Effects of Accessibility on the Records of Biodiversity Observation by the Citizens of Urban Forests

Abstract. The leveraging of social media for citizen science is a powerful tool for generating large-scale records of wildlife observations and engaging the public in biodiversity conservation. However, the utility of observation records is adversely affected by their biases. In particular, understanding the drivers behind observation hotspots—locations where observation records are concentrated—is vital for interpreting data and optimizing project design. This study investigated the factors forming observation hotspots in the urban forests of Tsukuba Science City, Japan, assuming that accessibility by humans is as important as ecological factors. We analyzed 17,224 observation records from a social media platform for citizen science across a 54-km2 study area and classified location accessibility into three levels (public wayside, public inland, or remote) based on road proximity and public access. Subsequently, models for five taxonomic groups were compared using (model 1) basic land-cover categories and (model 2) land-cover and accessibility categories. Model 2 consistently outperformed Model 1 in predicting hotspots and specific land-cover factors connected to species distributions. These findings highlighted the critical role of identifying biases that drive data patterns in citizen science, which is essential for interpreting data, designing effective engagement strategies, and planning biodiversity-friendly and accessible urban green spaces.

Authors

Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2025-09-19
DOI
https://doi.org/10.5194/isprs-annals-x-4-w7-2025-67-2025
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
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article

Effects of Accessibility on the Records of Biodiversity Observation by the Citizens of Urban Forests

Yui Ogawa, Shoma Jingu
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Species Distribution and Climate Change
article

Effects of Accessibility on the Records of Biodiversity Observation by the Citizens of Urban Forests

Yui Ogawa, Shoma Jingu
article en

Abstract

Abstract. The leveraging of social media for citizen science is a powerful tool for generating large-scale records of wildlife observations and engaging the public in biodiversity conservation. However, the utility of observation records is adversely affected by their biases. In particular, understanding the drivers behind observation hotspots—locations where observation records are concentrated—is vital for interpreting data and optimizing project design. This study investigated the factors forming observation hotspots in the urban forests of Tsukuba Science City, Japan, assuming that accessibility by humans is as important as ecological factors. We analyzed 17,224 observation records from a social media platform for citizen science across a 54-km2 study area and classified location accessibility into three levels (public wayside, public inland, or remote) based on road proximity and public access. Subsequently, models for five taxonomic groups were compared using (model 1) basic land-cover categories and (model 2) land-cover and accessibility categories. Model 2 consistently outperformed Model 1 in predicting hotspots and specific land-cover factors connected to species distributions. These findings highlighted the critical role of identifying biases that drive data patterns in citizen science, which is essential for interpreting data, designing effective engagement strategies, and planning biodiversity-friendly and accessible urban green spaces.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-4/W7-2025
Openalex Percentile: Top 86%
Species Distribution and Climate Change
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Effects of Accessibility on the Records of Biodiversity Observation by the Citizens of Urban Forests — Yui Ogawa, Shoma Jingu · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2025) | TGRS Research Map | TGRS