publications | Sujit Kumar Sikder

2026

Nature-Based Solutions Trends in Urban Water Security: A Pre-2021 Retrospective Look from Science and Practice

Riyan Habeeb, Sana Javaid, Sujit Kumar Sikder, and 2 more authors

Sustainable Communities, Dec 2026

DOI
A FAIR Social-Spatial Science Research Data Infrastructure

Gotthard Meinel, Jan Goebel, Stefan Jünger, and 6 more authors

Jun 2026

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The integration of social survey and spatial data is a prerequisite for cross-domain research but is constrained by infrastructural, legal, and methodological challenges. The Geolinking Service SoRa addresses these by providing a long-term, privacy-compliant research data infrastructure that links social science survey data with georeferenced spatial information. This poster introduces SoRa’s key infrastructure components: a user module, a public/private-mode API, a Geolinking API, and an R package to support user workflows. SoRa implements multiple geolinking methods—point-to-point, buffer, isochrone-based, and routing to the nearest point of interest (e.g., schools, hospitals)—and provides structural (synthetic) datasets that mirror spatial distributions for workflow testing without exposing sensitive data. By promoting FAIR and inclusive data integration, SoRa establishes a robust foundation for interdisciplinary, data-driven research. Explore more details on our website: https://sora-service.org/en
Integrating Local Large Language Models intoWebGIS: An Open-Source Framework for Natural Language Interaction

A. Rahaman and S. K. Sikder

AGIT Conference, 2026

Abs DOI

WebGIS applications are known for interacting with geospatial information. Integrating large language models (LLMs) can enable chat-based natural language interaction (NLI) features for exploring location-related questions. We implemented an open framework that enables chat-based user interaction to trigger geospatial actions while preserving data privacy. A Pythonnativ prototype was developed and tested using Ollama with controlled WebGIS interaction for a mobility-infrastructure use case based on open data.
Open Public Transit Plan Data: Geoprocessing and Spaital Analysis

Sujit Kumar Sikder

Oct 2026

Abs DOI

Dive into the fascinating realm of geoprocessing workflow and advanced spatial analysis with our comprehensive teaching material centered around the rich dataset provided by MDV - Local Public Transport in Central Germany. This educational resource is designed to empower learners, researchers, and professionals to unlock the full potential of open public transit data for spatial analytics. The case study area, situated within the operational domain of MDV, serves as a real-world backdrop for understanding and implementing geospatial techniques. The teaching material takes participants on a journey through the geoprocessing workflows, offering a step-by-step guide to harnessing the power of open data to derive meaningful insights. Key Highlights: Data Exploration: Learn to navigate and understand the intricacies of open public transit data. Explore the wealth of information provided by MDV, gaining insights into transportation offers, station density, and spatial relationships. Geoprocessing Techniques: Delve into fundamental geoprocessing techniques, from data cleaning and preprocessing to spatial indexing and spatial querying. Understand how to handle geographic data effectively, ensuring accuracy and reliability in subsequent analyses. Spatial Statistics: Elevate your spatial analysis capabilities with advanced statistical techniques. Analyze spatial patterns, detect clusters, and derive meaningful conclusions that can inform strategic planning and policy development within the Central German transportation context. Case Study Applications: Apply acquired knowledge to real-world scenarios within the MDV operational area. Explore case studies that demonstrate the practical applications of geoprocessing workflows and advanced spatial analysis in optimizing public transit systems and addressing regional transportation challenges. This teaching material is crafted to cater to a wide audience, from beginners seeking an introduction to geospatial analysis to seasoned professionals aiming to enhance their skill set. Embark on this educational journey and unlock the transformative potential of open public transit data in shaping the future of transportation in Central Germany.

2025

Repurposing Urban Parking Space to Green Space for Heat Stress Adaptation: Case Studies of Stuttgart (Germany) and Bhopal (India)

Chandana Basi, Ravan Marvin, and Sujit Kumar Sikder

In Urban Transformation - Connecting Urban Sustainability Labs, 2025

DOI
Digital & Data-Driven Transformations in Governance: A Landscape Review

Sarah Giest, Keegan McBride, Anastasija Nikiforova, and 1 more author

Data & Policy, 2025

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Abstract Data for Policy (dataforpolicy.org), a global community, focuses on policy–data interactions by exploring how data can be used for policy in an ethical, responsible, and efficient manner. Within its journal, six focus areas, including Data for Policy Area 1: Digital & Data-driven Transformations in Governance, were established to delineate the evolving research landscape from the Data for Policy Conference series. This review addresses the absence of a formal conceptualization of digital and data-driven transformations in governance within this focus area. The paper achieves this by providing a working definition, mapping current research trends, and proposing a future research agenda centered on three core transformations: (1) public participation and collective intelligence; (2) relationships and organizations; and (3) open data and government. The paper outlines research questions and connects these transformations to related areas such as artificial intelligence (AI), sustainable smart cities, digital divide, data governance, co-production, and service quality. This contribution forms the foundational development of a research agenda for academics and practitioners engaged in or impacted by digital and data-driven transformations in policy and governance.
The Urban Environment in South Asia: Studying the Ambient Air Quality in a Mid-Sized City in Bangladesh

Md. Monabbir Hossain, Md. Tariqul Islam, Sujit Kumar Sikder, and 4 more authors

Frontiers in Sustainable Cities, Mar 2025

Abs DOI

Improving the urban environment is an urgent task in the fast-growing mid-sized cities of South Asia. Ambient air pollution is worsened by unplanned urban land use and a lack of green and waterbodies, which combined cause a rapid increase in the urban heat island (UHI) effect. This study focuses on pervasive ambient air pollution in the urban environment, primarily driven by particulate matter (PM), which presents a dire public health threat. An in-situ investigation of 48 sites in a mid-sized but fast-growing city, Mymensingh, Bangladesh, suggested that the PM 2.5 concentration (118\,\textpm 64\,μg/m 3 ) is about eight times higher than the daily average suggested by WHO (15\,μg/m 3 ). Weekdays and weekends do not show significant differences in PM generation. Geospatial analysis suggests that good air quality conditions are not found in the study area, and\,> 50% of people are exposed to PM 10 in very unhealthy conditions (≥151\,μg/m 3 ). Traffic and commercial land cover generate the highest PM level. The monsoon climatic events control precipitation and are the most influential factor in diminishing PM concentrations. However, fast-growing mid-sized cities, like Mymensingh in Bangladesh and others throughout South Asia, are facing extreme ambient air pollution that severely impacts public health. Therefore, more action-oriented research initiatives are needed to formulate policies to control air pollution, considering local experiences, indigenous knowledge, logistics capabilities, cultural orientation, transparency, accountability, and strong collaboration, cooperation, and commitment among the public-private partnership.
Climate Change Impacts on Shoreline Migration and Community Livelihood Resilience: Evidence from Coastal Bangladesh

Md. Tariqul Islam, Md. Monabbir Hossain, Nur Mohammad Ha-Mim, and 2 more authors

Frontiers in Sustainability, Jan 2025

Abs DOI

The livelihoods of coastal people are at risk as shoreline migration is accelerated by climate change. To safeguard these communities and maintain their economy, it is imperative to strengthen resilience via adaptive strategies. Therefore, this study aims to estimate the rates and impacts of physical shoreline migration over the past 9,000 years using geospatial analysis and focus on understanding the livelihood resilience of coastal at-risk communities using in-depth interviews with environmental experts. The dynamic system of the Ganga-Brahmaputra-Meghna is highly complex and causes continuous shoreline migration. Historical data and more recent satellite remote sensing imagery analysis identified that the shrinking of the delta system has resulted from the migration of the shorelines at the mouth of the river system. Since 5,000 BP, it has been expanding towards the Bay of Bengal – meaning land gains at the coast. Land gain provides an opportunity for the extension of coastal communities but also increases their vulnerability to natural hazards. Moreover, by 2050, the salinity isoline with a 5-ppt is expected to shift inland by ⁓8 km in the south-east (Bhola-Patuakhali) and ⁓24 km in the southwest (Khulna-Satkhira) region. The in-depth interviews reveal several adaptive practices to effectively deal with the situation, including community knowledge, stakeholder engagement, local-led adaptation, and most importantly, temporal migration. The findings also highlighted the urgent need for an adaptation plan for the sustainability and resilience of coastal communities, considering indigenous knowledge with local cultural orientation and incorporation of scientific standards.
Mapping the Endogenous Drivers of Mega-Urbanisation in Contemporary Urban Development

Xinqin Liu, Runzhu Gu, Sujit Kumar Sikder, and 3 more authors

Journal of Urban Management, Jun 2025

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Potentials of a Research Infrastructure for Linking Survey and Spatial Data to Enable Interdisciplinary Research

T. Rieche, A. Jung, J. Lieth, and 3 more authors

AGIT Conference, 2025

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An interdisciplinary approach to the spatial analysis of survey data and the usage of social science and spatial science research data is a proper way to analyse questions of spatial justice and spatial inequality in more detail. The required technical linkage entails a number of hurdles such as data privacy, data access, reproducibility, and technical knowledge. The ’Geolinking ServiceSoRa’ is being developed to operationalise this linkage and make it easier to offer for research. The linking methods offered, their parametrisation and the expected output are presented in this article. Furthermore, the linkage process is demonstrated using the ’Practise Dataset’ by the Socio-Economic Panel (SOEP) and a spatial indicator of the ’IOER Monitor’ as an example to show the functionalities of the presented linking service. Challenges of implementing the SoRa service (such as usability, performance or handling of uncertainties) are discussed, with a focus on spatial science.
Geodata Management – Blessings of NoSQL - Database Systemes

Sujit Kumar Sikder

Aug 2025

Abs DOI

NoSQL database systems offer powerful advantages for managing geospatial dataset. Their flexible schema design allows seamless integration of diverse spatial formats such as GeoJSON and many more. Unlike traditional relational databases, NoSQL platforms scale horizontally and support real-time data ingestion and querying. Built-in geospatial functions and indexing enable efficient spatial analysis and location-based services. As geodata continues to grow in volume and complexity, NoSQL provides a dynamic and scalable foundation for innovative geospatial solutions. This material includes the following topics: a brief overview on the Geodata Management in the Context of “Big Data” , when to decide for NoSQL, What are the supports for spatial data?
Global Open Data in Local Urban Development: An Actionable Framework for Adopting Global Human Settlement Layer (GHSL) in the Global South

Sujit Kumar Sikder, Mohit Kapoor, Prajwal Parmar, and 2 more authors

Sustainable Communities, Dec 2025

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Transition of Car-Based Human-Mobility in the Pandemic Era: Data Insight from a Cross-Border Region in Europe

Sujit Kumar Sikder, Jyotirmaya Ijaradar, Hao Li, and 1 more author

2025

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Many transport authorities are collecting and publishing almost real-time road traffic data to meet the growing trend of massive open data, a vital resource for foresight decision support systems considering deep data insights. We explored the spatio-temporal transitions in the cross-country road traffic volumes in the context of modelling behavioural transitions in car-based human mobility. This study reports on individual car-based daily travel behaviour detected, before (2018) and during the COVID pandemic (2020), between Germany and neighbouring countries. In the case of Luxembourg, the Bridges and Roads Authority has installed a large digital traffic observatory infrastructure through the adoption of sensor-based IoT technologies, like other European member states. Since 2016, they have provided high-performance data processing and published open data on the country’s road traffic. The dataset contains an hourly traffic count for different vehicle types, daily for representative observation points, followed by a major road network. The original dataset contains significant missing entries, so comprehensive data harmonization was performed. We observed the decrease in traffic volumes during pandemic factors (e.g. lockdowns and remote work) period by following global trend of reduced personal mobility. The understanding the dynamic adaptive travel behaviours provide a potential opportunity to generate the actionable insight including temporal and spatial implications. This study demonstrates that the national open traffic data products can have adoption potential to address cross-border insights. In relevance to the net-zero carbon transition, further study should shed light on the interpolation and downscaling approaches at the comprehensive road-network level for identifying pollution hot spots, causal link to functional landuse patterns and calculation of spatial influence area.

2024

Rethinking Data Management Planning: Introducing Research Output Management Planning (ROMPi) Approach

Stefano Della Chiesa and Sujit Kumar Sikder

Data Science Journal, May 2024

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Sensing Spatial Inequality of Socio-Economic Factors for Deploying Permanent Deacons in the UK

Md. Tariqul Islam, Paul Rooney, Peter McGrail, and 2 more authors

Frontiers in Sociology, Nov 2024

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Integrating spatial inequality perspectives in strategic decision-making can ensure positive impacts on resource distribution for public welfare and sustainable development. This study aims to apply evidence-based approaches in deploying permanent deacons. The empirical case study has been conducted at the St Helens denary of the Liverpool archdiocese, UK. Assisting with charitable works is one of three served areas by the Roman Catholic Church facilitated by deacons. The deployment of permanent deacons could benefit from being evidence-based so that a deacon can serve to ease the socio-economic (e.g., population density, long-term health conditions, housing system, employment status, education level, social status) inequality in the most deprived area. We used geographic information system (GIS) based algorithms, Getis-Ord Gi* for hot spot analysis to find the clustered area by considering the socio-economic factors. The open/freely available government census dataset was found to help extract socio-economic parameters. Furthermore, a GIS-based multi-criteria assessment technique was conducted by applying map algebra (raster calculator) to identify the deprived area with ranks considering multiple socio-economic conditions, where served areas by the existing deacons were considered to constrain. The served areas were estimated by applying network analysis where OpenStreetMap and location existing deacons were used as input. Our empirical case study identified the central and northern parts of the deanery as the most and least deprived areas, respectively. Finally, Liverpool archdiocese could consider deploying new permanent deacons in St Helens denary based on suggested deprivation ranks. Therefore, the appropriate number of deacons in the deprived areas can quickly and effectively respond to the needy and enhance communities’ resilience and sustainable development by ensuring proportionate resource distribution.
An Experimental Hybrid Modelling Approach in Urban Energy Optimization: A Case Study in South Italy

Amro Issam Hamed Attia Ramadan, Sujit Kumar Sikder, Martin Behnisch, and 2 more authors

In 2024 IEEE Smart Cities Futures Summit (SCFC), May 2024

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Datenverknüpfung von Befragungsdaten mit Geodaten - wie geht das?

Theodor Rieche, Sujit Sikder, and Gotthard Meinel

FOSSGIS 2024, 2024

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Wie lassen sich Befragungs- und Geodaten für die Beforschung interdisziplinärer Forschungsfragen technisch verknüpfen? Zur Bereitstellung von Forschungsdaten für die Nutzung durch Dritte etablieren sich zunehmend sogenannte Forschungsdatenzentren (FDZ). Eine besondere Herausforderung stellt die Verknüpfung von sozialwissenschaftlich erhobenen Befragungsdaten mit raumwissenschaftlich generierten Geodaten dar, um Fragestellungen aus den Sozialwissenschaften hinsichtlich der Verteilung im Raum untersuchen zu können. Im von der DFG geförderten Forschungsprojekt "Aufbau der Sozial-Raumwissenschaftlichen Forschungsdateninfrastruktur SoRa: FAIR, intelligent, integrativ (SoRa+)" wird eine geeignete verteilte und modulare Infrastruktur entwickelt, welche die Datenverknüpfung standardisieren und erleichtern soll. Durch weniger Zeitaufwand für die Forschenden sowie für die FDZs soll das Forschen an interdisziplinären Fragen vereinfacht werden. Berücksichtigt werden dabei die Anforderungen des Datenschutzes sowie die FAIR-Prinzipien. Der Beitrag soll Interesse an der Nutzung von Forschungsdaten wecken und aktuelle Fragen aus dem Projekt SoRa+ vorstellen.
Verknüpfung von Langzeit-Befragungsdaten mit Geodaten – Potenziale für die Raumwissenschaften

Theodor Rieche, Sujit Kumar Sikder, and Gotthard Meinel

In , Dec 2024

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Langzeit-Befragungsdaten ermöglichen die Erfassung eines Stimmungsbildes der Bevölkerung zu vielfältigen Themen in den Sozialwissenschaften über einen langenZeitraum hinweg. Diese sogenannten Panelbefragungen reichen teilweise bis in die 1980er-Jahre zurück und werden zunehmend auch mit kleinräumigem Raumbezugder befragten Personen (wie Adresse oder Gitterzelle) in Forschungsdatenzentren in speziell geschützten Räumen für Forschungszwecke vorgehalten. Ein vergleichbarerTrend hin zur Erhebung und Bereitstellung von langen Zeitreihen lässt sich auch bei räumlichen Forschungsdaten in der Raumwissenschaft feststellen. So bieten z. B.Zeitreihen und Datenprodukte des ,,Monitors der Siedlungs- und Freiraumentwicklung“ des Leibniz-Institutes für ökologische Raumentwicklung eine Vielzahl an räumlichen Indikatoren unterschiedlicher räumlicher und zeitlicher Auflösung an, um vergleichende Analysen in Themenfeldern wie der Landnutzung oder der Nachhaltigkeit der Entwicklung zu ermöglichen. Da neue Erkenntnisse insbesondere durch interdisziplinäre Forschung erwartet werden, sollten z. B. auch sozialwissenschaftliche Daten mit Geodaten verknüpft und räumlich ausgewertet werden. Um diesen Prozess für Forschende zu vereinfachen, wird mit dem Geolinking Service SoRa ein Forschungsdatenservice entwickelt. Dieser Artikel gibt eine Einführung in diesen Dienst, wobei der Schwerpunkt auf den potenziellen Anwendungen für die Raumwissenschaften und relevanten sozialwissenschaftlichen Daten liegt, insbesondere in Bezug auf Umwelt- und räumliche Gerechtigkeit.
The Variability of Dynamics in Urban Spatial Transformation During the Post-COVID Era: Perspectives of the Global South and North

Sujit Kumar Sikder, Md Moynul Ahsan, Hassan Radoine, and 2 more authors

In Making Sense of Planning and Development for the Post-Pandemic Cities, 2024

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2023

World Settlement Footprint

Jan-Karl Haug, Tobias Krüger, Hendrik Zwenzner, and 9 more authors

Apr 2023

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Rapid urbanization is increasingly challenging in multiple domains including ecological, economic and social issues. In order to understand interrelationships between human habitat in relation to nature, to assess natural hazards more accurately, and to guide political and economic decisions more precisely, detailed settlement data is an important information base for further decisions and processes. This pilot project contributes novel and unique datasets from the World Settlement Footprint (WSF) suite for the NFDI4Earth community together with the IÖR-Monitor - a provider for data infrastructure and services, on land use and land cover in Germany. In addition to data itself, the data infrastructures are playing an increasingly important role to enable quick and easy access to data and a more efficient way of processing larger data. The objective of this pilot is to integrate these datasets into the NFDI4Earth infrastructure and make them accessible to a broad user community according to the FAIR principles and common standards. Stakeholders are data and infrastructure providers, data and system integrators as well as users from different scientific domains, public authorities, and decision-makers. We expect that the NFDI4Earth will advance and highly benefit from this pilot since the offered datasets are a valuable data source for many research applications. Besides, it can be seen as a precursor for numerous other satellite data applications, services and interoperability approaches to be integrated into NFDI4Earth.
Spatial Transition Dynamics of Urbanization and Rohingya Refugees’ Settlements in Bangladesh

Md. Tariqul Islam, Sujit Kumar Sikder, Mark Charlesworth, and 1 more author

Land Use Policy, Oct 2023

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Application of an Interdisciplinary Research Framework for Discerning Land Use Transitions in the Peri-Urban Areas of India

Manisha Jain, Sujit Sikder, and Artem Korzhenevych

Applied Geography, Jun 2023

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Application of an Interdisciplinary Research Framework for Discerning Land Use Transitions in the Peri-Urban Areas of India

Manisha Jain, Sujit Sikder, and Artem Korzhenevych

Applied Geography, Jun 2023

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Augmenting EV Charging Infrastructure towards Transformative Sustainable Cities: An Equity-Based Approach

Sujit Kumar Sikder, Magesh Nagarajan, and Navonil Mustafee

Technological Forecasting and Social Change, Nov 2023

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2022

Cellular Automata in Modeling and Predicting Urban Densification: Revisiting the Literature since 1971

Anasua Chakraborty, Sujit Sikder, Hichem Omrani, and 1 more author

Land, Jul 2022

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The creation of an accurate simulation of future urban growth is considered to be one of the most important challenges of the last five decades that involves spatial modeling within a GIS environment. Even though built-up densification processes, or transitions from low to high density, are critical for policymakers concerned with limiting sprawl, the literature on models for urban study reveals that most of them focus solely on the expansion process. Although the majority of these models have similar goals, they differ in terms of implementation and theoretical assumptions. Cellular automata (CA) models have been proven to be successful at simulating urban growth dynamics and projecting future scenarios at multiple scales. This paper aims to revisit urban CA models to determine the various approaches for a realistic simulation and prediction of urban densification. The general characteristics of CA models are described with respect to analysis of various driving factors that influence urban scenarios. This paper also critically analyzes various hybrid models based on CA such as the Markov chain, artificial neural network (ANN), and logistic regression (LR). Limitation and uncertainties of CA models, namely, neighborhood cell size, may be minimized when integrated with empirical and statistical models. The result of this review suggests that it is useful to use CA models with multinomial logistic regression (MLR) in order to analyze and model the effects of various driving factors related to urban densification. Realistic simulations can be achieved when multidensity class labels are integrated in the modeling process.
Spatializing Inequality across Residential Built-up Types: A Relational Geography of Urban Density in São Paulo, Brazil.

Alejandro De Castro Mazarro, Sujit Kumar Sikder, and Alexandra Aguiar Pedro

Habitat International, Jan 2022

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IOER Monitor: A Spatio-Temporal Research Data Infrastructure on Settlement and Open Space Development in Germany

Gotthard Meinel, Sujit Kumar Sikder, and Tobias Krueger

Jahrbücher für Nationalökonomie und Statistik, Feb 2022

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Abstract This paper gives a comprehensive introduction to the IOER Monitor – an open research data infrastructure (RDI) in Germany providing domain-specific multi-temporal geospatial datasets, services and visualizations for land use and land cover (LULC)-related development of settlements and open space and closely related topics. Its easy-to-use information system provides multi-scale data offers to form a discussion platform that supports spatial development assessment and evidence-based decision making. It contributes to public land-use change discourses by enhancing information offers that can be adopted by other multi-disciplinary data users - even from non-spatial domains. All data and services are freely available. IOER Monitor is committed to offering continuous services implementing FAIR principles (findable, accessible, interoperable and re-usable) and policy-relevant inputs for transformative spatial development.
Editorial: Data-Driven Approaches to Enable Urban Transformation

Sujit Kumar Sikder, Kh Md Nahiduzzaman, and Magesh Nagarajan

Frontiers in Sustainable Cities, Nov 2022

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2021

Revisiting Disaster Preparedness in Coastal Communities since 1970s in Bangladesh with an Emphasis on the Case of Tropical Cyclone Amphan in May 2020

Md. Tariqul Islam, Mark Charlesworth, Mohammad Aurangojeb, and 5 more authors

International Journal of Disaster Risk Reduction, May 2021

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The Cooperative Urban Land Development Model in Germany - An Effective Instrument to Support Affordable Housing

Theo Koetter, Sujit Kumar Sikder, and Dominik Weiss

Land Use Policy, Aug 2021

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Urban Transformation Toward a Smart City: An E-Commerce–Induced Path-Dependent Analysis

Kh Md Nahiduzzaman, Mark Holland, Sujit K. Sikder, and 3 more authors

Journal of Urban Planning and Development, Mar 2021

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Smart City in Bangladesh: Agenda of Spatial Data for Green Development

Sikder Sujit Kumar

Mar 2021

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An invited presentation at the Workshop on "Smart Village & City in Bangladesh",Organized by: Chittagong University of Engineering and Technology (CUET), Date: 27.03.2021

2020

An Infrastructure for Spatial Linking of Survey Data

Felix Bensmann, Lars Heling, Stefan Jünger, and 7 more authors

Data Science Journal, Jul 2020

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OPENGEOEDU – A MASSIVE OPEN ONLINE COURSE ON USING OPEN GEODATA

R. Bill, A. Lorenzen-Zabel, M. Hinz, and 8 more authors

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Aug 2020

Abs DOI

Abstract. This article presents the concept, implementation and results of the project "OpenGeoEdu", an open and web-based educational resource on Remote Sensing and GIS. OpenGeoEdu is focused on the use of open geodata in spatially oriented study courses. Teachers and students in the German-speaking countries are to be offered an open learning environment hoping to increase the motivation of students and researchers by dealing with current societal relevant issues. OpenGeoEdu is available at www.opengeoedu.de, has been offered as a MOOC since October 2018 and is being continuously expanded and developed. In addition, an umbrella portal of the portals on open geodata is available to quickly get an overview of the data offered. Four partners from universities, non-university research institutions as well as federal research authorities with R&D tasks are collaborating in this project offering case studies for teaching and education based on their experiences in a wide range of spatial applications.
Offene Daten für Lehre und Forschung in raumbezogenen Studiengängen - OpenGeoEdu : Abschlussbericht vom 07. Oktober 2020

Bill, Ralf, Lorenzen-Zabel, Axel, Hinz, Matthias, and 8 more authors

2020

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Housing and Human Settlements in a World of Change

2020
Urban Environmental Migrants: Demands for a Unique Category of Refugees to Ensure Their Right to Land and Resettlement

Syed Mukaddim and Zakir Hossain

In Housing and Human Settlements in a World of Change, Jul 2020

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Trends in Active and Sustainable Mobility: Experiences from Emerging Cycling Territories of Dhaka and Innsbruck

Rumana Islam Sarker, Golam Morshed, Sujit Kumar Sikder, and 1 more author

In Urban Ecology, 2020

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Analyse Der ÖPNV-Versorgung Mittels Offener Fahrplandaten – Potenziale, Herausforderungen Und Lösungsansätze

Sujit Kumar Sikder, Nico Ehrig, Hendrik Herold, and 1 more author

2020

Abs DOI

Auf der Basis öffentlich und frei verfügbarer Fahrplandaten stellt dieser Beitrag ein Konzept für einen kleinräumigen Indikator (1 km^2-Raster) zur ÖPNV-Versorgung vor. Grundlage dieser Studie sind Fahrplandaten des öffentlichen Personenverkehrs im digitalen Austauschformat General Transit Feed Service (GTFS). Mithilfe dieser Daten können ÖPNV-Haltestellen verortet und die Bedienfrequenzen der angebotenen Verkehrsmittelarten ermittelt werden. Die Untersuchung erfolgt am Beispiel des Mitteldeutschen Verkehrsverbundes (MDV), welcher die Großstädte Leipzig und Halle, Mittel- und Kleinstädte sowie ländliche Gebiete umfasst. Für die Datenanalyse wird die räumliche Verteilung mittels GINI und Moran‘s I nach Siedlungsstrukturtypen untersucht.
Transition to the New Normal: Lens on the Urban Spatial Data Science Agenda

Sujit Kumar Sikder

Journal of Urban Management, Dec 2020

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2019

Walking to a Public Transport Station: Empirical Evidence on Willingness and Acceptance in Munich, Germany

Rumana Islam Sarker, Markus Mailer, and Sujit Kumar Sikder

Smart and Sustainable Built Environment, Feb 2019

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Purpose The purpose of this paper is to explore the actual walking distance to public transport (PuT) stations and to report passenger perceptions on route choice. Design/methodology/approach A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). It can determine the interrelation between the accessibility of the transit service and evaluation on walking distance acceptance. Statistical analysis and geo-spatial approach were completed for obtaining major findings. Findings Statistical and geo-spatial analysis shows that respondents living in low-density areas walk longer than residents living in nearby inner city areas. In terms of PuT modes, residents walk longer for suburban train and subway/metro (U-Bahn) than for bus/tram services. Transit users accept a longer walking distance to reach a train station than other PuT modes and they choose the most direct and quickest route to reach PuT stations. Research limitations/implications Findings of this study would help to formulate future strategies and standards for the sustainable planning of public transportation systems in the context of Munich and many other cities around the globe with similar conditions. However, future research should be conducted using a large-scale survey for evaluating the comprehensive picture of walking patterns to PuT stations. Accessibility to PuT stations can also be modeled and evaluated by adopting open data and voluntary social media information. Unfortunately, this study only presents a partial evaluation of walking focused on accessibility at selected PuT stations in different settings of the urban fabric. Social implications This empirical study can be considered as an initial finding in the favor of the city transport authority to provide a design scale for improved accessibility of transit users; however, further investigation should be conducted using a large-scale survey for evaluating the comprehensive walking patterns. Originality/value A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). Findings of this study would help to formulate future strategies and standard for the sustainable planning of the public transportation system in the context of Munich and many other cities in the globe with similar conditions.
Measuring urban human activity intensity in the context of data scarcity

Sujit Kumar Sikder, Hendrik Herold, Gotthard Meinel, and 1 more author

Dec 2019

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We estimate the dynamic development of urban human activity in case of Bangladesh. The country is suffering to manage a sustainable pathway of spatial development due to the high-level vulnerability of global environmental challenges along with local social, demographic and geopolitical dilemmas. New-urbanism literature suggested to measure Urban Human Activity Intensity (UHAI) by integration of (i) density factors, (ii) network connectivity factors, and (iii) land-use mix factors. This contribution is reporting some initial findings in consideration of statistical urban area of Bangladesh.
Geospatial Analysis of Building Structures in Megacity Dhaka: The Use of Spatial Statistics for Promoting Data-Driven Decision-Making

Sujit Kumar Sikder, Martin Behnisch, Hendrik Herold, and 1 more author

Journal of Geovisualization and Spatial Analysis, Apr 2019

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Information on spatial building structures is limited, but it can support efficient planning and management in the context of fast-growing big cities in many developing countries. In this paper, we present a spatial analysis approach that includes an estimate of building intensity in the megacity of Dhaka and a spatial analysis using spatial statistics. The entire city was divided into regular grids and the building intensity (both horizontal and vertical) was extracted using vector type building information; the spatial statistics were calculated on the basis of Moran’s I and Gini indices. The variability of the estimated spatial statistics is interpreted according to co-relationship or clustering patterns with the location of the central business district (CBD) area as well as the public bus transit infrastructure (routes and stops). The results show that the residential building structure intensity is prominent and the concentrations are distributed all over the city. The mixed-use type building structures show highest clustering, with fewer outliers in the old part of the city. The vertical-use intensities indicate extreme clustering within highly intensified building activity in the nearby CBD area. The higher presence of low-low clustering of horizontal intensity indicated low development at the suburban area. However, the strongly clustered grid cells within residential sector as well as horizontal development classes are less accessible by bus transit within a defined catchment area, whereas the service sector and vertical development type seem to be more accessible. This type of geographic approach, visualization, and statistical information can help in making data-driven planning decisions with the advantage of monitoring urban development; however, the modeling sensitivity and uncertainties in the building data set remain open for further investigation.

2018

Forecast of Municipal Housing Demand: An Introduction to the IOER - Online Program" Kommunale Wohnungsnachfrageprognose" and Its Adoption Potential

Daniel Eichhorn, Sujit Kumar Sikder, and Gotthard Meinel

Nov 2018

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Housing markets develop very heterogeneously, with some trends even running in opposite directions. It is vital to consider the local trend of each municipality in order to capture dynamic developments in the housing market. This paper presents a method of forecasting demand for municipal housing. It has discussed about the adoption potential of such method to the regional or even international level. Since 2002, the IOER has been operating a web-based program to forecast municipal housing demand called "Kommunale Wohnungsnachfrageprognose". This is an open access forecasting platform that supports individual module-based forecasts of population, household patterns, housing offer and housing demand. Potential users can customize the forecasting of housing demand according to three different types of households and up to seven categories of housing market. Individual forecasts can be simulated for multiple scenarios. After choosing a base year, the user is given estimates for five-year periods in each forecasting module, up to a final forecasting horizon of 15 years. Generally, the individual forecasting method can be implemented using local municipal statistics as input data. For the last 17 years, this open access online service has helped many municipalities in eastern Germany to draw up an integrated urban development concept in the context of the federal programme "Stadtumbau Ost". An extension of the online service includes specific regional parameters to forecast housing demand for municipalities in western Germany. The service provides support to perform simplified forecasting of trends in the housing market for Polish and Czech municipalities and for small municipalities at the national border. The method can also be transferred to other countries or regions. To realize this, an initial study must be performed to determine specific basic parameters such as birth rate, mortality rate, household trends or housing patterns for different spatial scales and dimensions. These then can easily be implemented within scope of the online program.
Halten Sie die Augen nach einer Ladestation offen! - Die E-Ladestations- Infrastruktur in Deutschland: eine räumliche Analyse

Sujit Kumar Sikder, Hendrik Herold, and Gotthard Meinel

Jul 2018

DOI
Infrastrukturplanung mit verkehrsbezogenen Flächennutzungsindikatoren

Sujit Kumar Sikder, Hendrik Herold, and Gotthard Meinel

In , 2018

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Die Geodatendienste des IÖR-Monitors stellten bundesweit Indikatoren zur Flächennutzungsstruktur sowie der verkehrsbezogenen Infrastruktur bereit. Diese Daten können unter anderem für die Infrastrukturplanung genutzt werden. Ziel dieses Beitrages ist es, die räumliche Variabilität der aktuellen Ladestationspunkte (Electric Vehicle Charging Points: ECP) als Teil der zukünftigen Elektromobilitätsinfrastruktur bundesweit zu analysieren. Die explorative Analyse wird auf Kreisebene mithilfe eines hybriden Datensatzes, d. h. einer Kombination von offenen, amtlichen und nutzergenerierten (VGI) Daten-quellen durchgeführt. Sie umfasst die Analyse der Datenqualität, die Extraktion räumlicher Muster sowie die Erstellung deskriptiver Statistiken. Die höchste Konzentration von ECP gibt es erwartungsgemäß in den Großstädten, davon am meisten in den großen Ballungsräumen. Die bivariate Korrelationsanalye zeigt, dass der Anteil Verkehrsfläche an Gebietsfläche eine robuste Prädiktorvariable des IÖR-Monitors ist. Zur Erstellung deskriptiver Statistiken, zur Extraktion räumlicher Muster und deren Darstellung in Karten und Grafiken wurden ausschließlich offene und frei verfügbare analytische Softwarewerkzeuge eingesetzt. EN: — The geospatial services of the IÖR-Monitor provided nationwide indicators of land-use structure and transport-related infrastructure. These data can be used, among other purposes, for infrastructure planning. The aim of this paper is to analyse the spatial variability of existing electric vehicle charging points (ECPs) nationwide as part of the future electric mobility infrastructure. The exploratory analysis is conducted at the district level using a hybrid dataset, i.e., a combination of open, official, and volunteered geographic information (VGI) data sources. It includes an assessment of data quality, the extraction of spatial patterns, and the generation of descriptive statistics. As expected, the highest concentrations of ECPs are found in large cities, particularly in major metropolitan areas. The bivariate correlation analysis shows that the proportion of transport land relative to the total area is a robust predictor variable provided by the IÖR-Monitor. Open-source and freely available analytical software tools were used exclusively to generate descriptive statistics, extract spatial patterns, and visualise the results using maps and charts.
A Geospatial Approach of Downscaling Urban Energy Consumption Density in Mega-City Dhaka, Bangladesh

S. K. Sikder, M. Nagarajan, S. Kar, and 1 more author

Urban Climate, Dec 2018

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Lack of energy consumption data limits resource optimized urban structure and energy planning in developing countries like Bangladesh. Focusing on mega-city Dhaka as a case, this study applies a geospatial approach of using multi-source national and regional datasets and visual analytics to downscale and estimate energy consumption at a local scale (such as ward and gridcell). The energy consumption density (ECD), as a measure of end energy use in a unit area, was estimated and mapped by linking building floorspace data with residents’ energy use indicators such as per capita energy consumption, household energy expenditure, and mobility (transportation) pattern. This study also evaluated the ECD modelling outputs, and their sensitivity to distance from central business district (CBD) and total building floorspace. Results found a positive correlation between the residential building floorspace and estimated ECD. Regression and sensitivity analysis also identified and mapped significant spatial clusters and outliers in estimated ECD pattern of Dhaka city. This approach and methodology could help similar cities in other developing countries adopt and implement energy focused urban development.

2016

The Contribution of Energy-Optimized Urban Planning to Efficient Resource Use–A Case Study on Residential Settlement Development in Dhaka City, Bangladesh

Sujit Sikder, Francis Eanes, Henok Asmelash, and 2 more authors

Sustainability, Feb 2016

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This study examines and explores the contribution of an energy-optimized urban planning approach to efficient resource use in the context of Dhaka city, Bangladesh. A conceptual energy optimization model called the “EnUp” model has been developed and tested for feasibility and adaptation strategies to improve urban energy use in residential settlements. This study is based on a system analysis and grounded theory approach that involved field methods including key informant (KI) interviews and collection of data and information from local urban planning offices and other secondary sources. Results show that the adoption of an energy-optimized planning approach is possible and necessary in Dhaka city. The “EnUp“ model can be applied in new urban settlement planning and retrofitting existing urban settlements. Ensuring various stakeholders’ participation, technical inputs, and adaptability could make this innovative model and approach replicable in many other cities in the world. The study facilitates a better documentation and visualization for comprehensive urban planning and energy planning process in developing countries, while providing useful insights to policy makers, planners, developers, and interested urban stakeholders in the transition to urban sustainability.

2015

Urban Planning in the Age of Urban Energy Transition - What Is Going on in Mega-City Dhaka, Bangladesh?

Sujit Kumar Sikder and Theo Kortter

May 2015

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The transition of urban energy systems to inform sustainable urban planning scholarship is a popular topic of discussion. The related issues of urban form, energy efficiency and modern technologies have already been studied under different urban configurations and scales. Consequently, the energy integrated urban development policies are being adopted - at least in principal- by several urban authorities. However, this paper explores around the topic of urban planning in the context of energy transition by conceptualizing the case of residential settlement planning process and development systems of Mega city Dhaka are discussed. It is widely accepted that each urban residential project is unique within the general systems approach of sustainability. Such schemes at neighbourhood scale are also good starting point or pre-condition to create a truly sustainable community - because all new buildings and facilities are constructed there. Within the scope of this paper, the questions “what is goingon?” has addressed by adopting system analysis approach. All data used from secondary sources and key informant interviews with officials, developers, professionals and experts. The case study found that the urban planning has promising potentials for urban energy system transition even in the context of urban Bangladesh. But there are different identified challenges such as capacity building, professionalism and more others have to be addressed. From the technical point of view, there is a growing need for adopting an optimal urban planning framework along with methods, models and tools. The high quality data gap to urban planning and development control in the age of energy transition also has to be tackled.

2014

Assessing Site Selection of New Towns Using TOPSIS Method under Entropy Logic: A Case Study: New Towns of Tehran Metropolitan Region (TMR)

Asad Asadzadeh, Sujit Kumar Sikder, Farzin Mahmoudi, and 1 more author

Environmental Management and Sustainable Development, Feb 2014

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2008

Application of GIS in Urban Solid Waste Management: A Case Study in KCC

Kausik Das and Sujit Kumar Sikder

Feb 2008

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Urban solid waste management is considered as one of the most immediate and serious environmental problems confronting municipal authorities in developing countries like Bangladesh. A standard solid waste management should provide hygienic, efficient and economic collection, transportation and disposal of solid waste without polluting atmosphere. To ensure this standard management system GIS can be used as an effective tool in selecting suitable disposal sites and identifying the optimum routes for transportation. Suitable disposal sites and the optimum routes must have environmental safety criteria and attributes that will enable the wastes to be isolated so that there is no unacceptable risk to people or the environment while it is operating. The location of disposal sites of Khulna City Corporation represents the unconsciousness about the environmental and public health hazards. Response to this GIS here provides an opportunity to integrate spatial, aspatial data and other relevant data to select suitable disposal sites and identify optimum routes for transportation of solid waste. At this juncture GIS act as an important decision support system.

Blessings of Open Data and Technology: E-Learning Examples on Land Use Monitoring and E-Mobility

Sikder, Sujit Kumar , Dresden, Germany), Herold, Hendrik , Dresden, Germany), Meinel, G. , Dresden, Germany), and 2 more authors

DOI