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Maryam Lotfian Obtained her BSc in Geomatics Engineering from Tehran University (Iran) in 2013. In 2016, she received her MSc in Environmental and Geomatics Engineering from Politecnico di Milano (Italy) with a thesis on urban climate classification using satellite imagery. In collaboration with the University of Applied Sciences and Arts Western Switzerland (HEIG-VD), she began her PhD at the Politecnico di Milano Department of Civil and Environmental Engineering in October 2017. Her research focuses on challenges in citizen science projects, including participants’ motivations and data quality. She works on developing machine learning algorithms to perform automated data validation in citizen scientist projects.
Advances in artificial intelligence (AI) and the extension of citizen science to various scientific areas, as well as the generation of big citizen science data, are resulting in AI and citizen science being good partners, and their combination benefits both fields. The integration of AI and citizen science has mostly been used in biodiversity projects, with the primary focus on using citizen science data to train machine learning (ML) algorithms for automatic species identification. In this article, we will look at how ML techniques can be used in citizen science and how they can influence volunteer engagement, data collection, and data validation. We reviewed several use cases from various domains and categorized them according to the ML technique used and the impact of ML on citizen science in each project. Furthermore, the benefits and risks of integrating ML in citizen science are explored, and some recommendations are provided on how to enhance the benefits while mitigating the risks of this integration. Finally, because this integration is still in its early phases, we have proposed some potential ideas and challenges that can be implemented in the future to leverage the power of the combination of citizen science and AI, with the key emphasis being on citizen science in this article.
Maryam Lotfian; Jens Ingensand; Maria Brovelli. The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality. Sustainability 2021, 13, 8087 .
AMA StyleMaryam Lotfian, Jens Ingensand, Maria Brovelli. The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality. Sustainability. 2021; 13 (14):8087.
Chicago/Turabian StyleMaryam Lotfian; Jens Ingensand; Maria Brovelli. 2021. "The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality." Sustainability 13, no. 14: 8087.
Citizen science, the participation of the public in scientific projects, is growing significantly, especially with technological developments in recent years. Volunteers are the heart of citizen science projects; therefore, understanding their motivation and how to sustain their participation is the key to success in any citizen science project. Studies on participants of citizen science projects illustrate that there is an association between participant motivation and the type of contribution to projects. Thus, in this paper, we define a motivational framework, which classifies participant motivation taking into account the typologies of citizen science projects. Within this framework, we also take into account the importance of motivation in initiating and sustaining participation. This framework helps citizen science practitioners to have comprehensive knowledge about potential motivational factors that can be used to recruit participants, as well as sustaining participation in their projects.
Maryam Lotfian; Jens Ingensand; Maria Antonia Brovelli. A Framework for Classifying Participant Motivation that Considers the Typology of Citizen Science Projects. ISPRS International Journal of Geo-Information 2020, 9, 704 .
AMA StyleMaryam Lotfian, Jens Ingensand, Maria Antonia Brovelli. A Framework for Classifying Participant Motivation that Considers the Typology of Citizen Science Projects. ISPRS International Journal of Geo-Information. 2020; 9 (12):704.
Chicago/Turabian StyleMaryam Lotfian; Jens Ingensand; Maria Antonia Brovelli. 2020. "A Framework for Classifying Participant Motivation that Considers the Typology of Citizen Science Projects." ISPRS International Journal of Geo-Information 9, no. 12: 704.
Precipitation is one of the main stages of the water cycle, and it is required for the organisms to survive on the planet. In contrast, air pollution is a phenomenon that has greatly affected the human life nowadays. Population growth, development of factories and increasing number of fossil fuel vehicles are the most influencing factors on air pollution. In addition to understand nature of precipitation and air pollution, finding relationship between these two phenomena is necessary to make appropriate policies for reducing air pollution. Furthermore, studying trends of precipitation and air pollution in the past, is helpful to forecast the times and places with less precipitation and more air pollution for a better urban management. In this study, we tried to extract any probable relationship between these two parameters by investigating their monthly measured amounts in 22 municipal districts of Tehran in three epochs of time (2009, 2013 and 2017). Carbon Monoxide (CO) was considered as the indicator of air pollution. Results of the study show that the parameters have a significant relationship with each other. By using Pearson Correlation Coefficient and One-Way Variance (ANOVA) test, relationship between the data for each month and for each district of Tehran were studied separately. As the time has passed and the air pollution has increased, the correlation between the parameters in districts has decreased. In addition, during the cold months of the year, the correlations decrease since the fact that precipitation is not the only influencing factor on the air pollution due to the rise of air “Inversion”. Finally, the polynomial regression model of carbon monoxide based on precipitation was extracted for each of the three years. The model suggests a degree three polynomial equation. The obtained coefficients from the regression model show that the relationship between parameters was stronger in the years with more rainfalls. This can be due to the more significant impact of other influencing factors on air pollution, such as population density, wind direction, vehicles and factories in the areas or conditions with a less rainfall.
Shokouh Dareshiri; Mohammadreza Sahelgozin; Maryam Lotfian; Jens Ingensand. Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis. Proceedings of the ICA 2019, 2, 1 -7.
AMA StyleShokouh Dareshiri, Mohammadreza Sahelgozin, Maryam Lotfian, Jens Ingensand. Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis. Proceedings of the ICA. 2019; 2 ():1-7.
Chicago/Turabian StyleShokouh Dareshiri; Mohammadreza Sahelgozin; Maryam Lotfian; Jens Ingensand. 2019. "Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis." Proceedings of the ICA 2, no. : 1-7.
Data quality is the primary concern for researchers working on citizen science projects. The collected data by citizen science participants are heterogeneous and therefore must be validated. There are several validation approaches depending on the theme and objective of the citizen science project, but the most common approach is the expert review. While expert validation is essential in citizen science projects, considering it as the only validation approach can be very difficult and complicated for the experts. In addition, volunteers can get demotivated to contribute if they do not receive any feedback regarding their submissions. This project aims at introducing an automatic filtering mechanism for a biodiversity citizen science project. The goals of this project are to first use an available historical database of the local species to filter out the unusual ones, and second to use machine learning and image recognition techniques to verify if the observation image corresponds with the right species type. The submissions that does not successfully pass the automatic filtering will be flagged as unusual and goes through expert review. The objective is on the one hand to simplify validation task by the experts, and on the other hand to increase participants’ motivation by giving them real-time feedback on their submissions. Finally, the flagged observations will be classified as valid, valid but uncommon, and invalid, and the observation outliers (rare species) can be identified for each specific region.
Maryam Lotfian; Jens Ingensand; Olivier Ertz; Simon Oulevay; Thibaud Chassin. Auto-filtering validation in citizen science biodiversity monitoring: a case study. Proceedings of the ICA 2019, 2, 1 -5.
AMA StyleMaryam Lotfian, Jens Ingensand, Olivier Ertz, Simon Oulevay, Thibaud Chassin. Auto-filtering validation in citizen science biodiversity monitoring: a case study. Proceedings of the ICA. 2019; 2 ():1-5.
Chicago/Turabian StyleMaryam Lotfian; Jens Ingensand; Olivier Ertz; Simon Oulevay; Thibaud Chassin. 2019. "Auto-filtering validation in citizen science biodiversity monitoring: a case study." Proceedings of the ICA 2, no. : 1-5.
This paper aims at underling difficulties regarding the establishment of citizen engagement processes. The specificity of citizen engagement processes lies in their evolution over time where objectives, constraints, and latitudes of a given project influence the relevance of the tools offered to citizens. Three categories of urban projects (trans-urban, major metropolitan, architectural design) have been described. These classes range from a local space with short deadlines to a regional space spread over several decades. Furthermore, the use of 3D platforms for a broad public is influenced by the users’ preferences, perception, and expertise. Throughout this study, major challenges that have been experienced during the design a 3D participatory platform are identified. They range from the issues of implementing adequate tools according to the project (temporal and spatial scalability), the participation forms (passive, consultative or interactive), to the difficulties of convincing the authorities to use new bottom-up methods. Finally, a conceptual framework for the creation of a 3D participatory platform has been introduced. It can be summarized by three major steps: (1) Meeting the needs of a decision maker, (2) Designing the participation tool in accordance with the context, (3) Translating collected raw data in order to respond to the initial request.
Thibaud Chassin; Jens Ingensand; Maryam Lotfian; Olivier Ertz; Florent Joerin. Challenges in creating a 3D participatory platform for urban development. Advances in Cartography and GIScience of the ICA 2019, 1, 1 -8.
AMA StyleThibaud Chassin, Jens Ingensand, Maryam Lotfian, Olivier Ertz, Florent Joerin. Challenges in creating a 3D participatory platform for urban development. Advances in Cartography and GIScience of the ICA. 2019; 1 ():1-8.
Chicago/Turabian StyleThibaud Chassin; Jens Ingensand; Maryam Lotfian; Olivier Ertz; Florent Joerin. 2019. "Challenges in creating a 3D participatory platform for urban development." Advances in Cartography and GIScience of the ICA 1, no. : 1-8.
Maryam Lotfian. The relationship between land surface temperature and local climate zone classification: A case study of the canton Geneva, Switzerland. 2019, 1 .
AMA StyleMaryam Lotfian. The relationship between land surface temperature and local climate zone classification: A case study of the canton Geneva, Switzerland. . 2019; ():1.
Chicago/Turabian StyleMaryam Lotfian. 2019. "The relationship between land surface temperature and local climate zone classification: A case study of the canton Geneva, Switzerland." , no. : 1.
Climate issues are nowadays one of the most pressing societal challenges, with cities being identified among the landmarks for climate change. This study investigates the effect of urban land cover composition on a relevant climate-related variable, i.e., the air temperature. The analysis exploits different big geo-data sources, namely high-resolution satellite imagery and in-situ air temperature observations, using the city of Milan (Northern Italy) as a case study. Satellite imagery from the Landsat 8, Sentinel-2, and RapidEye missions are used to derive Local Climate Zone (LCZ) maps depicting land cover compositions across the study area. Correlation tests are run to investigate and measure the influence of land cover composition on air temperature. Results show an underlying connection between the two variables by detecting an average temperature offset of about 1.5 ∘ C between heavily urbanized and vegetated urban areas. The approach looks promising in investigating urban climate at a local scale and explaining effects through maps and exploratory graphs, which are valuable tools for urban planners to implement climate change mitigation strategies. The availability of worldwide coverage datasets, as well as the exclusive use of Free and Open Source Software (FOSS), provide the analysis with a potential to be empowered, replicated, and improved.
Daniele Oxoli; Giulia Ronchetti; Marco Minghini; Monia Elisa Molinari; Maryam Lotfian; Giovanna Sona; Maria Antonia Brovelli. Measuring Urban Land Cover Influence on Air Temperature through Multiple Geo-Data—The Case of Milan, Italy. ISPRS International Journal of Geo-Information 2018, 7, 421 .
AMA StyleDaniele Oxoli, Giulia Ronchetti, Marco Minghini, Monia Elisa Molinari, Maryam Lotfian, Giovanna Sona, Maria Antonia Brovelli. Measuring Urban Land Cover Influence on Air Temperature through Multiple Geo-Data—The Case of Milan, Italy. ISPRS International Journal of Geo-Information. 2018; 7 (11):421.
Chicago/Turabian StyleDaniele Oxoli; Giulia Ronchetti; Marco Minghini; Monia Elisa Molinari; Maryam Lotfian; Giovanna Sona; Maria Antonia Brovelli. 2018. "Measuring Urban Land Cover Influence on Air Temperature through Multiple Geo-Data—The Case of Milan, Italy." ISPRS International Journal of Geo-Information 7, no. 11: 421.
The public participation in scientific projects (citizen science) is significantly increasing specially with technology developments in recent years. Volunteers play an essential role in citizen science projects, therefore understanding their motivations, and understanding how to sustain them to keep contributing to the project are of utmost importance. This paper presents the analysis of volunteers’ characteristics and their motivations to contribute to a citizen science project, which aims at encouraging citizens to take action for biodiversity. The results from the online survey illustrate that people are more motivated by intrinsic nature-related motives rather than extrinsic motivations.
Maryam Lotfian; Jens Ingensand; Olivier Ertz; Sarah Composto; Mathias Oberson; Simon Oulevay; David Campisi; Florent Joerin. Participants’ motivations to contribute to biodiversity citizen science projects. 2018, 1 .
AMA StyleMaryam Lotfian, Jens Ingensand, Olivier Ertz, Sarah Composto, Mathias Oberson, Simon Oulevay, David Campisi, Florent Joerin. Participants’ motivations to contribute to biodiversity citizen science projects. . 2018; ():1.
Chicago/Turabian StyleMaryam Lotfian; Jens Ingensand; Olivier Ertz; Sarah Composto; Mathias Oberson; Simon Oulevay; David Campisi; Florent Joerin. 2018. "Participants’ motivations to contribute to biodiversity citizen science projects." , no. : 1.
Maryam Lotfian. Augmented reality technologies for biodiversity education. 2018, 1 .
AMA StyleMaryam Lotfian. Augmented reality technologies for biodiversity education. . 2018; ():1.
Chicago/Turabian StyleMaryam Lotfian. 2018. "Augmented reality technologies for biodiversity education." , no. : 1.
Being one of the most controversial issues in urban planning, land use planning has always been in the focus of researches. Land use planning is a subdivision of urban planning which tends to arrange land uses in order to avoid conflicts among them. In order to achieve a transparent and effective urban planning, land uses should be located and allocated in an ideal situation so that avoid negative impacts from neighbouring parcels and land uses. Neighbouring land uses can produce externalities and negative impacts on other land uses because of inter-land use interaction. These externalities may be undesirable effects such as noise, air and visual pollution or may be caused by hazardous facilities. The main objective of this research is to propose a new multi-criteria evaluation model for land use compatibility assessment. Considering the fact that a considerable number of factors affect the compatibility degree of neighbouring land uses, a multi-criteria evaluation approach is employed to address the aforementioned problem. This research employs the integration of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Ordered Weighted Averaging (OWA) methods to facilitate land use compatibility evaluation with respect to optimism degree. The applicability of the proposed model is illustrated by the problem of land use compatibility assessment for elementary schools in Tehran. The results indicate that most of the current schools are situated in a location which is incompatible for the land use type of elementary school especially in the southern and central parts of the city.
A. Abedini; M. Lotfian; M. Moradi. LAND USE COMPATIBILITY ASSESSMENT USING A MDIFIED TOPSIS MODEL: A CASE STUDY OF ELEMENTARY SCHOOLS IN TEHRAN. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2015, XL-1/W5, 5 -10.
AMA StyleA. Abedini, M. Lotfian, M. Moradi. LAND USE COMPATIBILITY ASSESSMENT USING A MDIFIED TOPSIS MODEL: A CASE STUDY OF ELEMENTARY SCHOOLS IN TEHRAN. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2015; XL-1/W5 ():5-10.
Chicago/Turabian StyleA. Abedini; M. Lotfian; M. Moradi. 2015. "LAND USE COMPATIBILITY ASSESSMENT USING A MDIFIED TOPSIS MODEL: A CASE STUDY OF ELEMENTARY SCHOOLS IN TEHRAN." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W5, no. : 5-10.