Integrated approach of RUSLE, GIS and ESA Sentinel-2 satellite data for post-fire soil erosion assessment in Basilicata region (Southern Italy)

Figures & data

Figure 1. Geographical localization of Basilicata region (left) and study sites (right).

Figure 2. (a) Geological sketch map of the Southern Apennines and surrounding areas; (b) geological cross-section (from Piedilato and Prosser 2005).

Figure 3. Soil erosion after wildfire (Pisticci, Basilicata).

Figure 4. Miglionico fire aerial image. (source: Civil Protection Department - Basilicata Region).

Figure 5. Stigliano fire aerial image. (source: Civil Protection Department - Basilicata Region).

Figure 6. Rifreddo fire aerial image. (source: Civil Protection Department - Basilicata Region).

Table 1. Sentinel-2 overview.

Sentinel-2 Bands	Central wavelength (nm)	Resolution (m)	Bandwidth (nm)
Band 1 – Coastal aerosol	443	60	27/45 (2A/2B)
Band 2 – Blue	490	10	98
Band 3 – Green	560	10	45/46 (2A/2B)
Band 4 – Red	665	10	38/39 (2A/2B)
Band 5 – Vegetation Red Edge	705	20	19/20 (2A/2B)
Band 6 – Vegetation Red Edge	740	20	18
Band 7 – Vegetation Red Edge	783	20	28
Band 8 – NIR	842	10	115
Band 8A – Narrow NIR	865	20	20
Band 9 – Water vapour	945	60	20
Band 10 – SWIR – Cirrus	1375	60	20
Band 11 – SWIR	1610	20	90
Band 12 – SWIR	2190	20	180

Figure 7. Sentinel-2 Multispectral Instrument (MSI) imagery (26 August 2017). True-colour composite of Red, Green and Blue bands in Bottom-of-Atmosphere reflectance data.

Table 2. Spatial datasets sources used for the five RUSLE factors.

Factor	Source
R	Functional Center for Civil Protection of Basilicata region – Precipitation data Departmental Cartographic Center of Basilicata region – DTM 5 m
K	JRC’s European Soil Data Centre (ESDAC) – K-factor High Resolution dataset
LS	Departmental Cartographic Center of Basilicata region – DTM 5 m
C	Vegetation map
P	Departmental Cartographic Center of Basilicata region – DTM 5 m

Table 8. Range and Mean of RUSLE factors and soil loss prediction.

	R - Factor (MJ·mm·ha^−1·h^−1·yr^−1 )			K - Factor (Mg·h·Mj^−1·mm^−1)						LS - Factor adimensional
				Pre-fire			Post-fire			Pre-fire			Post-fire
	min	max	mean	min	max	mean	min	max	mean	min	max	mean	min	max	mean
Brienza	5074	5350	5192	0,0189	0,0269	0,0230	0,0302	0,0754	0,0477	0	38,65	8,96	0	39,99	13,89
Stigliano	3838	4070	3958	0,0233	0,0327	0,0262	0,0373	0,0981	0,0639	0	39,50	6,85	0	44,9	10,22
Miglionico	3923	4101	4028	0,0263	0,0409	0,0334	0,0421	0,1085	0,0736	0	41,65	14,93	0	44,9	15,37
Rifreddo	3335	3542	3429	0,0182	0,0277	0,0221	0,0291	0,0742	0,0502	0	28,79	4,36	0	44,8	6,553

Figure 8. Landsat image (left) acquired on 13 August 2015 (RGB 321) and Vegetation Map (right).

Table 3. Fire events and Sentinel-2 data.

Fire name	Sentinel-2 image pre-fire	Sentinel-2 image post-fire	Wildfire data
Miglionico fire	3 August 2017	11 August 2017	4–5 August 2017
Rifreddo fire	6 August 2017	16 August 2017	9–11 August 2017
Stigliano fire	6 August 2017	16 August 2017	9–10 August 2017
Brienza fire	6 August 2017	26 August 2017	16–21 August 2017

Figure 9. Miglionico fire. Upper: Sentinel-2 image (pre-fire); Sentinel image (post-fire). Lower: dNBR; dNBR (range).

Figure 10. Rifreddo fire. Upper: Sentinel-2 image (pre-fire); Sentinel image (post-fire). Lower: dNBR; dNBR (range).

Figure 11. Stigliano fire. Upper: Sentinel-2 image (pre-fire); Sentinel image (post-fire). Lower: dNBR; dNBR (range).

Figure 12. Brienza fire. Upper: Sentinel-2 image (pre-fire); Sentinel image (post-fire). Lower: dNBR; dNBR (range).

Table 4. Burned surface distribution per fire severity class.

Severity classes	Brienza		Stigliano		Miglionico		Rifreddo
	%	ha	%	ha	%	ha	%	ha
Unburned	3.933	9.95	0.28	0.27	9.28	14.69	2.85	7.77
Very low	5.617	4,21	3.24	3.07	8.08	12.72	5.14	13.99
Low	49.589	125,46	15.69	14.89	37.43	58.94	24.12	65.66
Moderate	35.107	88,82	23.71	22.5	29.8	46.93	35.9	97.71
High	5.751	14,55	45.70	43.36	15.42	24.28	29.9	81.37
Very high	0.004	0,01	11.38	10.8			2.09	5.68
Total	100	253	100	94.89	100	157.48	100	272.18

Figure 13. Fire-modified RUSLE factors maps of Brienza (left) and Miglionico (right).

Figure 14. Fire-modified RUSLE factors maps of Stigliano (left) and Rifreddo (right).

Figure 15. Pre-fire (left) and post-fire (right) RUSLE A value. From the top to bottom: Miglionico, Rifreddo, Stigliano, Brienza. Values are expressed in Mg ha⁻¹ yr⁻¹.

Table 5. Pre-fire and post-fire erosion range distribution – RUSLE classes in Mg ha⁻¹yr⁻¹.

RUSLE classes	BRIENZA				STIGLIANO				MIGLIONICO				RIFREDDO
	Rusle pre-fire		Rusle post-fire		Rusle pre-fire		Rusle post-fire		Rusle pre-fire		Rusle post-fire		Rusle pre-fire		Rusle post-fire
	%	ha	%	ha	%	ha	%	ha	%	ha	%	ha	%	ha	%	ha
0–1	93.05	235.41	1.652	4.18	89.93572	85.34	7.387501	7.01	78.14	123.05	0.81	1.27	99.07	269.65	3.58	9.75
1–10	6.95	17.59	14.241	36.03	10.062428	9.55	23.7749	22.56	21.86	34.43	23.27	36.64	0.93	2.53	68.43	186.25
10–30	0	0	47.767	120.85	0	0	45.54748	43.22	0	0	33.08	52.1	0	0	2.75	68.57
30–70	0	0	32.526	82.29	0	0	91.81241	18.8	0	0	33.64	52.97	0	0	2.75	7.49
70–120	0	0	3.810	9.64	0	0	3.361787	3.19	0	0	8.89	14	0	0	0.04	0.12
>120	0	0	0.004	0.01	0	0	0.115924	0.11	0	0	0.32	0.5	0	0	0	0
Total	100	253	100	253	100	94.89	100	94.89	100	157.48	100	157.48	100	272.18	100	272.18

Table 6. Estimated soil losses per year for the studied sites before and after fire (1st year).

Overall estimated post-fire soil losses Tn/yr	Brienza		Miglionico		Stigliano		Rifreddo
	Pre-fire	Post-fire	Pre-fire	Post-fire	Pre-fire	Post-fire	Pre-fire	Post-fire
	114.74	7133.94	86.52	4956.75	39.34	2070.5	40.94	2350.41

Table 7. Average RUSLE A pre-fire and first year post-fire.

Brienza		Miglionico		Stigliano		Rifreddo
Av. Rusle A Pre-fire (Mg ha^−1yr^−1)	Av. Rusle A Post-fire (Mg ha^−1yr^−1)	Av. Rusle A Pre-fire (Mg ha^−1yr^−1)	Av. Rusle A Post-fire (Mg ha^−1yr^−1)	Av. Rusle A Pre-fire (Mg ha^−1yr^−1)	Av. Rusle A Post-fire (Mg ha^−1yr^−1)	Av. Rusle A Pre-fire (Mg ha^−1yr^−1)	Av. Rusle A Post-fire (Mg ha^−1yr^−1)
0.4535	28.1974	0.5494	31.4754	0.4146	21.819	0.1504	8.6355

Table 9. Comparison between average post-fire RUSLE for all severity classes and average post-fire RUSLE A for fire severity class ‘High’.

Brienza		Miglionico		Stigliano		Rifreddo
Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)	Av. Rusle A post-fire (Mg ha^−1yr^−1)
All fire severity classes classes	Fire severity class ‘High’	All fire severity classes classes	Fire severity class ‘High’	All fire severity classes classes	Fire severity class ‘High’	All fire severity classes classes	Fire severity class ‘High’
28.1974	54.6429	31.4754	67.7122	21.819	25.0651	8.6355	11.5584

Figure 16. dRUSLE-dNBR linear regression analysis. dRUSLE (Mg ha⁻¹ yr⁻¹) is the difference between RUSLE A post-fire and RUSLE A pre-fire.

Figure 17. Data distribution for C, K, LS and pre- and post-fire RUSLE-estimated erosion (Mg ha⁻¹ yr⁻¹) for each site. The bottom, the centre and the top of the boxplots represent, respectively, the first, the second and the third quartile of the data distribution. The whiskers extend 1.5 times the interquartile range (IQR).

Table

	C-Factor (adimensional)						RUSLE A (Mg·ha^−1·yr^−1)
	Pre-fire			Post-fire			Pre-fire			Post-fire
	min	max	mean	min	max	mean	min	max	mean	min	max	mean
Brienza	0,001	0,265	0,043	0,40	0,95	0,759	0	7,9	0,45	0	122,65	28,2
Stigliano	0,001	0,265	0,064	0,42	0,93	0,804	0	4.6	0,41	0	146,21	21,82
Miglionico	0,001	0,265	0,092	0,49	0,97	0,887	0	4.41	0,55	0	160,01	31.48
Rifreddo	0,001	0,265	0,060	0,32	0,98	0,775	0	2,53	0,15	0	84,5	8,64

Piedilato S, Prosser G. 2005. Thrust sequences and evolution of the external sector of a fold and thrust belt: example from the Southern Apennines (Italy). J Geodyn. 39(4):386–402.

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