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National Aeronautics and
Space Administration
Donnie Kirk (Project Lead)
Caitlin Toner
Emily Gotschalk
Rachel Cabosky
Brad Gregory
Candace Kendall
Improving the Capacity of Everglades
National Park to Monitor Mangrove
Extent Using NASA Earth Observations
Everglades Ecological Forecasting
Components
Objectives
Community Concerns
Study Area and Period
NASA Satellites & Sensors
Methodology
Results
Conclusions
Errors & Uncertainties
Future Work
Image Source : Wikimedia
Community Concerns
 Freshwater is important for
the Everglades
 Difficult to map and monitor
mangrove extent
 The National Park Service
(NPS) does not have
updated maps
Image Credit : National Park Service
Objectives
1. Utilize NASA Earth
observations and
Google Earth Engine
2. Create a replicable
methodology
3. Map the extent of
change
4. Forecast future
changes to the park
Image Source : Wikimedia
Study Area
 Everglades National Park
coastline
 Stratified random sampling
 Temporal analysis
NASA Satellites and Sensors
Landsat 8
Landsat 5
Methodology This is a Landsat
image clipped to the
ecotone samples in a
false color composite.
 Data Collection
 Random Sampling
 Spatial Analysis
Methodology
Image Modification
Everglades 2015
Methodology
Methodology
Classification
Methodology
Results
Classification of
five ecotone
samples
Results
1995 2005 2015
Results
seed 1
92 11 0 0 0 0 0
1 55 0 0 0 0 0
0 0 112 0 0 0 0
0 0 0 81 2 4 0
20 0 13 0 89 0 0
0 0 0 12 0 84 0
0 3 0 0 0 0 64 577
643
Accuracy 0.897356 %
seed 2
117 5 0 0 4 0 0
6 44 0 0 0 0 0
0 0 52 0 1 0 35
0 0 0 97 0 17 0
0 0 3 0 30 0 0
0 0 0 3 0 84 0
0 0 0 0 0 0 120 544
618
Accuracy 0.880259 %
seed 42
40 2 0 0 0 0 0
17 64 0 8 0 0 4
0 2 49 0 0 0 3
0 0 13 36 1 44 0
0 0 1 8 30 0 0
0 0 0 9 0 34 0
0 2 3 0 0 0 80 333
450
Accuracy 0.74 %
Average
( 0.897356 0.880259 0.74 )
=
0.839205 %
2015 Error Matrices
Transition Maps
1995-2005 2005-2015
Conclusions
Image Source:
Wikimedia
Winter 2005 Summer 2005
Error and Uncertainties
 Interpolation
 Classification
 Calculations
 Seasonality
Future Work
 Use in situ data
 Include more samples
 Focus on ecological forecasting
Image Source : Wikimedia
Acknowledgements
This material is based upon work supported by NASA through contract NNL11AA00B and cooperative agreement NNX14AB60A. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration
A special thank you to our contributors for their time and assistance with this project
Advisors
Dr. Kenton Ross, NASA DEVELOP National Program Science Advisor
Project Partners
Jed Redwine, National Park Service, Everglades National Park (ENP)
Ecologist, South Florida Natural Resources Center
Dr. Hans-Peter Plag: Group on Earth Observations (GEO) Blue Planet Initiative (BPI) and
Mitigation and Adaptation Research Institute (MARI)
Marguerite Madden, University of Georgia
Others
Brittany Zajic, NASA DEVELOP National Program Geoinformatics Fellow
Noel Gorelick, Engineer at Google

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2016EvergladesFinalPresentation

  • 1. National Aeronautics and Space Administration Donnie Kirk (Project Lead) Caitlin Toner Emily Gotschalk Rachel Cabosky Brad Gregory Candace Kendall Improving the Capacity of Everglades National Park to Monitor Mangrove Extent Using NASA Earth Observations Everglades Ecological Forecasting
  • 2. Components Objectives Community Concerns Study Area and Period NASA Satellites & Sensors Methodology Results Conclusions Errors & Uncertainties Future Work Image Source : Wikimedia
  • 3. Community Concerns  Freshwater is important for the Everglades  Difficult to map and monitor mangrove extent  The National Park Service (NPS) does not have updated maps Image Credit : National Park Service
  • 4. Objectives 1. Utilize NASA Earth observations and Google Earth Engine 2. Create a replicable methodology 3. Map the extent of change 4. Forecast future changes to the park Image Source : Wikimedia
  • 5. Study Area  Everglades National Park coastline  Stratified random sampling  Temporal analysis
  • 6. NASA Satellites and Sensors Landsat 8 Landsat 5
  • 7. Methodology This is a Landsat image clipped to the ecotone samples in a false color composite.  Data Collection  Random Sampling  Spatial Analysis
  • 14. Results seed 1 92 11 0 0 0 0 0 1 55 0 0 0 0 0 0 0 112 0 0 0 0 0 0 0 81 2 4 0 20 0 13 0 89 0 0 0 0 0 12 0 84 0 0 3 0 0 0 0 64 577 643 Accuracy 0.897356 % seed 2 117 5 0 0 4 0 0 6 44 0 0 0 0 0 0 0 52 0 1 0 35 0 0 0 97 0 17 0 0 0 3 0 30 0 0 0 0 0 3 0 84 0 0 0 0 0 0 0 120 544 618 Accuracy 0.880259 % seed 42 40 2 0 0 0 0 0 17 64 0 8 0 0 4 0 2 49 0 0 0 3 0 0 13 36 1 44 0 0 0 1 8 30 0 0 0 0 0 9 0 34 0 0 2 3 0 0 0 80 333 450 Accuracy 0.74 % Average ( 0.897356 0.880259 0.74 ) = 0.839205 % 2015 Error Matrices
  • 17. Winter 2005 Summer 2005 Error and Uncertainties  Interpolation  Classification  Calculations  Seasonality
  • 18. Future Work  Use in situ data  Include more samples  Focus on ecological forecasting Image Source : Wikimedia
  • 19. Acknowledgements This material is based upon work supported by NASA through contract NNL11AA00B and cooperative agreement NNX14AB60A. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration A special thank you to our contributors for their time and assistance with this project Advisors Dr. Kenton Ross, NASA DEVELOP National Program Science Advisor Project Partners Jed Redwine, National Park Service, Everglades National Park (ENP) Ecologist, South Florida Natural Resources Center Dr. Hans-Peter Plag: Group on Earth Observations (GEO) Blue Planet Initiative (BPI) and Mitigation and Adaptation Research Institute (MARI) Marguerite Madden, University of Georgia Others Brittany Zajic, NASA DEVELOP National Program Geoinformatics Fellow Noel Gorelick, Engineer at Google