Presentation is loading. Please wait.

Presentation is loading. Please wait.

Remote Sensing of Vibrio spp

Published byTheodora Sparks Modified over 8 years ago

Similar presentations

Presentation on theme: "Remote Sensing of Vibrio spp"— Presentation transcript:

1 Remote Sensing of Vibrio spp
Remote Sensing of Vibrio spp. bacteria in the Chesapeake Bay Estuary, MD Erin Urquhart1, Ben Zaitchik1, Seth Guikema1 1Johns Hopkins University

2 Vibrio in Chesapeake Bay
V. cholerae V. parahaemolyticus V. vulnificus Vibrio in Chesapeake Bay Sunlight Climate ENVIRONMENT PHYSICAL PARAMETERS Precipitation Circulation Sea surface height BIOLOGICAL PARAMETERS SST Salinity Nutrients pH HUMANS Bacteria Copepods Shellfish Rec. water Untreated sewage Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

3 * V. vulnificus * V. parahaemolyticus
Vibrio in Chesapeake Bay * V. vulnificus * V. parahaemolyticus Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

4 Remote Sensing of Vibrio spp. in Chesapeake Bay
z(V.v.)= (0.316 * Temp) + ( * (|Saln- 11.5|) Urquhart et al. (2012) RSE Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

5 Percent Satellite Coverage by Month
Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

6 Percent Satellite Coverage by Month & Station
Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

7 Urquhart et al. 2nd Symposium on Advances in Geospatial Technologies for Health
August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

8 Remote Sensing of Vibrio spp. in Chesapeake Bay
z(V.v.)= (0.316 * Temp) + ( * (|Saln- 11.5|) Urquhart et al. (2013) RSE Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

9 z(V.v.)= -7.867 + (0.316 * Temp) + (-0.342 * (|Saln- 11.5|)
z(V.c.)= ( * Temp) – ( * Saln) – ( * (Temp * Saln) z(V.v.)= (0.316 * Temp) + ( * (|Saln- 11.5|) Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

10 V. vulnificus & V. parahaemolyticus
Field Sampling Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

11 Vibrio spp. Modeling in the Chesapeake Bay
V. vulnificus and V. parahaemolyticus 148 surface samples Mar.-Sept. (2011 & 2012) Probability of presence algorithms Generalized Linear Model (GLM) Generalized Additive Model (GAM) Random Forest (RF) Optimal prediction point Bacteria abundance algorithms HYBRID abundance algorithms GAM/RF Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

12 Vibrio spp. Modeling in the Chesapeake Bay
Probability of presence V. vulnificus V. parahaemolyticus Model GLM GAM RF ACC 0.63 0.72 0.68 0.62 0.67 Abundance V. vulnificus V. parahaemolyticus Model GLM GAM RF MEAN MAE 4.69 4.79 3.87 4.39 7.43 7.51 5.76 6.34 HYBRID abundance V. vulnificus V. parahaemolyticus ABUNDANCE 3.87 4.39 5.76 6.34 HYBRID/P 2.79 4.30 4.36 5.83 HYBRID 2.94 3.44 5.26 6.12 Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

13 Summary Urquhart et al nd Symposium on Advances in Geospatial Technologies for Health August 27, Session 30: ISPRS: Infectious and Vector-borne Diseases II

14 Acknowledgments Johns Hopkins University, Rebecca Murphy, Matt Hoffman, Darryn Waugh Cornell University, Dr. Bruce Monger University of Delaware, Erick Geiger University of Maryland, Bradd Haley, Elisa Taviani, Arlene Chen, Rita Colwell, Anwar Huq NASA Goddard, Molly Brown, Carlos Del Castillo Funding Sources Johns Hopkins University, NASA, NSF, NIH

15 Satellite-derived Salinity Algorithms
- MODIS-Aqua Ocean Color Standard Products 10 Remote sensing reflectances (visible) - In situ – remote sensed measurement matchups 68 CBay Program in situ stations Single pass RS ocean color data 1km radius RS averaging Introduce NEURAL NETWORK A BIT HERE! - Salinity Prediction Models GLM CART GAM BCART ANN RF MARS BART - Cross- validation study

16 Satellite-derived Salinity Algorithms
GAM ANN GLM CART BCART RF MEAN BART MARS MAE 1.82 1.85 1.93 2.39 2.38 2.06 3.72 2.04 1.98 RMSE 2.50 2.53 3.03 3.01 2.67 4.69 2.60 2.52 MAE GLM GAM ANN MEAN East for West 2.1 1.8 1.7 3.3 West for East 2.6 2.8 4.0 4.1 North for South 3.4 5.9 5.7 South for North 3.0 6.4 6.1 High for Low 2.3 4.2 Low for High 2.5 3.9 MENTION HERE ABOUT POOR ACCURACY IN UPPER BAY Top performing prediction models: GAM and ANN All models outperform MEAN GLM and GAM are fairly generalizable in a cross-validation study Urquhart et al. (2012). RSE

Download ppt "Remote Sensing of Vibrio spp"

Similar presentations

REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales.

REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales.
U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis U.S. ECoS Science Team* ABSTRACT. The U.S. Eastern Continental.

U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis U.S. ECoS Science Team* ABSTRACT. The U.S. Eastern Continental.
Evaluation of Trends in Chlorophyll-a Concentration in Response to Climatic Variability in the Eastern Bering Sea from MODIS Puneeta Naik a,b and Menghua.

Evaluation of Trends in Chlorophyll-a Concentration in Response to Climatic Variability in the Eastern Bering Sea from MODIS Puneeta Naik a,b and Menghua.
Characterization of radiance uncertainties for SeaWiFS and Modis-Aqua Introduction The spectral remote sensing reflectance is arguably the most important.

Characterization of radiance uncertainties for SeaWiFS and Modis-Aqua Introduction The spectral remote sensing reflectance is arguably the most important.
Sonia Sen Mentor: Dr. Andrew Comrie Arizona/NASA Space Grant Undergraduate Research Internship Statewide Symposium April 21, 2012 Dynamic Modeling of Mosquito.

Sonia Sen Mentor: Dr. Andrew Comrie Arizona/NASA Space Grant Undergraduate Research Internship Statewide Symposium April 21, 2012 Dynamic Modeling of Mosquito.
1 Remote sensing applications in Oceanography: How much we can see using ocean color? Martin A Montes Ph.D Rutgers University Institute of Marine and Coastal.

1 Remote sensing applications in Oceanography: How much we can see using ocean color? Martin A Montes Ph.D Rutgers University Institute of Marine and Coastal.
Jacksonville, FL 9 – 12th February 2004 Triennial GIS Symposium Mapping of potential habitats for vectors of African Tick Bite Fever (ATBF) in the Maasai.

Jacksonville, FL 9 – 12th February 2004 Triennial GIS Symposium Mapping of potential habitats for vectors of African Tick Bite Fever (ATBF) in the Maasai.
Vibrio species are present in The Great Bay, Durham, NH. All three species which are monitored, V. parahaemolyticus, V. vulnificus, and V. cholerae, were.

Vibrio species are present in The Great Bay, Durham, NH. All three species which are monitored, V. parahaemolyticus, V. vulnificus, and V. cholerae, were.
Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of North Carolina Team Members: Brittany Maybin Yao Messan.

Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of North Carolina Team Members: Brittany Maybin Yao Messan.
Use of Remote Sensing for Routine Coastal Water Monitoring by a State Agency Bob Connell New Jersey Department of Environmental Protection Bureau of Marine.

Use of Remote Sensing for Routine Coastal Water Monitoring by a State Agency Bob Connell New Jersey Department of Environmental Protection Bureau of Marine.
Abbie Harris - NOAA Ocean Acidification Think Tank #5 Current and Future Research at the Institute for Marine Remote Sensing Abbie Rae Harris Institute.

Abbie Harris - NOAA Ocean Acidification Think Tank #5 Current and Future Research at the Institute for Marine Remote Sensing Abbie Rae Harris Institute.
Geospatial Interpolation of Remotely Sensed Observations in the Chesapeake Bay: an Ecological Forecasting Application Erin Urquhart 1, Rebecca Murphy 1,Matt.

Geospatial Interpolation of Remotely Sensed Observations in the Chesapeake Bay: an Ecological Forecasting Application Erin Urquhart 1, Rebecca Murphy 1,Matt.
In situ science in support of satellite ocean color objectives Jeremy Werdell NASA Goddard Space Flight Center Science Systems & Applications, Inc. 6 Jun.

In situ science in support of satellite ocean color objectives Jeremy Werdell NASA Goddard Space Flight Center Science Systems & Applications, Inc. 6 Jun.
A Comparison of Particulate Organic Carbon (POC) from In situ and Satellite Ocean Color Data Off the Coast of Antarctica Amanda Hyde Antonio Mannino (advisor)

A Comparison of Particulate Organic Carbon (POC) from In situ and Satellite Ocean Color Data Off the Coast of Antarctica Amanda Hyde Antonio Mannino (advisor)
Atmospheric Correction Algorithms for Remote Sensing of Open and Coastal Waters Zia Ahmad Ocean Biology Processing Group (OBPG) NASA- Goddard Space Flight.

Atmospheric Correction Algorithms for Remote Sensing of Open and Coastal Waters Zia Ahmad Ocean Biology Processing Group (OBPG) NASA- Goddard Space Flight.
John Janowiak Climate Prediction Center/NCEP/NWS Jianyin Liang China Meteorological Agency Pingping Xie Climate Prediction Center/NCEP/NWS Robert Joyce.

John Janowiak Climate Prediction Center/NCEP/NWS Jianyin Liang China Meteorological Agency Pingping Xie Climate Prediction Center/NCEP/NWS Robert Joyce.
Transitioning a Chesapeake Bay Ecological Prediction System to Operations January 24, 2012 D. Green 1, C. Brown 1, F. Aikman 1, A. Siebers 1, H. Tolman.

Transitioning a Chesapeake Bay Ecological Prediction System to Operations January 24, 2012 D. Green 1, C. Brown 1, F. Aikman 1, A. Siebers 1, H. Tolman.
Using MODIS Aqua, SeaWiFS and In Situ Data for the Assessment of Harmful Algal Blooms in the Northern Gulf of Mexico Gregory A. Carter and Dan Holiday.

Using MODIS Aqua, SeaWiFS and In Situ Data for the Assessment of Harmful Algal Blooms in the Northern Gulf of Mexico Gregory A. Carter and Dan Holiday.
Only the good die young: bottom water hypoxia as a mortality source for copepod eggs and nauplii in Chesapeake Bay Michael Roman, David Elliot and Jamie.

Only the good die young: bottom water hypoxia as a mortality source for copepod eggs and nauplii in Chesapeake Bay Michael Roman, David Elliot and Jamie.
Jensen, et. al. 2005 Winter distribution of blue crab Callinectes sapidus in Chesapeake Bay: application and cross- validation of a two- stage generalized.

Jensen, et. al Winter distribution of blue crab Callinectes sapidus in Chesapeake Bay: application and cross- validation of a two- stage generalized.

Similar presentations

Ads by Google