Feasibility study of flood risk monitoring based on optical satellite data

Satellite/Sensor		Ikonos	Eros A	QuickBird	OrbView-3	Eros B	KOMP SAT-2	CARTO SAT-2	World-View-1
Nationality/Company		GeoEye (previously Space Imaging), USA	ImageSat International, Israel	Digital Globe, USA	OrbImage, USA	ImageSat International, Israel	KARI, South Korea	ISRO, India	Digital Globe, USA
Operating time		since 24.09.1999	since 05.12.2000	18.10.2001 – 17.12.2014	26.06.2003 – 03.2007	since 25.04.2006	since 28.07.2006	since 10.01.2007	since 18.09.2007
Orbit altitude [km]		681-709	475-491	450	470	500	685	630	496
Spectral bands [um]	PAN	0.45-0.90	0.50-0.90	0.45-0.90	0.45-0.90	0.50-0.90	0.50-0.90	0.50-0.85	0.45-0.80
	MS	0.45-0.52		0.45-0.52	0.45-0.52		0.45-0.52
		0.52-0.61		0.52-0.60	0.52-0.60		0.52-0.60
		0.64-0.72		0.63-0.69	0.62-0.69		0.63-0.69
		0.72-0.88		0.76-0.90	0.76-0.90		0.76-0.90
Spatial resolution[m]	PAN	0.82×0.82	1.0×1.0 -1.8×1.8	0.61×0.61	1×1	0.7×0.7	1×1	0.8×0.8	0.50×0.50
Spatial resolution[m]	MS	3.28×3.28		2.44×2.44	4×4	1.9×1.9	4×4
Radiometric resolution [bit]		11	11	11	11	11	10	11	11
Footprint [km]		11×11	13.5×13.5	16×16	8×8	14×14	15×15	9.6×9.6	17.6×17.6
Maximum angle of incidence		+/- 45°	+/- 43°	+/- 30°	+/- 45°	+/- 45°	+/- 60°	+/- 45°	+/- 45°
Satellite/ Sensor		Geoeye-1	WorldView-2	CartoSat-2B	Plèiades-1A	KOMPSAT-3	Plèiades-1B	World-View-3	KOMPSAT-3A
Nationality/Company		GeoEye (previously Space Imaging), USA	Digital Globe, USA	ISRO, India	CNES, AIRBUS Defence & Space, France	KARI, South Korea	CNES, AIRBUS Defence & Space, France	Digital Globe, USA	KARI, South Korea
Operating time		since 06.09.2008	since 08.10.2009	since 12.07.2010	since 17.12.2011	since 17.05.2012	since 02.12.2012	since 13.08.2014	since 25.03.2015
Orbit altitude [km]		681	770	637	694	685	694	617	528
Spectral bands[um]	PAN	0.45-0.90	0.45-0.80	0.45-0.85	0.48-0.83	0.45-0.90	0.48-0.83	0.45-0.80	0.45-0.90
	MS	0.45-0.52	0.40-0.45		0.43-0.55	0.45-0.52	0.43-0.55	0.40-0.45	0.45-0.52
		0.52-0.60	0.45-0.52		0.49-0.61	0.52-0.60	0.49-0.61	0.45-0.51	0.52-0.60
		0.63-0.70	0.51-0.58		0.60-0.72	0.63-0.69	0.60-0.72	0.51-0.58	0.63-0.69
		0.76-0.90	0.59-0.63		0.75-0.95	0.76-0.90	0.75-0.95	0.59-0.63	0.76-0.90
			0.63-0.69					0.63-0.69
			0.71-0.75					0.71-0.75
			0.77-0.90					0.77-0.90
			0.86-1.04					0.86-1.04
Spatial resolution [m]	PAN	0.41×0.41	0.46×0.461	0.8×0.8	0.5×0.5	0.7×0.7	0.5×0.5	0.31×0.311	0.5×0.5
Spatial resolution [m]	MS	1.65×1.65	1.84×1.84		2×2	2.8×2.8	2×2	1.24×1.24	2×2
Radiometric resolution [bit]		11	11	10	12	14	12	11	14
Footprint [km]		15×15	16.4×16.4	9.6×9.6	20×20	15×15	20×20	13.1×13.1	12×12
Maximum angle of incidence		+/- 60°	+/-45°	+/-45°	+/-45°	+/-45°	+/-45°	+/-45°	+/-45°

[i] Source: own elaboration based on: Airbus Defence and Space 2018, Satellite Imaging Corporation 2018, DigitalGlobe 2018, ESA Earth Online 2018.

Table 2

Selected high resolution (HRS) optical satellite data parameters

Satellite/Sensor		LANDSAT-7/ETM+	SPOT5	ALOS/PRISM/AVNIR-2	SPOT6/7	LDCM/OLI	Sentinel-2A	Sentinel-2B
Nationality/Company		NASA, USA	AIRBUS Defence & Space (previously SpotImage), France	JAXA, Japan	AIRBUS Defence & Space, France	NASA, USA	ESA, European Union	ESA, European Union
Operating time		since 15.04.1999	04.05.2002 -31.03.2015	since 24.01.2006	since 12.09.2012	since 11.02.2013	since 23.06.2015	since 07.03.2017
Orbit altitude [km]		705	832	692	832	705	786	786
Spectral bands [um]	PAN	0.52-0.90	0.48-0.71	0.52-0.77	0.455-0.745	0.500-0.680	0.430-0.457	0.420-0.465
	MS	0.45-0.52	0.50-0.59	0.42-0.50	0.455-0.525	0.433-0.453	0.448-0.546	0.443-0.541
		0.52-0.60	0.61-0.68	0.52-0.60	0.530-0.590	0.450-0.515	0.538-0.583	0.536-0.582
		0.63-0.69	0.78-0.89	0.61-0.69	0.625-0.695	0.525-0.600	0.646-0.684	0.646-0.685
		0.76-0.90	1.58-1.75	0.76-0.89	0.760-0.890	0.630-0.680	0.694-0.713	0.694-0.714
		1.55-1.75				0.845-0.885	0.731-0.749	0.730-0.748
		10.40-12.50				1.560-1.660	0.769-0.797	0.766-0.794
		2.08-2.35				2.100-2.300	0.763-0.908	0.767-0.900
						1.360-1.390	0.848-0.881	0.848-0.880
							0.932-0.958	0.930-0.957
							1.336-1.411	1.339-1.415
							1.542-1.685	1.540-1.681
							2.081-2.323	2.067-2.305
Spatial resolution [m]	PAN	15×15	2.5×2.5, 5.0×5.0	2.5×2.5	1.5×1.5	15×15	10×10	10×10
Spatial resolution [m]	MS	30×30	10×10	10×10	6.0×6.0	30×30	10×10 20×20 60×60	10×10 20×20 60×60
Radiometric resolution [bit]		8	8	8	12	12	12	12
Footprint [km]		185×185	60×60	70×70	60×60	185×185	290	290
Maximum angle of incidence		0°	+/- 31°		+/- 27°	0°	+/-46°	+/-46°

[i] Source: own elaboration based on: Airbus Defence and Space 2018, Satellite Imaging Corporation 2018, ESA Earth Online 2018.

Table 3

Damage identification based on VHRS 0.3 m × 0.3 m pixel optical data

Type of damage	Damage	Dimensions (approximate)	Spectral ranges	Estimated accuracy of results
Damage/loss of ground	Den, cavity, tunnel caused by the activity of burrowing animals	0.1 - 1 m	VIS, NIR	0.3 - 0.6 m
Surface damage	Traces in the crown of the levees	0.1 - 0.3 m	VIS, NIR	0.15 - 0.30 m

[i] Source: Own elaboration

Table 4

Damage identification based on VHRS 0.5 m × 0.5 m optical data

Type of damage	Damage	Dimensions(approximate)	Spectral ranges	Estimated accuracy of results
Surface damage	Wild crossings	0.3 - 1 m	VIS, NIR	0.3 - 0.5 m
Surface damage	Defects in the body and on the sides of the levees caused by wild and burrowing animals	Unspecified	VIS, NIR	0.3 - 0.5 m
Slope deformation	Local soil runoff	Unspecified	VIS, NIR	0.3 - 0.5 m

[i] Source: Own elaboration

Presents damaged flood banks caused by animals. The holes were caused by the beavers living in the area. Grazing animals on the levees and in their immediate vicinity violates the construction of levees and causes changes in soil mass. Photo by Janusz Orzepowski

Table 5

Damage identification based on HRS 2 m × 2 m optical data

Type of damage	Damage	Dimensions (approximate)	Spectral ranges	Estimated accuracy of results
Surface defects	Theft of part of the infrastructure	2 - 10 m	VIS, NIR	1 - 2 m
Surface damage	Transhumance within the body of the levee	2 - 10 m	VIS, NIR	1 - 2 m
Landslides	Possibility of landslide in the section with very low geotechnical parameters	from several to dozens of metres	VIS, NIR	1 - 2 m
Landslides	Undercutting of the base of the levee by the current of the river during floods	from several to dozens of metres	VIS, NIR	1 - 2 m
Cracks in the body	Longitudinal slits	5 - 15 m	VIS, NIR	1 - 2 m
Blur of the shaft	May occur when the flood wave elevation is greater than the lowest point of the levee crown	Unspecified	NIR	1 - 2 m

[i] Source: Own elaboration

Presents an example of a landslide in Poland in 2015 and levee surface damage caused by people. Photo by Janusz Orzepowski

Workflow of optical satellite imagery analysis
Source: Own elaboration

Bare soil detection based on Plèiades data (a) using MSAVI (b) and NDVI (c)
Source: Own elaboration based on Pleiades data

Detection of water bodies based on WorldView-2 (a) data using NDVI (b), SAVI (c), SARVI (d), WV-WI (e) and NDWI (f) - results comparison with reference data (a)
Source: Own elaboration based on WorldView-2 data

Table 6

Assessment of the accuracy of determining the range of water bodies on the basis of index images obtained from WorldView-2 data (partly cloudy)

Index	Threshold values	Correctly detected water	Error of omission	Error of commission
DVI	<-30	71.61%	28.39%	2.93%
NDVI	<-0.14	94.76%	5.24%	10.04%
NDVI	<-0.15	94.40%	5.60%	7.54%
NDVI	<-0.16	93.99%	6.01%	5.68%
NDVI	<-0.22	89.73%	10.27%	1.40%
NDWI	>0.32	78.57%	21.43%	6.24%
SAVI	<-0.20	94.96%	5.04%	12.01%
SAVI	<-0.25	93.66%	6.43%	4.71%
SAVI	<-0.27	92.97%	7.03%	3.49%
OSAVI	<-0.25	90.22%	9.78%	1.56%
SARVI	<-0.4, 0.0>	88.48%	11.52%	15.01%
ARVI	<-0.1	85.06%	4.37%	14.94%
WV-WI	-0.5	93.36%	6.64%	19.88%
WV-WII	<29	91.26%	8.74%	16.49%

[i] Source: Own elaboration

References

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DOI: https://doi.org/10.2478/mgrsd-2018-0011 | Journal eISSN: 2084-6118 | Journal ISSN: 0867-6046 (formerly 2084-6118)

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Language: English

Page range: 172 - 180

Submitted on: Jan 21, 2018

Accepted on: Apr 14, 2018

Published on: Sep 30, 2018

Published by: Faculty of Geography and Regional Studies, University of Warsaw

In partnership with: Paradigm Publishing Services

Keywords:

floods,

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© 2018 Beata Weintrit, Katarzyna Osińska-Skotak, Magdalena Pilarska, published by Faculty of Geography and Regional Studies, University of Warsaw
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 22 (2018): Issue 3 (September 2018)

Feasibility study of flood risk monitoring based on optical satellite data

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