Citizen Science and Environmental Health
Millions of people carry a sensor in their pocket. Through NASA GLOBE Observer, our EMERGE program, and partners from Guatemala to Florida, we turn public observations into training data for GeoAI, into forecasts of mosquito-borne disease risk, and into open, bilingual curricula that anyone can teach from.
EMERGE, our open education program
EMERGE (Environmental Monitoring through Education, Research and Geospatial Engagement) is supported by NASA and ESIP. With the STEAM Programme at Universidad de San Carlos de Guatemala and GLOBE colleagues, we run teacher workshops where every teacher leaves with a monitoring kit and a certificate, so the science continues after we go home.
• Two free textbooks: Data Analysis, and Participatory Science and GeoAI
• Monthly webinars with Spanish subtitles, launched October 2026
• A Spanish-language site, teacher workshops, and school visits in Guatemala
• ask-globe, an open-source AI assistant for exploring GLOBE data
How public observations become science
Forecasting mosquito-borne disease risk. Our NASA project (2025 to 2027) combines GLOBE Mosquito Habitat Mapper photos with NASA Earth system data to predict where Aedes and Anopheles risk will rise as the climate changes, with modeling partners at Emory University.
Photo: students and teachers collecting GLOBE observations in the field.
Better maps from many eyes. GLOBE land cover photos taken in several directions make satellite land cover maps more accurate: the more views, the better. We also use GLOBE observations to check global satellite land cover products and to train machine-learning models.
Photos: EMERGE teacher workshop in Guatemala and a GLOBE session with STEAM Guatemala; chart: GLOBE land cover observations by year and class.
Citizen data for health and disasters. Community-contributed data helped us map a mass die-off of migratory birds across the western U.S., evaluate how land use shaped Hurricane Harvey flooding in Houston, and study how people used parks during COVID-19 and wildfire seasons.
Photo: an EMERGE session with students in Guatemala.
Projects you can join
Can citizen-science habitat photos plus satellite climate data predict where Aedes and Anopheles risk will rise?
Students: map larval habitat from high-resolution imagery, clean GLOBE Observer data, and build and test disease-risk forecasting models. EMERGE textbooks and webinar seriesESIP · PI · 2026
How do we make geospatial AI teachable to anyone, in any language?
Students: write open textbook chapters, host the monthly webinars, and translate materials into Spanish. ask-globe: an AI assistant for GLOBE dataOpen source · GeoDI Lab
Can a language model help teachers and students explore millions of GLOBE observations?
Students: build retrieval and evaluation pipelines for an open-source geospatial assistant.
What you will learn
Citizen science students learn to work with people as well as with data.
- GLOBE Observer protocols and data quality
- Machine learning on crowdsourced images
- Disease-risk and habitat modeling
- Curriculum design and bilingual science communication
- Workshop facilitation with schools and communities
- Google Earth Engine and Python
New to GLOBE data? Start with our lab tutorial, Merging NASA GLOBE Observer Images.
- Kianfar, N., Savoji, K., Huang, X., Yang, D., and Mollalo, A. (2026). The role of citizen science in mosquito-borne disease surveillance and control: a scoping review. PLoS One, 21(5).
- Yang, D., Huang, X., He, Y., Low, R., and Nelson, P. (2026). Forecasting mosquito-borne disease risk integrating GLOBE citizen science and NASA Earth observations. In Citizen Earth: Crowdsourced Geospatial Data for Earth and Human Observations. Springer Nature.
- Nelson, P. V., Low, R., Kohl, H., Overoye, D., Yang, D., Huang, X., and others (2024). GLOBE Observer: a case study in advancing Earth system knowledge with AI-powered citizen science. Citizen Science: Theory and Practice, 9(1).
- Huang, X., Wang, S., Yang, D., Hu, T., Chen, M., Zhang, M., and others (2024). Crowdsourcing geospatial data for Earth and human observations: a review. Journal of Remote Sensing, 4, 0105.
- Huang, X., Yang, D., He, Y., Nelson, P., Low, R., McBride, S., and others (2023). Land cover mapping via crowdsourced multi-directional views: the more directional views, the better. International Journal of Applied Earth Observation and Geoinformation, 122, 103382.
- Yang, D., Fu, C. S., Herrero, H. V., Southworth, J., and Binford, M. (2023). Linking forest management to surrounding lands: a citizen-based approach towards the regional understanding of land-use transitions. Frontiers in Remote Sensing, 4, 1197523.
- Yang, A., Rodriguez, M., Yang, D., Yang, J., Cheng, W., Cai, C., and Qiu, H. (2022). Leveraging machine learning and geo-tagged citizen science data to disentangle the factors of avian mortality events at the species level. Remote Sensing, 14(10), 2369.
- Yang, D., Yang, A., Yang, J., Xu, R., and Han, Q. (2021). Unprecedented migratory bird die-off: a citizen-based analysis on the spatiotemporal patterns of mass mortality events in the western United States. GeoHealth, 5, e2021GH000395.
- Yang, A., Yang, J., Yang, D., Xu, R., He, Y., and Qiu, H. (2021). Human mobility to open space and public parks under the COVID-19 pandemic and wildfire seasons in the western and central United States. GeoHealth, e2021GH000494.
- Yang, D., Wan, H., Huang, T. K., and Liu, J. (2019). The role of citizen science in conservation under the framework of telecoupling. Sustainability, 11, 1108.
- Yang, D., Yang, A., Qiu, H., Zhou, Y., Herrero, H., Fu, C. S., Yu, Q., and Tang, J. (2019). A citizen-contributed GIS approach for evaluating the impacts of land use on Hurricane Harvey-induced flooding in the Houston area. Land, 8(2), 25.
Join the citizen science team
We welcome students from geography, education, public health, and data science, and we especially welcome Spanish speakers. Send a short note and your CV to yangdi1031@ufl.edu.