An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency

Olteanu‐Raimond, Ana‐Maria; Jolivet, Laurence; Damme, Marie-Dominque Van; Royer, Timothée; Fraval, Ludovic; See, Linda; Sturn, Tobias; Karner, Mathias; Moorthy, Inian; Fritz, Steffen

doi:10.3390/land7030103

Cited by 11 publications

(6 citation statements)

References 22 publications

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“…The construction of materials, the maintenance of an interactive website, smartphone apps, and continuous email contact requires considerable resources, especially in terms of staff with relevant experience in science and education. More recent projects like the School of Ants (Lucky et al, 2014 ), LandSense (Olteanu-Raimond et al, 2018 ), and eMammal (Schuttler et al, 2019 ) have mirrored the success of these large-scale schools projects, while national schools-based citizen science projects in the future are likely to tackle aspects of post-pandemic life (Eichler et al, 2020 ; Ugolini et al, 2020 ). Smaller contributory projects sometimes lack such infrastructure and resources and, consequently, participants are often only involved in data collection without gaining experience of the complete inquiry process (Jenkins et al, 2015 ).…”

Section: Challenges For Citizen Science Education and Learningmentioning

confidence: 99%

Citizen Science, Education, and Learning: Challenges and Opportunities

et al. 2020

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Citizen science is a growing field of research and practice, generating new knowledge and understanding through the collaboration of citizens in scientific research. As the field expands, it is becoming increasingly important to consider its potential to foster education and learning opportunities. Although progress has been made to support learning in citizen science projects, as well as to facilitate citizen science in formal and informal learning environments, challenges still arise. This paper identifies a number of dilemmas facing the field—from competing scientific goals and learning outcomes, differing underlying ontologies and epistemologies, diverging communication strategies, to clashing values around advocacy and activism. Although such challenges can become barriers to the successful integration of citizen science into mainstream education systems, they also serve as signposts for possible synergies and opportunities. One of the key emerging recommendations is to align educational learning outcomes with citizen science project goals at the planning stage of the project using co-creation approaches to ensure issues of accessibility and inclusivity are paramount throughout the design and implementation of every project. Only then can citizen science realise its true potential to empower citizens to take ownership of their own science education and learning.

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Section: Challenges For Citizen Science Education and Learningmentioning

confidence: 99%

Citizen Science, Education, and Learning: Challenges and Opportunities

et al. 2020

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“…Crowd-sensed and crowd-sourced data can also be used for mapping urban environments by creating accurate surface maps (Fan et al 2019), 3D city models (Bshouty et al 2019), or by exploring heat patterns (Yin et al 2021). Such information can help decision-makers to find sustainable solutions for land administration (Du et al 2021;Olteanu-Raimond et al 2018), urban green space planning and management (Heikinheimo et al 2020;Schrammeijer et al 2022), human mobility improvement (Hologa and Riach 2020; Howe 2021), or heritage building management (Brigham et al 2018;Lamas et al 2021).…”

Section: Results and Interpretationmentioning

confidence: 99%

The role of citizen science mobile apps in facilitating a contemporary digital agora

Hognogi,

Meltzer,

Alexandrescu

et al. 2023

Humanit Soc Sci Commun

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The advancements in digital technologies, especially for mobile apps, enabled simplified data collection methods. Consequently, through Citizen Science, numerous opportunities arose for citizens to become contributors and not just beneficiaries of scientific research. Furthermore, through such engagement, citizens can participate in decision-making processes at different spatial scales, getting closer to the civic aspiration of a digital agora. This paper offers a systematic review of 303 studies on such initiatives to outline the potential of mobile apps in Citizen Science. Based distinctly on their specificities and the needs they address, three content categories were highlighted: a) monitoring tools, b) validation of techniques and methods to improve mobile technologies for Citizen Science, and c) participatory approaches of citizens employing mobile apps. The review also showed a susceptibility of several domains of activity towards Citizen Science, such as monitoring biodiversity and reconnecting people with nature, environmental risk monitoring or improving well-being. The findings highlight future research potential in addressing topics such as new technologies to increase Citizen Science performance and its contributions to Open Science, as well as diversification and enhancement of citizen scientists’ contributions.

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“…Concerning the change/no change accuracy assessment, it was, unfortunately, not possible for us to measure the omission of the change due to the lack of reference data. This issue can be tackled in the future by adding not only construction sites to the sample that have been provided by the change detection method but also other triggers coming from different VGI projects where citizens send in alerts when a change occurs [79].…”

Section: Discussionmentioning

confidence: 99%

Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change

et al. 2020

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Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done on a multi-year cycle due to the high costs involved, so changes are only detected when mapping exercises are repeated. Consequently, the information on LULC can quickly become outdated and hence may be incorrect in some areas. In the current era of big data and Earth observation, change detection algorithms can be used to identify changes in urban areas, which can then be used to automatically update LULC databases on a more continuous basis. However, the change detection algorithm must be validated before the changes can be committed to authoritative databases such as those produced by national mapping agencies. This paper outlines a change detection algorithm for identifying construction sites, which represent ongoing changes in LU, developed in the framework of the LandSense project. We then use volunteered geographic information (VGI) captured through the use of mapathons from a range of different groups of contributors to validate these changes. In total, 105 contributors were involved in the mapathons, producing a total of 2778 observations. The 105 contributors were grouped according to six different user-profiles and were analyzed to understand the impact of the experience of the users on the accuracy assessment. Overall, the results show that the change detection algorithm is able to identify changes in residential land use to an adequate level of accuracy (85%) but changes in infrastructure and industrial sites had lower accuracies (57% and 75 %, respectively), requiring further improvements. In terms of user profiles, the experts in LULC from local authorities, researchers in LULC at the French national mapping agency (IGN), and first-year students with a basic knowledge of geographic information systems had the highest overall accuracies (86.2%, 93.2%, and 85.2%, respectively). Differences in how the users approach the task also emerged, e.g., local authorities used knowledge and context to try to identify types of change while those with no knowledge of LULC (i.e., normal citizens) were quicker to choose ‘Unknown’ when the visual interpretation of a class was more difficult.

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An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency

Cited by 11 publications

References 22 publications

Citizen Science, Education, and Learning: Challenges and Opportunities

Citizen Science, Education, and Learning: Challenges and Opportunities

The role of citizen science mobile apps in facilitating a contemporary digital agora

Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change

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