Investigating

Harmful Algal

Blooms using: -Satellites

-Drones

-Boats

-Citizen Science

Nina Raqueno

nina@cis.rit.edu

Ryan Ford, Ph.D. Candidate

Dr. Anthony Vodacek

Rochester Institute of Technology

Center for Imaging Science

Digital Imaging & Remote Sensing

Remote Sensing

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“Remote sensing is the field of study associated with extracting information about an object without physical contact with it.” – Dr. John Schott, Remote Sensing: The

Imaging Chain Approach

• RIT’s Digital Imaging and Remote Sensing (DIRS) Group

• Focus on developing and improving remote sensing techniques and sensors including airborne, satellite, and drone imagery.

• This research using Landsat and drones to detect and monitor harmful algal blooms is funded by NASA/USGS.

Cyanobacteria Blooms in the Finger Lakes

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New York State Department of Environmental Conservation reported blooms in the Finger Lakes from 2012 to 2016. Red coloring represents waterbodies with reported

bloom and not spatial extent.

Landsat 8 Owasco LakeBloom 9/20/2016

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Near shore

monitoring could miss

the off shore bloom.

Satellite image (when

available and cloud free)

can provide a lake

wide assessment of

the conditions.

http://arcg.is/2e3bAcG

Landsat 8 and Sentinel 2 Spectral Responses

Sentinel 2

Landsat 8

Satellite Imagery: more than pretty pictures

Satellite Imagery: Spectral Band Combinations

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Cyanobacteria Absorption Vs. Green Algae

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Chlorophyll-a

Phycocyanin

Landsat 8 Band

RSR

Landsat Next?RIT’s research provides

guidance to NASA on how to

improve their satellite sensors for

improved water quality analysis.

Owasco Bloom Retrieval: Landsat 8 September 20, 2016

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Chlorophyll-a (mg/m^3) Phycocyanin (mg/m^3)

Honeoye Lake Chl-a and PC

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Results using

all Landsat 8

spectral bands

to extract Chl-a

& Phycocyanin

Concentrations

Limitation of Imaging Satellites

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Landsat 8 September 11, 201611:50 AM

• Clouds

• Temporal Coverage

• Spatial Coverage

Avon Marsh Dam Pond

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30 Meter Landsat 8 OLI Imagery September 11, 2016

Google Maps Imagery

• Spatial Coverage

DRONE IMAGERY

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Quantification of Cyanobacteria Blooms Using Drone (UAS) Imagery

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Stitched Drone Imagery of

Honeoye Lake

September 12, 2016

Ryan Ford, Ph.D. Student

Nina Raqueno, Research Scientist

Dr. Anthony Vodacek, Faculty

RIT Strategic Initiative in UAS Imaging ResearchUAV Sensor Integration Lab UAV Flight Testing Enclosure

Hyperspectral LidarMultispectral Infrared

High Performance

Algorithms and Computing

High Performance Multi-rotor Copters

DJI S1000

DJI M600

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Sandy Bottom Beach, Honeoye Lake

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Google Maps Imagery

Drone Spatial Coverage: Limited

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Honeoye Lake, September 12, 2016

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Color (RGB) Composite Imagery of Sandy Bottom Beach

Honeoye Lake, September 12, 2016

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IR False color imagery of Sandy Bottom BeachNIR, Red, Green Composite

Conclusions

Results are promising, but improvements can be made:

• Further Develop Drone Collection Strategies- Test bands to determine optimal combination

- Determine optimum way to reduce levels of sun/sky glint

- Address possible bottom issues

- RTK GPS

• Refining Data Analysis- Removing non-physical concentration combinations

• Integrate and share all data streams

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What’s YOUR real question?

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Do I go swimming today?

Do I go swimming HERE today?

Is my water safe to drink?

Is it safe to eat the fish?

What is contributing to HABs?

Can we predict HABs?

....

Citizen Science Example

21http://arcg.is/2dRx5d3

Follow this link for an example of a GIS web tool that could be used

for reporting and educating the public on what HABs look like, results

from monitoring programs, invasive species surveys....

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2017

20 October, 2017

http://ewh.ieee.org/r1/rochester/grss/STRATUS2017/

Want to learn more about UAS/Drone Research?