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EMERGE Project

Tracking Mosquito Habitats: From Your Backyard to Space

Connecting Libraries, Educators & Communities through Remote Sensing

Dr. Di Yang,

Dr. Caroline Nickerson,

Olivia Zhang, & Ashley Hays

Department of Geography

University of Florida

September 2025

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Webinar Overview

Today's Topics

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Introduction to EMERGE Project

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Mosquito Biology & Disease Risk

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NASA Earth Observations & Remote Sensing

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GLOBE Observer App Tutorial

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Community Activities & Resources…Including Coding Practice!

Your Takeaways

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Understanding of mosquito-borne disease risks

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Hands-on experience with GLOBE Observer app

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Resources for community engagement

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Eligibility for mini-grants and support

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Connection to a global research network

Who Should Participate?

Libraries • Schools • Community Centers • Local Governments • Families • Individuals

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The Power of Citizen Science

What is Citizen Science?

A collaborative approach to research involving public participation in scientific data collection, analysis, and discovery.

Public participation

Scientific data collection

Real research impact

Citizen science has emerged as a powerful approach to scientific research that engages the public in meaningful ways. It's a collaborative methodology where community members participate in data collection, analysis, and discovery alongside professional scientists. The impact is significant—over 50% of global biodiversity records for birds and invertebrates in the Global Biodiversity Information Facility since 2000 come from citizen scientists. Successful platforms like eBird, iNaturalist, and City Nature Challenge demonstrate how effective these approaches can be at scale. These initiatives prove that when properly structured, citizen-collected data can achieve the rigor and quality needed for scientific research while expanding our capacity for environmental monitoring far beyond what would be possible with professional scientists alone.

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EMERGE Project Overview

NASA Award #80NSSC25K7190 | GeoDI Lab, University of Florida

What is EMERGE?

Project Duration

3 years (2025-2027)

Key Objectives

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Climate-driven risk prediction

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AI-driven mosquito habitat modeling

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GLOBE-NASA Earth Observation data framework

Revolutionary Approach

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First-ever fusion of citizen science, NASA Earth observations, and AI

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Real-time, hyperlocal mosquito-borne disease risk forecasting

Environmental Monitoring through Education, Research & Geospatial Engagement

EMERGE stands for Earth observations and citizen science for Mosquito-borne disease risk GEomapping and pREdiction. It's a 3-year NASA-funded project running from 2025 to 2027. Our key objectives include developing climate-driven risk prediction models, creating AI-driven mosquito habitat analysis tools, and building a data framework that connects GLOBE citizen science observations with NASA Earth observation satellite data. We've assembled an impressive team of partners, including the University of Florida's GeoDI Lab, NASA, the GLOBE program, and collaborators from the University of South Carolina, Emory University, and the University of Arkansas. What makes our approach revolutionary is the fusion of citizen science, space-based observations, and artificial intelligence to create hyperlocal disease risk forecasting capabilities that have never been possible before.

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The EMERGE Initiative

NASA

Environmental Monitoring through Education, Research & Geospatial Engagement

Community

Public libraries as hubs for citizen science

Local data collection campaigns

Public health awareness building

Educators

STEM curriculum integration

Hands-on science activities

Professional development opportunities

Public Health

Disease risk monitoring

Vector control coordination

Early warning system development

Research

Satellite data validation

Predictive model development

Geospatial analysis & visualization

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All resources: geoemerge.com

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EMERGE Highlights

Upcoming Hack-A-Thon in Florida
Curriculum with easy-to-use coding tutorials for all levels & backgrounds to analyze mosquito data & come up with public health solutions (from anywhere)

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The Growing Threat of Mosquito-Borne Diseases

Climate change expands mosquito habitat range

2024: Florida recorded 1,044 dengue cases

2024: 18 human West Nile cases

Hurricane events boost post-storm mosquito abundance 7–8×

Source: UF Emerging Pathogens Institute; Florida DOH; Moise et al 2024

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Global Disease Risk Maps

Malaria Risk

High Risk

Medium Risk

Low Risk

Dengue Risk

High Risk

Medium Risk

Low Risk

Climate Change Impact

Mosquito-borne diseases are expanding into new regions due to:

• Rising global temperatures

• Changing precipitation patterns

• Extreme weather events

• Human migration and urbanization

EMERGE's Approach

• Integration of cutting-edge CMIP6 climate models

• Novel downscaling techniques for hyper-local predictions

• Scenario planning for multiple climate futures

• Community-powered data collection

These global disease risk maps help us visualize the current distribution of mosquito-borne diseases and how they might change in the future. Malaria, primarily transmitted by Anopheles mosquitoes, is most prevalent in sub-Saharan Africa, parts of South Asia, and regions of South America. Dengue, carried by Aedes mosquitoes, is concentrated in Southeast Asia, Central America, and parts of South America, with lower prevalence in Africa. Climate change is having a significant impact on the spread of these diseases, driven by rising global temperatures, changing precipitation patterns, extreme weather events, and human factors like migration and urbanization. Our projections show that by 2050, mosquito habitats could expand significantly northward and southward from the equator, putting hundreds of millions more people at risk. The EMERGE project is addressing this challenge through a sophisticated approach that integrates CMIP6 climate models, downscaling techniques for hyperlocal predictions, scenario planning for different climate futures, and community-powered data collection to create more accurate risk maps.

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Mosquito Biology & Disease Risk

Eggs

2-3 days

Larvae

4-14 days

Pupae

2-3 days

Adult

Up to 6 weeks

Standing Water

Key Florida Vector Species

Species

Associated Pathogens

Habitat

Aedes aegypti

Yellow Fever Mosquito

Dengue

Zika

Chikungunya

Yellow Fever

Urban, artificial containers

Aedes albopictus

Asian Tiger Mosquito

Dengue

Chikungunya

Eastern Equine Encephalitis

Suburban, natural & artificial containers

Culex quinquefasciatus

Southern House Mosquito

West Nile Virus

St. Louis Encephalitis

Urban/suburban, polluted water

Anopheles quadrimaculatus

Malaria Mosquito

Malaria (historical)

Rural, fresh water with vegetation

Understanding mosquito biology is crucial for effective monitoring and control. The mosquito lifecycle consists of four stages: eggs, larvae, pupae, and adults. Eggs typically hatch within 2-3 days of being laid in standing water. The larval stage lasts 4-14 days, during which mosquitoes feed and grow. The pupal stage follows for 2-3 days, and finally, adult mosquitoes emerge and can live up to 6 weeks. In Florida, four key mosquito species pose significant public health concerns. Aedes aegypti transmits dengue, Zika, chikungunya, and yellow fever, typically breeding in urban artificial containers. Aedes albopictus (Asian Tiger) carries similar pathogens plus Eastern Equine Encephalitis and thrives in suburban environments. Culex quinquefasciatus transmits West Nile and St. Louis Encephalitis viruses, favoring polluted water. Anopheles quadrimaculatus, historically associated with malaria, prefers rural fresh water with vegetation. Disease transmission risk increases with optimal temperature (22-32°C), high humidity (60-80%), and high population density.

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Meet the GLOBE Observer App

Our primary tool for citizen science data collection

User-Friendly Interface

Intuitive design for all ages and tech skill levels

GPS Integration

Automatically captures location data with observations

Photo Documentation

Capture visual evidence of mosquito habitats

Offline Capability

Collect data without internet, sync later

9:41 AM

Free for everyone!

The GLOBE Observer app is our primary tool for citizen science data collection. It features a user-friendly interface designed for people of all ages and technical skill levels, making it accessible to everyone from students to seniors. The app integrates GPS functionality to automatically capture precise location data with each observation, ensuring accurate spatial mapping. Its photo documentation capabilities allow users to capture visual evidence of mosquito habitats, which helps with verification and creates a valuable visual database. One particularly useful feature is its offline capability—users can collect data in areas without internet connectivity and synchronize later when connection is available. The app is free to download on both iOS and Android platforms, removing financial barriers to participation. This tool is essential for bridging the gap between satellite data and ground-level observations.

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Mosquito Habitat Mapper Workflow

A simple 4-step process anyone can follow

STEP 1

Identify Standing Water

Locate potential breeding sites where water collects

STEP 2

Photograph

Document the habitat with clear photos through the app

STEP 3

Sample Larvae (Optional)

Collect larvae sample if present and identify species

STEP 4

Upload

Submit data to the GLOBE database for scientific use

The Mosquito Habitat Mapper workflow consists of four straightforward steps that anyone can follow. First, users identify standing water—the potential breeding sites where mosquitoes lay eggs, such as buckets, ditches, or natural depressions. Next, they photograph these habitats directly through the app, creating visual documentation that aids in verification and analysis. The third step—sampling larvae—is optional but valuable; users can collect samples if larvae are present and use the app's identification guide to determine species. Finally, they upload their observations to the GLOBE database, where the data becomes immediately available to scientists and public health officials. The app's interface guides users through each step with clear instructions and visual aids, making the process accessible even to those with no prior scientific experience. This standardized workflow ensures consistent, high-quality data collection across diverse participant groups.

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NASA Earth Observations

EMERGE: Leveraging NASA Earth Science Data

Earth Science Missions

Key Satellite Missions

SMAP

Soil Moisture Active Passive

GPM

Global Precipitation Measurement

MODIS

Moderate Resolution Imaging Spectroradiometer

Landsat

Land Remote-Sensing Satellite

ECOSTRESS

ECOsystem Spaceborne Thermal Radiometer

PACE

Plankton, Aerosol, Cloud, ocean Ecosystem

Key Environmental Variables

Atmospheric

• Air temperature

• Precipitation

• Humidity

• Wind patterns

Source: MODIS, GPM

Surface

• Soil moisture

• Soil temperature

• Surface temperature

• Elevation

Source: SMAP, ECOSTRESS

Aquatic

• Water temperature

• Water quality

• Standing water

• Flooding extent

Source: Landsat, MODIS

Land Cover

• Vegetation type

• Canopy coverage

• Urban density

• Land use changes

Source: Landsat, MODIS

NASA's Earth observation satellites provide critical data for understanding and predicting mosquito habitats and disease risk. Key missions include SMAP (Soil Moisture Active Passive), which measures soil moisture; GPM (Global Precipitation Measurement), which tracks rainfall patterns; MODIS on the Terra and Aqua satellites, which monitors vegetation and land surface temperature; Landsat, which provides detailed land cover information; and ECOSTRESS, which measures land surface temperature with high precision. The EMERGE project aligns with NASA's Earth Science mission timeline, running from 2025 to 2027. We're focusing on four categories of environmental variables that influence mosquito breeding and disease transmission: atmospheric variables like temperature, precipitation, and humidity from MODIS and GPM; surface variables like soil moisture and temperature from SMAP and ECOSTRESS; aquatic variables like water temperature and flooding extent from Landsat and MODIS; and land cover characteristics like vegetation type and urban density from Landsat and MODIS. One key challenge is the resolution gap - NASA satellites typically provide data at resolutions between 30 meters and 1 kilometer, but mosquito breeding habitats exist at much smaller scales. EMERGE bridges this gap by combining satellite data with ground-level observations from GLOBE Observer participants.

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NASA Earth Observations

EMERGE: Leveraging NASA Earth Science Data

The Resolution Challenge

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NASA satellites provide data at 30m-1km resolution, but mosquito habitats exist at meter scales

EMERGE Solution:

Combining satellite data with ground-level GLOBE Observer data to bridge the resolution gap

NASA's Earth observation satellites provide critical data for understanding and predicting mosquito habitats and disease risk. Key missions include SMAP (Soil Moisture Active Passive), which measures soil moisture; GPM (Global Precipitation Measurement), which tracks rainfall patterns; MODIS on the Terra and Aqua satellites, which monitors vegetation and land surface temperature; Landsat, which provides detailed land cover information; and ECOSTRESS, which measures land surface temperature with high precision. The EMERGE project aligns with NASA's Earth Science mission timeline, running from 2025 to 2027. We're focusing on four categories of environmental variables that influence mosquito breeding and disease transmission: atmospheric variables like temperature, precipitation, and humidity from MODIS and GPM; surface variables like soil moisture and temperature from SMAP and ECOSTRESS; aquatic variables like water temperature and flooding extent from Landsat and MODIS; and land cover characteristics like vegetation type and urban density from Landsat and MODIS. One key challenge is the resolution gap - NASA satellites typically provide data at resolutions between 30 meters and 1 kilometer, but mosquito breeding habitats exist at much smaller scales. EMERGE bridges this gap by combining satellite data with ground-level observations from GLOBE Observer participants.

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NASA Earth Observation & GLOBE Integration

Contextualizing NASA Earth Observations

The Integration Challenge

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NASA provides rich satellite data (MODIS, GPM, SMAP, ECOSTRESS, Landsat) at various resolutions

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Critical environmental variables influence mosquito habitats but exist across different scales

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Need to contextualize these observations with ground-level realities

The Data Scale Gap

1m

10m

100m

1km

10km

100km

Mosquito�Breeding Sites

GLOBE Observations

Landsat�(30m)

MODIS�(250m-1km)

Climate Models�(25-100km)

Data Integration Process

Multi-Scale Data Fusion

NASA Satellite Data

Coarse resolution (30m-1km)

GLOBE Citizen Science

Fine resolution (meter-scale)

Bayesian Data Integration

Harmonizing multi-scale observations

High-Resolution Mosquito Risk Map

Comprehensive environmental context at multiple scales

High Risk

Medium Risk

Low Risk

One of the most innovative aspects of the EMERGE project is how we contextualize NASA Earth observations with GLOBE citizen science data. This integration addresses several key challenges. First, NASA provides rich satellite data from instruments like MODIS, GPM, SMAP, ECOSTRESS, and Landsat, but at various resolutions. Second, the environmental variables that influence mosquito habitats exist across different spatial scales. Third, we need to contextualize these space-based observations with ground-level realities. This creates what we call the "data scale gap." Mosquito breeding sites exist at the meter scale, while GLOBE observations are collected at similar fine resolutions. However, NASA satellite data ranges from 30 meters (Landsat) to 250 meters or 1 kilometer (MODIS), and climate models operate at even coarser scales of 25 to 100 kilometers. Our harmonization framework addresses this challenge by combining four key variable categories: atmospheric variables like air temperature, precipitation, and humidity from MODIS and GPM; surface variables like soil characteristics and temperature from SMAP and ECOSTRESS; aquatic variables like water properties from SeaWiFS and HICO for breeding sites; and land cover variables like vegetation health and canopy coverage from MODIS and Landsat. Our data integration process uses multi-scale data fusion techniques to bring these diverse data sources together. We employ Bayesian data integration methods to harmonize multi-scale observations, resulting in comprehensive high-resolution mosquito risk maps that provide environmental context at multiple scales. We enhance this process with artificial intelligence, using machine learning to identify patterns across scales, neural networks trained on matched NASA-GLOBE data pairs, and Generative Adversarial Networks for creating high-resolution synthetic data where observations are sparse. Our technical innovations include cross-scale data consistency checks using Bayesian methods, uncertainty quantification at each integration step, cascading downscaling techniques across multiple resolutions, and an open-source codebase to ensure transparency and reproducibility.

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The Land Cover-Disease Connection

The "Perfect Storm" for Mosquitoes

Urban Heat Island Effect

Urban areas can be 2-5°C warmer than surrounding rural areas, creating ideal mosquito development conditions

Predicting Future Hotspots

Land Cover Change Impact

2025

Forest/Vegetation

Urban

Water

2050 (Projected)

EMERGE: Transforming Citizen Science into Actionable Insights

Our research has uncovered critical connections between land cover patterns and mosquito-borne disease risk, revealing what we call the "perfect storm" conditions for mosquito breeding. The urban heat island effect is a key factor - urban areas can be 2 to 5 degrees Celsius warmer than surrounding rural areas, creating ideal conditions for accelerated mosquito development and viral replication. We've identified four key risk factors that contribute to mosquito proliferation: Urbanization, which increases impervious surfaces, creates poor drainage systems, and concentrates human populations; Land Use Changes, including deforestation, wetland conversion, and agricultural expansion; Water Management practices like irrigation, water storage, and stormwater retention; and Vegetation Changes such as canopy reduction, invasive species introduction, and landscaping choices. We're analyzing how these factors combine to create optimal conditions for mosquito breeding and disease transmission. Looking toward the future, our predictive models are examining how urbanization patterns and land use changes will create new mosquito hotspots by 2050. We're particularly concerned about development impacts, as urban sprawl creates fragmented habitats that favor disease-carrying mosquitoes, edge environments between developments and natural areas create ideal breeding zones, and infrastructure development like roads and drainage systems alters water flow patterns. Based on our findings, we're developing planning recommendations, including incorporating mosquito risk assessment in development planning, designing stormwater systems to prevent mosquito breeding, preserving continuous natural habitat corridors, and using EMERGE data to guide public health resource allocation. This represents a new paradigm for disease risk assessment that integrates environmental, climate, and human factors.

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Mosquito Habitat Data Insights

Global Contributions

Total Contributions

47,090

From 107 countries

Habitat Types & Insights

Common Mosquito Breeding Sites

Based on GLOBE Observations

The GLOBE Observer Mosquito Habitat Mapper has collected impressive amounts of data worldwide. To date, there have been nearly 13,000 mosquito habitat observations submitted from 78 countries around the world. The United States leads with over 6,000 contributions, followed by India with more than 800, and Thailand with about 700. We see interesting patterns in the monthly contribution data, with peaks typically coinciding with warmer, wetter months in the northern hemisphere where most participants are located. When we analyze the types of mosquito breeding sites being reported, puddles account for about 28% of observations, followed by various containers at 24%, discarded tires at 15%, ditches at 12%, and plant containers at 8%. This aligns with what we know about mosquito breeding preferences - they seek out standing water in both natural and human-created environments. Looking at water source analysis, we find that artificial containers make up 42% of breeding sites, natural water sources account for 27%, flowing water represents 18%, and other types comprise the remaining 13%. These insights are incredibly valuable, showing that artificial containers are the most common breeding sites globally, urban areas have about three times more breeding sites than rural areas, there are clear seasonal patterns with peaks following rainy periods, and simple prevention measures could eliminate over 60% of the habitats identified. This kind of data helps public health officials target their mosquito control efforts more effectively and empowers communities to take preventive action.

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Mosquito Habitat Images

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Downscaling Climate Models

The Need for Downscaling

This mismatch creates significant uncertainty in disease risk predictions, requiring sophisticated downscaling techniques

GLOBE Ground Truth

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GLOBE observations provide essential ground truth for validating downscaled models

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Citizen science data points identify local variations missed by models

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Fine-tuning algorithms based on real-world observations

Uncertainty Quantification

1

Bayesian ensemble approaches to quantify prediction uncertainty

2

Monte Carlo simulations explore parameter space

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Confidence metrics for each prediction to guide decision-making

Downscaling climate models is another critical innovation of the EMERGE project that addresses what we call the "resolution gap challenge." This challenge arises because global climate models operate at 50-100 kilometer resolution while mosquito habitats exist at meter scales. There are three key aspects to this resolution mismatch: first, CMIP6 climate models typically operate at 50-100 kilometer grid cells; second, NASA satellite data ranges from 30 meters (Landsat) to 1 kilometer (MODIS); and third, mosquito breeding sites can be as small as a few centimeters to meters. This mismatch creates significant uncertainty in disease risk predictions, requiring sophisticated downscaling techniques to bridge the gap between global climate models and local mosquito habitats. Our innovative solution is a two-stage downscaling framework. The first stage uses statistical downscaling with Bias Correction Spatial Disaggregation (BCSD), which corrects systematic biases in climate model outputs, preserves spatial patterns from high-resolution observations, and transfers climate change signals to finer scales. The second stage employs machine learning downscaling with advanced AI approaches for hyperlocal predictions, including Long Short-Term Memory networks that learn temporal patterns in climate data, Convolutional Neural Networks that capture spatial relationships, Generative Adversarial Networks that create realistic high-resolution data, and reinforcement learning for adaptive downscaling parameters. GLOBE observations play a crucial role in this process by providing essential ground truth for validating downscaled models, identifying local variations missed by models, and helping fine-tune algorithms based on real-world observations. We also implement robust uncertainty quantification using Bayesian ensemble approaches to quantify prediction uncertainty, Monte Carlo simulations to explore parameter space, and confidence metrics for each prediction to guide decision-making.

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How can you get involved?

Use the GLOBE Observer App and/or lead others to use it
Analyze local (like your own county) and/or global GLOBE Observer data to understand public health risks. Let’s get into it with a coding tutorial!

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All resources: geoemerge.com

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