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KIT The Research University in the Helmholtz Association Institute for Geography and Geoecology (ifgg) www.kit.edu Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data Teja Kattenborn, Javier Lopatin, Michael Förster, Fabian Fassnacht

Mapping of invasive plant species with Sentinel-1 and -2 ... · 5 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based

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Page 1: Mapping of invasive plant species with Sentinel-1 and -2 ... · 5 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based

KIT – The Research University in the Helmholtz Association

Institute for Geography and Geoecology (ifgg)

www.kit.edu

Mapping of invasive plant species with Sentinel-1

and -2 data calibrated with UAV-based training data

Teja Kattenborn, Javier Lopatin, Michael Förster, Fabian Fassnacht

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Institute for Geography and Geoecology (ifgg)2

Rationale

Invasive plant species can pose major threats to

biodiversity, ecosystem functioning and services

Sentinel-1 (SAR) and Sentinel-2 (Multispectral)

satellite data have unpreceded spatial and

temporal resolution with global coverage

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Early, R. et al. (2016), Nature Communications

Sentinel-1(SAR) Sentinel-2 (Multispectral)

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Institute for Geography and Geoecology (ifgg)3

Rationale

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV photogrammetry Sentinel data

Field sampling is

expensive and

time consuming

Field sampling is

often biased by

accessibility

Linking discrete field samples

to the remote sensing scale

is challenging

Field samples often do

no match the ‘bird

perspective’

Visual interpretation

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Institute for Geography and Geoecology (ifgg)4 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Study site

Pinus radiata Acacia dealbata Ulex europaeus

RGB camera

Canon 100D

Hyperspectral camera

(Gamaya-Oxi, 400-900nm)

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Institute for Geography and Geoecology (ifgg)5 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Visual

interpretation of

UAV products

Automatic classification

(MaxEnt) using UAV–

based predictors

Upscaling from UAV

(0.1m) to the Sentinel

scale (10m) by

random forest

Proposed workflow

Digitial Elevation Model

RGB

RGB

Texture (2D)

Structure (3D)

Hyperspectral 400-900nm

Sentinel-2 (multispectral)

Sentinel-1 (SAR)

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Institute for Geography and Geoecology (ifgg)6 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV-based classification

Pinus radiata Acacia dealbata Ulex europaeus

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Institute for Geography and Geoecology (ifgg)7 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV-based classification

Manmade

objects

Native

shrubs

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Institute for Geography and Geoecology (ifgg)8 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV to Sentinel – Pinus radiata

Native

Broadleaf

evergreen

forest

Pinus

radiata

Native beech

forest

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Institute for Geography and Geoecology (ifgg)9

UAV to Sentinel – Acacia dealbata

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Predicted likelihood / cover fraction

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Institute for Geography and Geoecology (ifgg)10

UAV to Sentinel – Ulex europaeus

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Predicted likelihood / cover fraction

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Institute for Geography and Geoecology (ifgg)11

UAV to Sentinel – Pinus radiata

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Predicted likelihood / cover fraction

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Institute for Geography and Geoecology (ifgg)12 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV to Sentinel – statistical summary

Variable importance Sentinel-1: 8-16%

Variable importance Sentinel-2: 84-92 %

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Institute for Geography and Geoecology (ifgg)13

Conclusions & Outlook

Invasive species can be quite accurately mapped using

UAVs when combining different predicors

UAV-based estimates can be accurately up-scaled to the

Sentinel scale

→Promising alternative to traditional field sampling!

Sentinel-2 (Multispectral) was more important than Sentinel-

1 (SAR) for up-scaling species cover

Workflow is transferable to other sensors and endmembers

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Sentinel-2 Sentinel-1

>

Landsat?Biodiversity assessments?

Tree species classifcation?

Habitat mapping?

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Institute for Geography and Geoecology (ifgg)14

Thank you for your attention!

[email protected]

Institute for Geography and Geoecology (IFGG),

Karlsruher Institute of Technology

21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

Thank you for your attention!

[email protected]

Institute for Geography and Geoecology (IFGG)

Karlsruher Institute for Technology (KIT)

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Institute for Geography and Geoecology (ifgg)15 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data

UAV to Sentinel – Pinus radiata

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Institute for Geography and Geoecology (ifgg)16 21.12.2018 Teja Kattenborn - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data