cities - Milano, München, Barcelona and Brussels - to ensure the repeatability and generality of our approach, and we explain the experimental conditions, as well as the employed datasets to guarantee reproducibility. We extensively report on quantitative and qualitative evaluation results, to judge the validity, as well as the limitations of our proposed approach.
Presentation by Mr. Paolo Veneri, Head of Territorial Statistics and Analysis, OECD
The 2nd OECD Roundtable on Cities and Regions for the SDGs was held at the World Conference Center in Bonn, Germany, on 9 December 2019, within the scope of the OECD programme on A Territorial Approach to the SDGs. The Roundtable brought together cities, regions, national governments, international organisations, private sector and other key stakeholders to identify trends and challenges in the localisation of the SDGs, including the experiences and key findings from the pilots of the programme.
Towards a Planning Decision Support System for Low-Carbon Urban DevelopmentBeniamino Murgante
Towards a Planning Decision Support System for Low-Carbon Urban Development
Ivan Blečić, Arnaldo Cecchini, Giuseppe A. Trunfio - Department of Architecture, Planning and Design, University of Sassari, Alghero
Serena Marras, Donatella Spano - Department of Economics and Woody Plant Ecosystems,University of Sassari
Matthias Falk, David R. Pyles - Land, Air and Water Resources, University of California
The use of GIS for the development of the A9 dual-carriagewayPeter McCready
Geographic Information Systems (GIS):
An argument for using a Geographic Information System (GIS) for the environmental assessment of the A9 dual-carriageway road development.
Produced in fulfilment of MSc Geospatial & Mapping Sciences at the University of Glasgow (2015).
Analysis Of Solar Radiation Towards Optimization and Location Of The Urban Bl...IEREK Press
Increasing population causes Energy consumption and environmental pollution. It is essential to consider renewable forms of energy, especially solar power, to reduce energy consumption. This requires attention to energy issues in the early stages of urban design and practical and creative solutions for more efficient use of this type of energy. This study aims at calculating the annual solar radiation at a city scale through a novel process and methodology. In this regard, artificial intelligence algorithms and satellite data can help maximize the amount of sunlight in neighborhoods and urban blocks in neighborhood units during the development process. In the simulation process, location, and optimization of the urban form, it is necessary to consider the limitations and resources for field study and simulation of urban blocks. Therefore, in this study, Farhangian neighborhood in phase 1 of Kermanshah, Iran, which has a good level of structural diversity and lends itself to field studies, was selected and studied at neighborhood and urban block scales. The case study indicates the significant role of calculatingand optimizing the patterns of urban blocks to achieve maximum solar energy. Estimates at different levels show that urban block variables effectively access solar radiation energy and, given various scales of development -from macro-scale spatial planning to micro-scale local design -can improve energy intake by 3 to 5 percent. Accordingly, the results show that to accelerate the calculation of energy at the planning scale, the use of 2.5D locating model and 3D optimization contribute to achieving the maximum or minimum solar radiation, respectively. On the other hand, this method can be used to organize calculations and planning for maximum absorption of solar radiation at different stages of development.
Similar to Urban Development Scenarios and Probability Mapping for Greater Dublin Region: The MOLAND Model Applications (20)
Analyzing and assessing ecological transition in building sustainable citiesBeniamino Murgante
"Analyzing and assessing ecological transition in building sustainable cities" Keynote presentation at "International Conference on Sustainable Environment and Technologies" 23 September 2022, Nicolas Tesla University Union, Belgrade, Serbia
Smart Cities: New Science for the Cities
Beniamino Murgante
School of Engineering, University of Basilicata
Lecture at the Department of Community and Regional Planning
Smart Cities course - Professor Alenka Poplin
Keynote at the 24th International Conference on Urban Planning and Regional Development in the Information Society
GeoMultimedia 2019, 2-4 April 2019
Karlsruhe Institute of Technology, Germany
Involving citizens in smart energy approaches: the experience of an energy pa...Beniamino Murgante
Involving citizens in smart energy approaches: the experience of an energy park in Calvello municipality
4th International Conference on Urban e-Planning, University of Lisbon, 23-24 April 2019
Programmazione per la governance territoriale in tema di tutela della biodive...Beniamino Murgante
Programmazione per la governance territoriale in tema di tutela della biodiversità - Sabrina Lai - Regione Sardegna, Direzione generale della difesa dell’ambiente slai@regione.sardegna.it
Università degli Studi di Cagliari, DICAAR, sabrinalai@unica.it
RISCHIO TERRITORIALE NEL GOVERNO DEL TERRITORIO: Ricerca e formazione nelle s...Beniamino Murgante
RISCHIO TERRITORIALE NEL GOVERNO DEL TERRITORIO: Ricerca e formazione nelle scuole di ingegneria
Giuseppe Las Casas, Beniamino Murgante, Francesco Scorza
UrbIng 2016
GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven g...Beniamino Murgante
GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven geospatial workforce education/training system
Mauro Salvemini, Giuliana Vitiello, Monica Sebillo, Sergio Farruggia. Beniamino Murgante
Focussing Energy Consumers’ Behaviour Change towards Energy Efficiency and Lo...Beniamino Murgante
Focussing Energy Consumers’ Behaviour Change towards Energy Efficiency and Low Carbon Economy: Perspective for Policy Making, Transnational Cooperation and Research.
Beniamino Murgante, Francesco Scorza,
Alessandro Attolico, Federico Amato
Presented at the REAL CORP 2016 - 21st International Conference on Urban Planning
and Regional Development in the Information Society
GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven g...Beniamino Murgante
GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven geospatial workforce education/training system
Mauro Salvemini, Francesco Di Massa, Monica Sebillo, Sergio Farruggia. Beniamino Murgante
Garden in motion. An experience of citizens involvement in public space regen...Beniamino Murgante
Garden in motion. An experience of citizens involvement in public space regeneration.
Sara Lorusso, Gerardo Sassano, Michele Scioscia, Antonio Graziadei, Pasquale Passannante, Sara Bellarosa, Francesco Scaringi, Beniamino Murgante
Fino alla fine degli anni '80 un urbanista che cercava di supportare dei ragionamenti di piano con l'informatica riusciva ad ottenere, nel migliore dei casi, qualche dato statistico sulla popolazione. Con il trascorrere degli anni si è assistito ad un incremento dell'utilizzo delle tecnologie per la costruzione dei quadri conoscitivi a supporto del processo di piano, fino a raggiungere l'attuale Information Explosion Era.
Il contenuto dell'intervento si baserà su aspetti teorici ed applicativi a partire dall'esperienza di Ian McHarg fino all'ultima "moda" delle Smart Cities.
Introduzione
Andreina Maahsen-Milan
Università di Bologna
Tecnologie, Territorio, Smartness
Beniamino Murgante
Università della Basilicata
Facoltà Ingegneria Edile di Ravenna - Università di Bologna
Via Tombesi dall'Ova 55, 48121 Ravenna
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
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Urban Development Scenarios and Probability Mapping for Greater Dublin Region: The MOLAND Model Applications
1. Urban Development Scenarios and Probability Mapping for Greater Dublin Region The MOLAND Model Application Harutyun Shahumyan White R., Petrov L., Williams B., Convery S., Brennan M. University College Dublin [email_address]
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3. European Environment Agency (EEA) cite Dublin’s sprawl as ‘worst-case scenario’ of urban planning so that newer member states such as Poland might avoid making the same mistakes… 75% of all Europeans now live in urban areas and this is expected to rise to 90% by 2020 based on current trends (EEA)
10. Simulation Results Land use maps of GDR in 2026 SEA 1 Continued trend SEA2 Finger expansion SEA3 Consolidation of key towns & the City SEA 4 Managed Dispersal
11. Residential Area Development Difference Between SEA Scenarios SEA1 2006 & 2026 Residential areas in 2026 not in 2006 2006 not in 2026 SEA2 SEA3 SEA4
21. Areas which will have no residential development by 2026 in any of considered scenario
22. Areas by their likelihood of becoming residential by 2026 for WWT3 and for 3 WWT scenarios combined
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25. Thank You www.uep.ie The Urban Environment Project is generously sponsored by the Irish Environmental Protection Agency as part of the ERTDI programme which is funded through the National Development Plan. 2005-CD-U1-M1 “Decision support tools for managing urban environment in Ireland’ All work undertaken on the MOLAND model, for the Greater Dublin Region is subject to the license conditions of the software developers, Research Institute Knowledge Systems b.v. (RIKS b.v.) and the data set owners, DG JRC under license no. JRC.BWL.30715. The authors would like to thank the Dublin and Mid East Regional Authorities for their cooperation in providing data and the context for the waste water facility case study. We would also like to acknowledge the assistance of the Urban Environment Project team.
Editor's Notes
Within the scope of the Urban Environment Project implemented in UCD Urban Institute Ireland (UII) several scenarios have been developed for the Greater Dublin Region and simulated by the MOLAND model in recent years. Initially simple scenarios were tested where only one or two elements were changed in each scenario. Then, based on the lessons learnt, more realistic and complex scenarios were simulated with key input from different thematic groups, researchers and officials. Some of these scenarios resulted in practical application, forming an important part of the latest review of the Regional Planning Guidelines (RPG) published in 2010.
The MOLAND model was used to simulate the spatial distribution of new urban development using three population projections for the GDR and to examine how this could impact planned future wastewater treatment capacity and defined catchment areas. The scenarios were based on the Irish Central Statistics Office’s (CSO) regional population projections for 2011-2026 . In addition to the Baseline scenario described above (SEA1), three other scenarios of GDR urban development were produced by early-stage and senior scientists and policy-makers during a summer school and workshop in 2009 held at UII, Dublin. The aim of this exercise was to bridge the scientific and stakeholder communities in order to collaborate around spatial models and produce future land use maps which should have a clear and accepted interpretation, be robust, statistically validated and respond to policy interventions. By using five driving forces (population, economic trends, urbanisation, transport and overall trends), the following qualitative scenarios were realised using the MOLAND model:
All ten scenarios described above were simulated by the MOLAND model running from 2006 to 2026. Though most of the parameters in the model were not changed, there were specific modifications in the input maps of suitability, zoning and the transport network as well as in the projected population and employment numbers. As a result the land use maps of 2026 generated by the model for different scenarios vary substantially. However, the aims of the described three studies are convergent, generating scenarios for future policy directions and urban development (e.g. with impact on future wastewater treatment), and linking the scientific and stakeholders community and therefore, the maps retrieved can be used complementarily. Figure 2 shows a comparison of the maps for each scenario. Specifically, the residential areas of the simulated maps in 2026 are compared with the actual residential areas in 2006. The comparison maps confirm that the GDR can have substantially different development patterns depending on the decisions made. Specifically, in some scenarios we have large urban development in the north of Dublin County (WWT2, WWT3); while in other scenarios urban sprawl is directed to the west of Dublin (SEA2, SEA3, EIA2). In some cases a few hinterland towns are developed broadly (SEA3, SEA4, EIA2); while in other cases more dispersed development in the hinterlands is observed (WWT1, WWT2, SEA1, EIA3). It is also noticeable that the most development occurs in the scenario with the highest projected population (WWT3); while the least development and even shrinkage of residential areas occur in the case of the recession scenario (EIA1).
The statistics show that most of the development takes place in Dublin County; and the maximum is reached in scenario WWT3. The minimum and maximum possible increase of residential areas if any one of the scenarios occurs was also calculated. Thus, compared with the residential areas as they were in 2006, the maximum increase of total residential areas by 2026 could be about 128% (WWT3) and the minimum increase could be about 65% (EIA1). The average estimated increase from all ten scenarios is about 87%.
Figure 4 shows five statistics (minimum, first quartile, median, third quartile, and maximum) as well as outliners for residential areas in hectares by county. Here again it is noticeable, that for all scenarios the most residential areas are developed in Dublin County. In addition, the residential areas in scenario WWT3 are substantially greater than in any other scenario in almost all counties. Therefore, it appears as an outlier in the boxplot (marked as ‘o’). Similarly, residential areas in 2006 are substantially smaller than in 2026 for any scenario, making them outliers too (marked as ‘*’).
Figures 5 and 6 show the industrial areas in 2026 for each scenario in each county compared with 2006 actual areas. For industrial areas the maximum increase by 2026 is 101% in the EIA2 scenario while the minimum increase is 11% in the EIA1 scenario. The average estimated increase is 47%.
In the case of the EIA2 scenario, Dublin and Kildare get significantly more industrial areas compared with other scenarios and counties (outliers in the boxplot). Similar analyses were done for commercial and service areas in the GDR.
The MOLAND model helps us to understand trends we are interested in and provides predictions of future land use changes. But in reality it offers not predictions of the future, but perspectives or alternative possible futures [18]. Indeed, each time the model runs it gives different predictions, both because of random elements and bifurcations inherent in the dynamics of the model. Therefore, the proper way to view the output of the model is probabilistically. To do this, a simulation should be run a sufficient number of times and a map of all the output possibilities produced [19]. Of course some possible outcomes will be very similar, and some can be quite different.
Probability mapping of a single scenario is used often in urban modelling practice. It is an effective approach to assist decision makers to understand the most likely development patterns of a particular scenario. However, if there are several scenarios, it is often difficult to justify the preference of a particular one. A solution can be a combined probability map of several different scenarios. In principle a composite probability map generated from the output of several different appropriate scenarios is not qualitatively different from a probability map representing the effect of the stochastic perturbations within a single scenario. For example, in the case of three growth scenarios — low, medium, and high — the combined probability map of urbanisation is essentially equivalent to a map generated from model runs in which the growth rate parameter varies stochastically. In any case some scenarios are more likely than others, and so the composite probability map should be constructed by weighting the various scenarios by their estimated likelihoods. The weighting factors themselves constitute a higher level scenario.
For illustration purposes the WWT scenarios described above were used for combined probability mapping. These scenarios are especially appropriate because of their similarity and simplicity. In particular, the WWT scenarios vary only by population projections. Using the methodology described in the previous section we have created a composite probability map using the three WWT scenarios. Specifically, each of the WWT scenarios was run 10 times, resulting in 30 land use maps of the GDR for 2026. Based on [11] and discussions with several researchers and officials, the following weights were defined for the WWT scenarios: 0.2 (WWT1), 0.5 (WWT2), 0.3 (WWT3). The residential development probability map was generated from the weighted sum of the 30 land use raster maps in ArcGIS using the specified weights. The result is shown in the right image of Figure 7, which represents the likelihood of residential sprawl in the GDR in 2026 given the assumption that three WWT scenarios have the specified likelihoods (weights). The maps in Figure 7 show that in the case of combined scenarios, the probability of residential development is decreased in some areas. More spatial statistical analyses of these maps is presented below. Probability maps show that most areas around Dublin are relatively predictable in terms of future urban land use: either they are likely to be developed or they are unlikely to be developed. However, if one land use class is equally likely as another of being present, there is a high degree of uncertainty related to the modelled class transition. Thus, many areas are not easily predictable (e.g. areas presented by the middle colours from the legend scheme). These areas are approximately equally likely to be developed or not and therefore the model is not capable of predicting accurately what may happen. In spite of this, for planners and decision makers these results still contain useful information (as these areas are capable of change and being influenced to change in various ways). It is useful to know, in a spatially explicit sense, where the probabilities of certain land use transitions are intermediate, because in these areas the future land uses can be influenced by small interventions in the present. In contrast, in the highly predictable area, major efforts would have to be made to alter the future land use patterns.
Figure 8 presents the areas in hectares by counties where there is no likelihood of residential development for scenario WWT3 as well as for all three WWT scenarios combined. Total area in each county with no development is larger in case of WWT combined scenarios compared with a single WWT3 scenario. This is the result of the variation of population projections used in the scenarios. While WWT3 reflects the population high growth scenario, WWT combined scenario includes weighted scenarios with lower population growth. Therefore, in case of combined scenarios we obtain less residential development than in WWT3.
More interesting are the areas with some likelihood of becoming residential. Figure 9 presents the areas with 10% to100% probability of residential development in the GDR. It should be noted that the numbers with 100% development include also residential areas already existing in 2006 the start year of the simulations (marked by ‘o’ in the figure). This shows that the vast majority of areas with 100% predictability are areas which already were residential in 2006 and in case of combined probability mapping new development with 100% probability is essentially smaller than in the case of WTT3 scenario. Indeed, uncertainty is higher in the combined probability mapping. Combining three different scenarios includes some scenario-specific assumptions, making the results more general. Therefore, the combined scenario probability map in general has less area where the model predicts residential development by 2026.
But whether it makes sense to combine scenarios depends also on the point of view — i.e. on the user of the probability map. For example, to combine the output from three different planning scenarios, corresponding to different land use zoning schemes or transportation policies, would make no sense from the point of view of the planner, who would be using the model to examine the consequences of alternative policies with the aim of choosing one of them. But from the standpoint of a developer, who can't know what policy will be adopted in the future, or to what degree a policy, if adopted, will be enforced, combining the scenarios is reasonable because the combined probability map would represent the uncertainty of the future land use environment given the information available to the developer.