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

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 t...

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Main Authors: Hyuksoo Kwon, Bumsuk Seo, Jungin Kim, Heera Lee
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/14/1/169
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author Hyuksoo Kwon
Bumsuk Seo
Jungin Kim
Heera Lee
author_facet Hyuksoo Kwon
Bumsuk Seo
Jungin Kim
Heera Lee
author_sort Hyuksoo Kwon
collection DOAJ
description 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.
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spelling doaj-art-3cf65f3e653e4f9aadf46b42269abf702025-01-24T13:38:10ZengMDPI AGLand2073-445X2025-01-0114116910.3390/land14010169Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field ObservationsHyuksoo Kwon0Bumsuk Seo1Jungin Kim2Heera Lee3Ecosystem Service Team, Division of Ecological Assessment Research, National Institute of Ecology, 1210 Geumgang-ro, Maseo-myeon, Seocheon-gun 33657, Republic of KoreaInstitute of Construction and Environmental Engineering (ICEE), Seoul National University, 316 dong 307 ho, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of KoreaEcosystem Service Team, Division of Ecological Assessment Research, National Institute of Ecology, 1210 Geumgang-ro, Maseo-myeon, Seocheon-gun 33657, Republic of KoreaDepartment of Forestry and Landscape Architecture, College of Sang-Huh Life Science, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of KoreaCultural 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.https://www.mdpi.com/2073-445X/14/1/169crowdsourced dataiNaturalistvisitor statisticsspatial point pattern analysisCross-KGlobal Biodiversity Information Facility
spellingShingle Hyuksoo Kwon
Bumsuk Seo
Jungin Kim
Heera Lee
Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
Land
crowdsourced data
iNaturalist
visitor statistics
spatial point pattern analysis
Cross-K
Global Biodiversity Information Facility
title Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
title_full Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
title_fullStr Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
title_full_unstemmed Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
title_short Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
title_sort crowdsourced indicators of flora and fauna species comparisons between inaturalist records and field observations
topic crowdsourced data
iNaturalist
visitor statistics
spatial point pattern analysis
Cross-K
Global Biodiversity Information Facility
url https://www.mdpi.com/2073-445X/14/1/169
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