Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations

Hyuksoo Kwon, Bumsuk Seo, Jungin Kim and Heera Lee ()
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Hyuksoo Kwon: Ecosystem Service Team, Division of Ecological Assessment Research, National Institute of Ecology, 1210 Geumgang-ro, Maseo-myeon, Seocheon-gun 33657, Republic of Korea
Bumsuk Seo: Institute of Construction and Environmental Engineering (ICEE), Seoul National University, 316 dong 307 ho, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
Jungin Kim: Ecosystem Service Team, Division of Ecological Assessment Research, National Institute of Ecology, 1210 Geumgang-ro, Maseo-myeon, Seocheon-gun 33657, Republic of Korea
Heera Lee: Department of Forestry and Landscape Architecture, College of Sang-Huh Life Science, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea

Land, 2025, vol. 14, issue 1, 1-22

Abstract: Cultural ecosystem services provide intangible benefits such as recreation and aesthetic enjoyment but are difficult to quantify compared to provisioning or regulating ecosystem services. Recent technologies offer alternative indicators, such as social media data, to identify popular locations and their features. This study demonstrates how large volumes of citizen science and social media data can be analyzed to reveal patterns of human interactions with nature through unconventional, scalable methods. By applying spatial statistical methods, data from the citizen science platform iNaturalist are analyzed and compared with ground-truth visitation data. To minimize data bias, records are grouped by taxonomic information and applied to the metropolitan area of Seoul, South Korea (2005–2022). The taxonomic information included in the iNaturalist data were investigated using a standard global biodiversity database. The results show citizen science data effectively quantify public preferences for scenic locations, offering a novel approach to mapping cultural ecosystem services when traditional data are unavailable. This method highlights the potential of large-scale citizen-generated data for conservation, urban planning, and policy development. However, challenges like bias in user-generated content, uneven ecosystem coverage, and the over- or under-representation of locations remain. Addressing these issues and integrating additional metadata—such as time of visit, demographics, and seasonal trends—could provide deeper insights into human–nature interactions. Overall, the proposed method opens up new possibilities for using non-traditional data sources to assess and map ecosystem services, providing valuable information for conservation efforts, urban planning, and environmental policy development.

Keywords: crowdsourced data; iNaturalist; visitor statistics; spatial point pattern analysis; Cross-K; Global Biodiversity Information Facility (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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