hyperspectral remote sensing and analysis of intertidal zones: a contribution to monitor coastal...

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Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity Benjamin D. Hennig(1), Christopher B. Cogan(2), Inka Bartsch(2) GI_Forum Salzburg July 4 2007 (1) Department of Geography, University of Cologne (2) Alfred-Wegener Institute for Polar and Marine Research, Bremerhaven

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Page 1: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Hyperspectral remote sensing

and analysis of intertidal zones:

A contribution to monitor coastal biodiversity

Benjamin D. Hennig(1), Christopher B. Cogan(2), Inka Bartsch(2)

GI_Forum Salzburg

July 4 2007

(1) Department of Geography, University of Cologne

(2) Alfred-Wegener Institute for Polar and Marine Research, Bremerhaven

Page 2: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Overview:Hyperspectral remote sensing and analysis of intertidal zones

1. Introduction:

Research goals

and study area

2. Data and analysis approach

3. Results:

Biotope classification

and data accuracy

4. Perspectives of GIS-RS-based

environmental monitoring

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 2

Page 3: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Study area

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 3

Page 4: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Helgoland Northern Intertidal

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 4

Page 5: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Biotopes in the study area

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 5

Abrasion platform of the northern intertidal

Red algae area (Mastocarpus)

Musselbed with brown algae

(Mytilus and Fucus)

Green algae zone (Enteromorpha)

Page 6: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Working scheme

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 6

Page 7: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Data

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 7

Imaging Spectrometer

ROSIS 03

Page 8: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Image Analysis

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 8

Page 9: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Biotope classification

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 9

Page 10: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Biotope classification

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 10

Page 11: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Reference Data

Cla

ssif

ied

Data

No

Ve

ge

tatio

n

Bro

wn A

lgae

De

nse

Bro

wn

Alg

ae

Re

d A

lga

e

Gre

en A

lgae

Kelp

Vegeta

ted

Ch

an

ne

ls

Mussel bed

Barn

acle

s

To

tal

Us

er´

s

Accu

rac

y %

No Veget. 9 6 15 60

Brown Algae 19 9 4 32 59,4

Dense Brown

Algae38 4 42 90,5

Red Algae 24 2 26 92,3

Green Algae 18 18 100

Kelp 3 17 8 28 60,7

Vegetated

Channels1 3 20 24 83,3

Mussel bed 27 9 36 75

Barnacles 3 12 30 45 66,7

Total 12 19 38 37 22 20 40 39 39 266 76,4

Producer’s

accuracy %75 100 100 64,9 81,8 85 50 69,2 76,9 78,1 75,9

Thematic accuracy

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 11

Page 12: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Location accuracy

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 12

Page 13: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Field work

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 13

Page 14: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Integrated GIS-RS-analysis approaches

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 14

Page 15: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Sylt

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 15

Page 16: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Comparative Study:Rocky vs.muddy intertidal

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 16

Page 17: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

PerspectivesThe presented methods are suitable fundaments for

scientific and applied fields in the conservation

of biodiversity – not only in coastal

environments:

• GIS-RS integration provides a powerful tool in

geospatial data acquisition especially in

inaccessible and small scale or heterogeneous

environments

• Integrated monitoring systems allow the

combination of different levels of resolution as

well as different data sources which are needed

to detect significant changes in ecosystems

• to monitor ecological conditions standards of

data acquisition need to be evaluated for certain

environments

• with the growing range and continuous upgrade

of multi- and hyperspectral sensors (air- and

spaceborne) data availability increases

significantly contributing to the availability of a

wide range of data for monitoring systems

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 17

Page 18: Hyperspectral remote sensing and analysis of intertidal zones: A contribution to monitor coastal biodiversity

Thanks for your attention!

The presented study has been conducted at

the Alfred-Wegener-Institute for Polar and

Marine Research (AWI Bremerhaven) for

Diplom-thesis research at the Department of

Geography, University of Cologne

(Germany)

Field work has been conducted with the

support of the Biologische Anstalt Helgoland

(BAH) and the Wadden Sea Station Sylt

(List)

Thanks to

Christopher B. Cogan, Inka BartschAlfred-Wegener Institute for Polar and Marine Research,

Bremerhaven (Germany)

1. Introduction – 2. Data analysis – 3. Results – 4. Perspectives

Hyperspectral remote sensing and analysis of intertidal zones

Benjamin D. Hennig

GI_Forum Salzburg, 4.07.2007

University of Cologne

Department of Geography

Slide: 18