Academic Journal

Assessing urban forest biodiversity through automatic taxonomic identification of street trees from citizen science applications and remote-sensing imagery

التفاصيل البيبلوغرافية
العنوان: Assessing urban forest biodiversity through automatic taxonomic identification of street trees from citizen science applications and remote-sensing imagery
المؤلفون: Luisa Velasquez-Camacho, Esko Merontausta, Maddi Etxegarai, Sergio de-Miguel
المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 128, Iss , Pp 103735- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Physical geography
LCC:Environmental sciences
مصطلحات موضوعية: Urban forest inventory, Geospatial analysis, Artificial intelligence, Citizen science, Species identification apps, Remote sensing, Physical geography, GB3-5030, Environmental sciences, GE1-350
الوصف: The positive impact of urban forests and trees on the well-being of urban residents worldwide is well known. Resistance to pests, diseases, and extreme weather events are among the most critical characteristics of resilient cities, closely related to species richness and, consequently, to the diversity of street trees. However, urban forest inventories are currently scarce worldwide. For this reason, urban trees' biodiversity and capacity to provide these ecosystem services are not developed enough. Three state-of-the-art species identification applications were tested, Plant.id, Pl@ntNet and Seek (iNaturalist) to identify a large number of tree families, genera, and species automatically. Two individual Google Street View images were queried for each tree in the study area, adjusting the Field of View and pitch parameters. The predictive capacity of the three apps was compared, and a biodiversity analysis was performed for different geospatial scales within the study area (i.e., at the whole study area, neighborhood, and street levels, respectively). Notably, our research contributes in an innovative way to the assessment and monitoring of the ecosystem services provided by street trees and sheds light on the great potential of combining remote sensing, citizen science and artificial intelligence for urban forest biodiversity assessments at multiple spatial and temporal scales.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1569-8432
Relation: http://www.sciencedirect.com/science/article/pii/S156984322400089X; https://doaj.org/toc/1569-8432
DOI: 10.1016/j.jag.2024.103735
URL الوصول: https://doaj.org/article/23aad65430764d1685c9ab20fe8138ac
رقم الانضمام: edsdoj.23aad65430764d1685c9ab20fe8138ac
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15698432
DOI:10.1016/j.jag.2024.103735