Investigating Harmful Algal Blooms using: -Satellites -Drones -Boats -Citizen Science Nina Raqueno [email protected] Ryan Ford, Ph.D. Candidate Dr. Anthony Vodacek Rochester Institute of Technology Center for Imaging Science Digital Imaging & Remote Sensing Remote Sensing “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. 2 Cyanobacteria Blooms in the Finger Lakes 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. 3 Landsat 8 Owasco Lake Bloom 9/20/2016 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 4 Satellite Imagery: more than pretty pictures Landsat 8 and Sentinel 2 Spectral Responses Sentinel 2 Landsat 8 Satellite Imagery: Spectral Band Combinations 6 Cyanobacteria Absorption Vs. Green Algae Landsat 8 Band Chlorophyll-a RSR Phycocyanin Landsat Next? RIT’s research provides guidance to NASA on how to improve their satellite sensors for improved water quality analysis. 10 Owasco Bloom Retrieval: Landsat 8 September 20, 2016 Chlorophyll-a (mg/m^3) Phycocyanin (mg/m^3) 8 Honeoye Lake Chl-a and PC Results using all Landsat 8 spectral bands to extract Chl-a & Phycocyanin Concentrations 15 Limitation of Imaging Satellites • Clouds • Temporal Coverage • Spatial Coverage Landsat 8 September 11, 2016 11:50 AM 10 Avon Marsh Dam Pond • Spatial Coverage 30 Meter Landsat 8 OLI Imagery September 11, 2016 Google Maps Imagery 11 DRONE IMAGERY 12 Quantification of Cyanobacteria Blooms Using Drone (UAS) Imagery Ryan Ford, Ph.D. Student Nina Raqueno, Research Scientist Dr. Anthony Vodacek, Faculty Stitched Drone Imagery of Honeoye Lake September 12, 2016 13 RIT Strategic Initiative in UAS Imaging Research High Performance UAV Sensor Integration Lab UAV Flight Testing Enclosure Algorithms and Computing Multispectral Hyperspectral Lidar Infrared High Performance Multi-rotor Copters DJI S1000 DJI M600 14 Sandy Bottom Beach, Honeoye Lake Google Maps Imagery 15 Drone Spatial Coverage: Limited 16 Honeoye Lake, September 12, 2016 Color (RGB) Composite Imagery of Sandy Bottom Beach 17 Honeoye Lake, September 12, 2016 IR False color imagery of Sandy Bottom Beach NIR, Red, Green Composite 18 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 19 What’s YOUR real question? 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? .... 20 Citizen Science Example 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.... http://arcg.is/2dRx5d3 21 Want to learn more about UAS/Drone Research? 2017 20 October, 2017 http://ewh.ieee.org/r1/rochester/grss/STRATUS2017/ 22.