Aligning citizen science and remote sensing phenology observations to characterize climate change impact on vegetation. (1st August 2022)

• Record Type: Journal Article
• Authors: Domingo-Marimon, Cristina; Masó, Joan; Prat, Ester; Zabala, Alaitz; Serral, Ivette; Batalla, Meritxell; Ninyerola, Miquel; Cristóbal, Jordi
• Is Part Of: Environmental research letters. Volume 17:Number 8(2022)
• Publication Date: 2022-08-01
• Subjects: citizen science -- phenology -- phenometrics -- Sentinel-2 -- time-series -- remote sensing; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ac8499
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Phenology observations are essential indicators to characterize the local effects of climate change. Citizen participation in the collection of phenological observations is a potential approach to provide data at both high temporal scale and fine grain resolution. Traditional observation practices of citizen science (CS), although precise at the species scale, are limited to few observations often closely located to an observer's residence. These limitations hinder coverage of the great variability of vegetation phenology across biomes and improvement of the knowledge of vegetation changes due to climate change impacts. This study presents a new approach to overcome these limitations by improving CS guidance and feedback as well as expanding phenology report sites and observations across different habitats and periods to contribute to monitoring climate change. This approach includes: (a) a new methodology focused on harmonizing remote sensing phenology products with traditional CS phenology observations to direct volunteers to active phenology regions and, (b) a new protocol for citizen scientists providing tools to guide them to specific regions to identify, collect and share species phenological observations and their phenophases. This approach was successfully tested, implemented and evaluated in Catalonia with more than 5000 new phenologically interesting regions identified and more than 200 observations collected and Sentinel-2 derived phenometrics were demonstrated as of good quality.