Social media and deep learning reveal specific cultural preferences for biodiversity

Autor: Ilan Havinga, Diego Marcos, Patrick Bogaart, Dario Massimino, Lars Hein, Devis Tuia

Publikováno v: People and Nature, Vol 5, Iss 3, Pp 981-998 (2023)

Abstract Social media has created new opportunities to map cultural ecosystem services (CES) related to biodiversity at large scales. However, using these novel data to understand people's preferences in relation to these CES remains a challenge. To

Externí odkaz: https://doaj.org/article/54cdb5b482c74b27b8e8bc365c9f74aa

Social media data for environmental sustainability: A critical review of opportunities, threats, and ethical use

Autor: Andrea Ghermandi, Johannes Langemeyer, Derek Van Berkel, Fulvia Calcagni, Yaella Depietri, Lukas Egarter Vigl, Nathan Fox, Ilan Havinga, Hieronymus Jäger, Nina Kaiser, Oleksandr Karasov, Timon McPhearson, Simone Podschun, Ana Ruiz-Frau, Michael Sinclair, Markus Venohr, Spencer A. Wood

Publikováno v: One Earth, 6(3), 236-250
One Earth 6 (2023) 3

Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff06e4cb6abac8af85fc78dd53f73a1a
https://doi.org/10.1016/j.oneear.2023.02.008

GB aesthetics

Autor: Ilan Havinga, Diego Marcos, Patrick Bogaart, Lars Hein, Devis Tuia

Scripts and data associated with the publication "Social media and deep learning capture the aesthetic quality of the landscape". If making use of this dataset in your research, we would appreciate a reference to the following paper: Havinga, I, Marc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db45a05d90b8302fd96c5ccbd5194926
https://doi.org/10.5281/zenodo.5534028

Cross-Modal Learning of Housing Quality in Amsterdam

Autor: Alex Levering, Ilan Havinga, Diego Marcos, Devis Tuia

Publikováno v: Proceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2021
GeoAI@SIGSPATIAL
Proceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2021. Association for Computing Machinery, Inc

In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Google StreetView (GSV) to Flickr images. Our results show that GSV predi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f17cfd61e4571da9bdcd8d438812b95
https://research.wur.nl/en/publications/cross-modal-learning-of-housing-quality-in-amsterdam

Spatial quantification to examine the effectiveness of payments for ecosystem services: A case study of Costa Rica's Pago de Servicios Ambientales

Autor: Lars Hein, Antoine Languillaume, Mauricio Vega-Araya, Ilan Havinga

Publikováno v: Ecological Indicators 108 (2020)
Ecological Indicators, 108

Payments for ecosystem services (PES) have been developed as a policy instrument to help safeguard the contributions of ecosystems to human well-being. A critical measure of a programme’s effectiveness is whether it is generating an additional supp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2473f08098d50c45653ee83b2ceaede
https://doi.org/10.1016/j.ecolind.2019.105766