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Presentation: Fee & Brigley
Remote sensing was used to map coastal environments in Nova Scotia for various applications. In Little Harbour, multispectral imagery was classified to map eelgrass extent. For Isle Madame, imagery was classified to inventory land cover and assess vulnerability to oil spills. In Shag Harbour, multispectral imagery and lidar were used to map rockweed spatial distribution for a seaweed company. High resolution coastal data allows efficient environmental monitoring and management.
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Presentation: Fee & Brigley
- 1. Remote Sensing Applicationsin the Coastal Environment By Matthew Brigley and Natasha Fee
- 2. Overview • Eelgrass Mapping LittleHarbour, NS • Tanker Safety Program Isle Madame, NS • Acadian Seaplants Limited Shag Harbour, NS
- 3. Little Harbour Eelgrass Mapping Departmentof Fisheries and Oceans
- 4. Little Harbour Eelgrass Mapping Purpose: 1. To classify the spatial extent of coastal eelgrass. 2. To inventory the near-coast environment. Data: Multispectral Imagery (RGB + NIR) Source: Cornell Extension Marine Program
- 5. Eelgrass Significance Amongthe most productive & Biologically diverse ecosystems Functions: Seafloor & Shoreline Stabilization, Flora & Fauna habitat, supports the Detrital food web foundation. Considered a sentinel species for evaluating ecosystem health Biggest Disturbances: Declining water quality & Physical Disturbance
- 6. Multispectral Imagery VisibleIssues: Swirls/blocky sections throughout the mosaic. Color balancing Issue at the sensor level
- 7. Image Classification Resample 20cm ->2m Maximum Likelihood Classification Sieve Filter Threshold: 20px Workflow
- 8. Isle Madame World ClassTanker Safety Program Department of Fisheries and Oceans & Transport Canada
- 9. Isle Madame World ClassTanker Safety Program Purpose 1. To create an inventory of the coastal land cover in areas with heavy tanker traffic. This will be used to: 1. Determine the area’s vulnerability to marine-sourced oil spills. 2. Plan future tanker routes in order to minimize the impact on vulnerable coastlines. 3. Develop Area Response Plans to be use in the event of a spill. Data: Multispectral Imagery (RGB + NIR) Source: Transport Canada
- 10. Significance Each year,80 million tonnes of oil are shipped in Canadian coastal waters (Transport Canada) Oil is transported by waves and accumulates in the intertidal zone Knowing the intertidal zone’s composition is paramount Source: National Park Service (USA) Source: Jacqui Michel - Research Planning Inc.
- 11. Imagery Overview ofthe study area (5cm resolution). Note: Mosaic produced by Nathan Crowell
- 12. Classification Clip •Change 0 valuesto NoData Generate Signature Files •Select training areas from 1 image per flight line Maximum Likelihood Classification •Using 1 signature file per flight line Workflow
- 13. Mosaic per FlightLine Create Mosaic Dataset • Creates empty mosaic datasets for each flight line (11 in total) Add Rasters to Mosaic Dataset • Using a wildcard to differentiate flight lines (ie. o_ims001_*) Build Seamlines •Method: Radiometric •No smoothing (categorical data) Mosaic to New Raster •Generates a mosaicked image for each flight line Workflow
- 14. Class Aggregation Add Field •“Class”-> A number from 1-10 representing universal classes Lookup Tool •Generates a raster for each flight line based on the universal “Class” field Class ID Classes 1 Sand 2 Pebbles 3 Rocks 4 Eelgrass 5 Rockweed 6 Coastal Grasses 7 Driftwood 8 Shadow 9 Deep Water 10 Cultural Features Workflow
- 15. Final Mosaic Create MosaicDataset • Creates an empty mosaic dataset Add Rasters to Mosaic Dataset • Adds each mosaicked flight line to the final mosaic dataset Build Seamlines •Method: Radiometric •No smoothing (categorical data) Mosaic to New Raster •Generates a mosaic based on the composite of all 11 flight lines
- 16. Tidal Ranges Basedon a 2m DEM Values required: Type Value Source Chart Datum Offset 0.545m Canadian Hydrographic Service Lowest Astronomical Tide (LAT) Highest Astronomical Tide (HAT) LAT: -0.36m (CD), - 0.905m (CGVD28) HAT: 2.16m (CD), 1.615m (CGVD28) Closest active tidal gage was used as a proxy (North Sydney) • Acquired 19 years worth of hourly data (01-01-1999 to 01-01-2015) • Minimum and maximum tidal height values were found with Excel • Converted from Chart Datum to CGVD28 ortho-height using the Chart Datum Offset for North Sydney Tidal Surge (1m & 2m) 2.615m and 3.615m HAT + surge value
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- 19. Shag Harbour Rockweed Mapping AcadianSeaplants Limited
- 20. Shag Harbour Rockweed Mapping Purpose To determine the rockweed’s spatial extent. Data: Multispectral Imagery (RGB + NIR) Bathymetric LiDAR Source: Acadian Seaplants Limited
- 21. Rockweed Significance Playsa very important role in the Bay of Fundy ecosystem Fish & Waterfowl Used in fertilizer production Stimplex Source: Acadian Seaplants Limited Source: AGRG
- 22. Multispectral Imagery Overviewof the study area (20cm resolution).
- 23. Image Classification Maximum LikelihoodClassification Sieve Filter Threshold: 20px Workflow
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- 28. LiDAR Low Tide +High Tide
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- 30. LiDAR - TIN HighTide Low Tide
- 31. LiDAR – TINto Raster
- 32. 5m LiDAR sectionin Shag Harbour
- 33. High Tide Dataset:Ground Class
- 34. High Tide Dataset:Ground + Rockweed
- 35. Accuracy Assessment (LiDARvs. Ground Truth) • Utilizing ArcMap 10.4’s new LAS tool, (LAS Point Statistics by Area), statistics including Min Z, Max Z, Mean Z, & Standard Deviation were calculated inside of a 5, 3, and 1 meter buffer. • The buffers were generated around individual Ground Truth GPS points, eight were used in this assessment. • The results were statistics derived out of the LiDAR points that could then be compared to the same measurements collected through Ground Truth.
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- 38. Conclusions High resolutionmultispectral imagery can be a valuable asset to decision-makers Allows for the acquisition of surface data on a large scale More efficient than ground-based techniques Based off of the results comparing the Ground Truthing to the LiDAR collected: It’s plausible that just flying a high tide scan could provide the user with enough information to map the inventory of coastal vegetation. More transects would have to be evaluated on accuracy and the ground class would have to be a bit more refined.
- 39. Acknowledgement Special thanksto: AGRG for the opportunity, data, and guidance Canadian Hydrographic Service