Development of a processing chain of multispectral Sentinel ...

Development of a processing chain of multispectral Sentinel–2 data to extract meandering river courses

for geomorphometric analysis in Central Amazonia Region

NOÉMI KÓSA* and Balázs Székely

ELTE Eötvös Loránd University, Department of Geophysics and Space Science, Hungary

* [email protected]

https://doi.org/10.5194/egusphere-egu2020-17488

https://meetingorganizer.copernicus.org/EGU2020/EGU2020-17488.html

INTRODUCTION

Freely-meandering rivers are sensitive indicators of neotectonic activity in low-relief areas.

The first objective of this project was to develop a processing chain of multispectralSentinel–2 data to extract meandering river courses.

Then sinuosity analysis has been carried out on 20 main rivers and tributaries of CentralAmazonia Region as an aid for localization of river channel patterns influenced by on-goingtectonic activity.

Petrovszki et al. 2012

(Timár 2003, Zámolyi et al. 2010, Petrovszki et al. 2012, Ibanez et al. 2014)

Kósa & Székely EGU2020-17488

STUDY AREACentral Amazonia Region

• Situated in an intracratonic Paleozoic sedimentary basin

• Topography caracterized by low relief

• Intraplate tectonics since Miocene

• Drained by right-bank tributaries of the Amazon River: Preto da Eva, Urubu, Anebá, Uatumã, Jatapu, Nhamundà

• Seasonal variations in rainfall

• Densely vegetated

SATELLITE DATA

• wide-swath

• high-resolution

• multispectral

• radiometrically and geometrically corrected

• 100×100 km2

• UTM, WGS84ESA Sentinel-2 Data

Images from June to October (dry season)Fletcher 2012


DATA PROCESSING CHAIN

Different rivers (colour, width) → needs more spectral filteringMultispectral

satellite images

Resampling &

Spectral Filtering

Binarizing

Skeletonizing

Creatingpolylines

Vectorized

river sections

Noise removal

Continous digitizedriver sections

a quick and accurate way to digitize river sections


SINUOSITY INDEX CALCULATIONContinous digitized

river sections

S: sinuosity index assigned to point P

A: window size (along-track distance)

D: shortest path-length

d: resolution

Defining differentwindow sizes

Sinuosity Index Calculation

Tímár 2003

Classification of values Visualization RESULTS


RESULTSName Number

Digitized

length

Urubu 1 141,5 km

Uatumã 2 169,4 km

Abacate 3 90,7 km

Capucapu 4 163,3 km

Cararà 5 56,3 km

Jatapu 6 349,5 km

Nhamundà 7 412,3 km

Igarapé Pitinga 8 83,6 km

Igarapé Jauari 9 40,2 km

Acari 10 84,3 km

Cachorrinho 11 139,9 km

Cachorro 12 227 km

Rio das Antas 13 74,8 km

Rio do Prato 14 75,3 km

Igarapé Repartimento 15 50 km

Turuna 16 128,3 km

Rio Velho 17 56,2 km

Igarapé Caxipacoro 18 127,8 km

Igarapé Água Fria 19 61,5 km

Rio Acapu 20 164,2 km

Sinuosity values calculated on 20 main rivers and tributaries.

Analysis of distribution of sinuosity variations using:• classification• various representations (mapping, cross-plots, spectrum)

1

1,5

2

2,5

3

3,5

1 1,5 2


Small window size (1 000 - 2 000 – 5 000 m)

Natural Breaks Classification

Sensitive for small, short wavelength, zigzag shape meanders.

Used for making cross-plots (x-axis):

1

1,5

2

2,5

3

3,5

4

1 1,5 2 2,5 3

SI v

alu

esca

lcu

late

dw

ith

20 0

00 m

win

do

wsi

ze

SI values calculated with 1000 m window size

Sinuosity values of AcapuRiver


Medium window size (10 000 – 20 000 m)

Useful for detecting channel sinuositychanges that could indicate recentvertical crustal movements!

Natural Breaks Classification

Cross-plots (y-axis):

1

1,5

2

2,5

1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6SI v

ales

calc

ula

ted

wit

h20

000

m

win

od

wsi

ze


Sinuosity values of Rio das Antas


Large window size (25 000 m – )

SI values of Nhamundà River, window size: a) 10 000 m, b) 20 000 m, c) 40 000 m

Sinuosity spectrum of Nhamundà River

As the visualization methodscomplement each other thevariations in sinuosity values can behighlighted and verified in severalaspects.

1

2

3

4

1 2 3 4 5 6 7 8 9SI v

alu

esca

lcu

late

dw

ith

20

000

m

win

do

wsi

ze


Sinuosity values of Nhamundà River

The case of Nhamundà River


CONCLUSIONS

The results compared to former neotectonic studies some significant sinuosity changes can be correlated to known faults (Costa 1996).

The mentioned sinuosity variations coincides with the location of NW–SE normal and thrust faults active since Pleistocene times and NE–SW Miocene normal faults supporting the idea that these structures may have beenreactivated (Ibanez 2014).

Multi-window sinuosity index calculation applied to satellite data based digitized water

courses is a useful tool for recognizing recent tectonic activity in large low-relief areas,

such as Central Amazonia.

Our data processing method of high resolution satellite images provides a quick andaccurate way to digitize river sections of a large part of the sedimentary basin.

THANK YOU FOR YOUR ATTENTION!Questions and suggestions are welcome!


https://doi.org/10.5194/egusphere-egu2020-17488

https://meetingorganizer.copernicus.org/EGU2020/EGU2020-17488.html

REFERENCES• COSTA, J. B. S. (1996): A neotectônica na Amazônia. In: Simpósio de Geologia da Amazônia, 5., Belém. Anais... Belém:

SBG/NO, 1996, v. 1, p. 35-8.

• FLETCHER, K. (2012): Sentinel-2: ESA's optical high-resolution mission for GMES operational services. Noordwijk: ESA Communications.

• IBANEZ, D.M., RICCOMINI, C., DE MIRANDA, F.P. (2014): Geomorphological evidence of recent tilting in the CentralAmazonia Region. Geomorphology 214:378-387.

• PETROVSZKI, J., SZÉKELY, B., TIMÁR, G. (2012): A systematic overview of the coincidences of river sinuosity changes and tectonically active structures in the Pannonian Basin. Global and Planetary Change 98–99:109-121.

• TIMÁR, G. (2003): Controls on channel sinuosity changes: a case study of the Tisza River, the Great Hungarian Plain. Quaternary Science Reviews 22:2199-2207.

• ZÁMOLYI, A, SZÉKELY, B, DRAGANITS, E, TIMÁR, G. (2010): Neotectonic control on river sinuosity at the western margin of the Little Hungarian Plain. Geomorphology 122(3-4):231-243.


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