Citizen science is a form of scientific research in which members of the public participate. It is often used to describe scientific research conducted by amateur scientists, but it can also be used to describe scientific research conducted by professional scientists that involve members of the public.
Exploratory Data Analysis in R/RStudio using GBIF citizen-science data. Demonstrates working with biodiversity APIs, spatial mapping (sf, rnaturalearth), and reproducible R Markdown workflows. Distribution mapping and temporal trends for Rainbow Lorikeet records in Australia.
Heatmap showing monthly sky brightness and moon phase created for "Was het Donker?", a citizen science project in The Netherlands to monitor light pollution
Code used in the paper: Crop management for climate adaptation supported by citizen science
Repository for the analysis of the MS: "Detecting flying insects using car nets and DNA metabarcoding"
This repository contains R code and dataset for analyzing photo-identification data of humpback whales (Megaptera novaeangliae) from Malagasy waters.
Study that examines the landscape-level effects of land cover and land use on flying insect biomass
data and R code to reproduce the analysis and plots presented in the manuscript: "Macrophenological dynamics from citizen science plant occurrence data"
This is an ongoing project on Characterizing, calculating and understanding(the drivers of) Elevational Migration of resient birds in the southern western Ghats.
iNaturalist_Phenology_for_California_Oaks_RShiny
Analysis for InsectMobile diversity and biomass across Denmark and Germany in the summer of 2018 and 2019
Workflow for data analysis applied on ClimMob.net
Shiny app for air quality data Onze Lucht
Beginning work on data extracts and trends for NPMS species
Training Materials on Citizen Science in Agriculture
Determining the most commonly misidentified bee species in Canada using the iNaturalist database 🔎 🐝
Emergency Flood Forecasting (2011) 💧 How Do You Predict Floods When All Models Fail? : Grassroots forecasting system that helped 13M people prepare during Thailand's worst disaster - using only existing water data and adaptive research-based models, when conventional prediction tools broke down.
R code supporting Lavender et al. (2022). Benthic animal-borne sensors and citizen science combine to validate ocean modelling. Scientific Reports, 12, 16613. https://doi.org/10.1038/s41598-022-20254-z
R code and templates for generating recorder feedback content
An R script to download data from an iNaturalist project that was conducted as a bioblitz, and to create a slideshow that presents a variety of basic data exploration charts and maps