Application of drone technologies in

quantifying stranded Sargassum

Joseph WeekesHazel A. Oxenford, Kimberly Baldwin

39th AMLC Scientific MeetingEnvironmental variability in the wider Caribbean and the ecological, social and economic consequences.

Punta Cana, Dominican Republic, 20-24 May 2019

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Background• Massive influxes of sargassum since 2011• New normal requiring adaptation and

management • Lack of standard monitoring guidelines to

determine how much, when and where sargassum is stranding

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Project Aim To assess the applicability of using drone technology together with GIS analysis to:

• Detect • Map • Quantify

Sargassum seaweed beach strandings

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Study Area

• Walkers Long Pond beach, NE coast of Barbados

• 2 km stretch of coastline

• 200 ha of beach area

• Located outside designated ‘no-fly areas’

• Not cleaned of sargassum

Walkers Long Pond

Methods • Flew drone over pre-selected area of

beach (every 2 weeks June-Sept 2018)

• Used conventional quadrat survey simultaneously

• Quadrat method used to:• Ground-truth drone images

(spectral signatures)• Provide independent estimate of

sargassum cover and volume• Provide volume to wet-weight and dry-

weight conversions• Species composition

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• DJI Inspire I and Phantom 4 Pro drones• DroneDeploy© software • Flight parameters same for each survey:

• Flight altitude (90 m)• Path overlap (front 85%, side 75%)• Area covered (same flight plan)

• Flight times (15-20 min)• Flight speed (14-16 m/sec)• Number of images (approx. 400)• Automated processing time for

orthomosaic image (approx. 1 hr)

DJI Inspire I

Methods: Drone surveys

Phantom 4 Pro

Methods: Drone surveys

Supervised classification

Fresh goldenOld

golden

Old dry

Estimating volume

Mapping cover• ArcMap © GIS software • Supervised classification (using MLC tool)• Trained MLC algorithm using 2 steps

• By eye • By known quadrats (small subset)

• Checked accuracy using quadrats (all)• Calculated cover of each sargassum class

(using Zonal Geometry tool)Estimating volume• DroneDeploy© software• Using ‘Volume’ and ‘Stock pile analysis’ tools• Drew polygons around sargassum classes

Methods: Quadrat surveys • Selection of focal area (300 x 90 m)

• Five straight-line transects (75 m apart)

• Set perpendicular to tide line• Square PVC quadrat frames (0.5 × 0.5m)

placed every 5m along the transect• Quadrat photographed • Sargassum ‘class’ recorded• Sargassum volume measured in bucket

Fresh golden

Old golden

Old dry

300 m

21940 m2

Methods: Quadrat surveys

• Full bucket of fresh sargassum collected• 1 kg sub-sample sorted into species• Dried at 76oC for 24 hr and re-weighed• Quadrat photographs processed using

CPCe software to determine exact area of sargassum cover (cm2)

• Quadrat mean cover extrapolated to focal area

S. natans VIIIS. fluitans III

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June 22 2018

August 9 2018

September 20 2018

Results: Drone surveys Orthomosiac images

Supervised Classification Accuracy Assessment

Survey Date

Sargassum class

Producers accuracy

(%)

User accuracy

(%)

Overall accuracy

(%)

Kappa coefficient

31 July 2018

Fresh golden 93.3 88.7

77.3 0.76Old golden 87.9 91.5

Old dry 77.4 69.6

Results: Drone surveys

KAPPA shows moderate level of

agreement between cell classification &

Ground Data

Results: Drone surveys

Processed image showing map of cover by sargassum ‘classes’

22 June 2018

Sargassum class

Cover (m2)

Cover(%)

Fresh golden 2,231 10.2

Old golden 7,364 33.6

Old dry 9,470 43.2

All 19,065 86.922 June 2018

Mapping Cover

Sargassum area cover by drone method versus cover by transect method

Results: Comparison

Sargassum class

DroneCover (m2)

QuadratCover(m2)

Fresh golden 2,231 2,361

Old golden 7,364 4,073

Old dry 9,470 9,091

All 19,065 15,53322 June 2018 All surveys

Mapping Cover

Results: Quadrat surveys additional Information

Sargassum class

Cover (m2)

Cover(%)

Volume (m3)

Wet weight

(mt)

Dry weight

Fresh golden 2,054 9.4 262.2 30.8 7.53

Old golden 1,650 7.5 201.5 - -

Old dry 6,045 27.6 354.1 - -

All 9,750 44.4 817.8 - -

Mapping cover, volume and biomass

31 July 2018

Results: Quadrat surveys additional Information

Species Composition

S. fluitans S. natans

VIII

31-Jul

S. fluitans

S. natans I

S. natans VIII

9-Aug

S. fluitans S. natans I

31-Aug

Key Messages Detecting• Drones now relatively inexpensive, easy to fly and excellent for detecting

sargassum remotely• Information can be collected very fast!• Flight plan can be stored and repeated each survey

Mapping• Georeferenced mapping requires greater skill level (knowledge of GIS)• Drones with a high resolution camera allow accurate classification and

mapping from orthomosaic image• Accuracy can be improved by using ground-truthing points

Key Messages Quantification• Quantifying sargassum from images requires GIS skills• Surface area can be calculated from orthomosaic image for each class• Volume of sargassum could not be measured due to changing beach profile

Value added• Some in situ sampling can add significant value

• Ground truthing identification of sargassum classes• Volume (recommend using replicate quadrats for fresh golden

sargassum only)• Wet to dry weight conversions and species composition

Thank you to our volunteers!

Renata GoodridgeAnnabel CoxCarla DanielsLeisl Brewster

Charleen Charles