Landslide Susceptibility Assessment in Constantine Region (NE Algeria) By Means of Statistical Models

Nabil Manchar; Chaouki Benabbas; Riheb Hadji; Foued Bouaicha; Florina Grecu

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Landslide Susceptibility Assessment in Constantine Region (NE Algeria) By Means of Statistical Models

| 21 dic 2018

Studia Geotechnica et Mechanica

Volumen 40 (2018): Edición 3 (November 2018)

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Article Category: Research Article

Publicado en línea: 21 dic 2018

Páginas: 208 - 219

Recibido: 01 jun 2018

Aceptado: 08 oct 2018

DOI: https://doi.org/10.2478/sgem-2018-0024

Palabras clave
geographic information system, probabilistic methods, information value, weight of evidence, frequency ratio

© 2018 Nabil Manchar, Chaouki Benabbas, Riheb Hadji, Foued Bouaicha, Florina Grecu published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Optical remote sensing images and air photo used for the landslides determination in the study area: a- Panchromatic satellite image. b- A landslide occurred in highway’s segment before construction (air photo). c- A neighboring road affected by a rotational landslide.

Landslide inventory map of the study area.

Landslide conditioning factor used for landslide susceptibility mapping in the study area: a- Lithology. b- Slope angle. c- Slope aspect. d- Elevation.

LSMs for a: IV, b: WoE, and c: FR. d: ROC curves of the three used models.

Spatial relationship between landslide and conditioning factors in the study.

Factor	Classes	Landslide	IV			FR			WoE
		pixels in classes	(S_if)	D_if	(D)	% of total area (a)	% of landslide area (b)	FR	W+	W-	C
Lithology	Flysch	8395	-0.343	-28.61	83.5	45.52	32.31	0.71	-0.357	0.383	-0.740
	Clay	7450	0.175	14.61		24.07	28.67	1.19	0.184	1.096	-0.911
	Marl	5188	0.710	59.29		9.81	19.97	2.03	0.762	2.150	-1.388
	Colluvium	4950	0.075	6.22		17.68	19.05	1.08	0.078	1.525	-1.447
	Marly	0	0.000	0.00		1.09	0.00	0	–	–	–
	limestone
	Limestone	0	0.000	0.00		1.13	0.00	0	–	–	–
	Travertine	0	0.000	0.00		0.70	0.00	0	–	–	–
Slope gradient (°)	0–5°	504	-3.156	-315.63	100.0	45.52	1.94	0.04	-3.202	0.722	-3.924
	5–10°	7603	0.195	19.54		24.07	29.26	1.22	0.206	1.089	-0.883
	10–15°	9870	1.354	135.37		9.81	37.99	3.87	1.503	1.993	-0.490
	15–20°	4504	-0.020	-1.99		17.68	17.33	0.98	-0.021	1.541	-1.562
	20–25°	2207	2.053	205.31		1.09	8.49	07.79	2.451	4.829	-2.377
	25–30°	678	0.842	84.15		1.13	2.61	2.32	0.908	4.527	-3.619
	>30°	618	1.219	121.93		0.70	2.38	3.38	1.342	5.057	-3.715
Rainfall (mm)	500	0	0.000	0.00	74.6	0.51	0.00	0	-	-	-
	550	22019	0.226	16.86		67.60	84.74	1.25	0.238	-1.476	1.715
	600	3964	-0.606	-45.25		27.98	15.26	0.55	-0.628	1.086	-1.715
	650	0	0.000	0.00		3.91	0.00	0	–	–	–
Distance to lineaments (m)	0–400	17409	0.070	7.04	100.0	62.44	67.00	1.07	0.074	-0.634	0.708
	400–800	8377	0.491	49.06		19.74	32.24	1.63	0.522	1.264	-0.743
	800–1200	22	-4.670	-466.96		8.89	0.08	0.01	-4.716	2.372	-7.089
	1200–1600	88	-2.616	-261.55		4.63	0.34	0.07	-2.659	3.025	-5.684
	1600–2000	88	-2.085	-208.52		2.73	0.34	0.12	-2.127	3.558	-5.684
	2000–2400	0	0.000	0.00		1.15	0.00	0	–	–	–
	2400–2800	0	0.000	0.00		0.34	0.00	0	–	–	–
	2800–3200	0	0.000	0.00		0.08	0.00	0	–	–	–
	3200–3600	0	0.000	0.00		0.00	0.00	0	–	–	–
Distance to streams (m)	0–200	23041	0.183	13.57	74.2	73.86	88.68	1.20	0.193	-1.866	2.058
	200–400	2942	-0.612	-45.38		20.87	11.32	0.54	-0.634	1.425	-2.058
	400–600	0	0.000	0.00		4.12	0.00	0	-	–	–
	600–800	0	0.000	0.00		0.98	0.00	0	–	–	–
	800–1000	0	0.000	0.00		0.17	0.00	0	–	–	–
Elevation (m)	500–600	1347	-0.424	-25.07	59.2	7.92	5.19	0.65	-0.440	2.466	-2.906
	600–700	3040	-0.520	-30.78		19.68	11.70	0.59	-0.540	1.481	-2.021
	700–800	8249	0.422	24.99		20.81	31.75	1.53	0.448	1.214	-0.765
	800–900	8607	0.811	47.96		14.73	33.12	2.25	0.873	1.575	-0.703
	900–1000	4453	0.160	9.48		14.60	17.14	1.17	0.169	1.745	-1.576
	1000–1100	288	-2.576	-152.40		14.55	1.11	0.08	-2.620	1.872	-4.492
	1100–1200	0	0.000	0.00		7.71	0.00	0	–	–	–
NDVI	-0.974–0.231	61	-3.216	-35.11	10.9	5.88	0.24	0.04	-3.261	2.785	-6.047
	0.231–0.148	154	-3.861	-42.15		28.13	0.59	0.02	-3.907	1.216	-5.123
	0.148–0.045	508	-1.110	-12.11		5.93	1.96	0.33	-1.141	2.774	-3.915
	0.045–0.151	2932	0.057	0.62		10.66	11.28	1.06	0.059	2.122	-2.062
	0.151–0.818	22328	0.554	6.05		49.40	85.93	1.74	0.590	-1.220	1.810
Stream density	0–0.2	20887	0.616	33.22	53.9	1.85	80.39	1.85	0.658	-0.752	1.411
	0.2–0.4	3478	-0.851	-45.91		0.43	13.39	0.43	-0.879	0.988	-1.867
	0.4–0.6	492	-2.057	-110.92		0.13	1.89	0.13	-2.099	1.850	-3.948
	0.6–0.8	1126	-0.426	-22.99		0.65	4.33	0.65	-0.443	2.651	-3.094
	0.8–1	0	0.000	0.00		0.00	0.00	0	–	–	–
	1–1.2	0	0.000	0.00		0.00	0.00	0	–	–	–
Slope aspect	N	7306	0.922	65.77	71.3	11.18	28.12	2.51	0.998	1.937	-0.939
	NE	2162	-0.157	-11.23		9.74	8.32	0.85	-0.165	2.235	-2.399
	E	2763	-0.092	-6.55		11.66	10.64	0.91	-0.096	2.032	-2.129
	SE	1622	-0.760	-54.21		13.35	6.24	0.47	-0.786	1.924	-2.709
	S	2380	-0.408	-29.09		13.77	9.16	0.67	-0.424	1.870	-2.294
	SW	4074	0.173	12.35		13.19	15.68	1.19	0.182	1.865	-1.682
	W	2938	-0.225	-16.07		14.16	11.31	0.80	-0.235	1.825	-2.060
	NW	2738	-0.206	-14.68		12.95	10.54	0.81	-0.215	1.924	-2.139

LD in different susceptibility zones of the study area (IV, WoE, FR)..

Susceptibility	Area		Landslide	area	LD
	km²	%	km²	%
IV
Very low	14.817	6.58	0.015	0.21	0.0323
Low	39.457	17.52	0.124	1.72	0.0981
Moderate	48.609	21.59	0.626	8.65	0.4007
High	72.912	32.38	1.553	21.46	0.6627
Very high	49.362	21.92	4.917	67.96	3.0998
FR
Very low	27.481	12.21	0.032	0.44	0.0363
Low	61.116	27.14	0.602	8.33	0.3068
Moderate	66.398	29.49	0.735	10.16	0.3446
High	49.896	22.16	5.372	74.25	3.3504
Very high	20.266	9.00	0.493	6.82	0.7577
WoE
Very low	19.669	8.74	0.015	0.21	0.0243
Low	41.123	18.26	0.097	1.33	0.0730
Moderate	56.676	25.17	0.393	5.43	0.2158
High	63.927	28.39	1.972	27.26	0.9602
Very high	43.762	19.44	4.758	65.76	3.3834

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Landslide Susceptibility Assessment in Constantine Region (NE Algeria) By Means of Statistical Models

Article Category: Research Article

Publicado en línea: 21 dic 2018

Páginas: 208 - 219

Recibido: 01 jun 2018

Aceptado: 08 oct 2018

DOI: https://doi.org/10.2478/sgem-2018-0024

Palabras clave
geographic information system, probabilistic methods, information value, weight of evidence, frequency ratio

© 2018 Nabil Manchar, Chaouki Benabbas, Riheb Hadji, Foued Bouaicha, Florina Grecu published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Spatial relationship between landslide and conditioning factors in the study.

LD in different susceptibility zones of the study area (IV, WoE, FR)..

Landslide Susceptibility Assessment in Constantine Region (NE Algeria) By Means of Statistical Models

Article Category: Research Article

Publicado en línea: 21 dic 2018

Páginas: 208 - 219

Recibido: 01 jun 2018

Aceptado: 08 oct 2018

DOI: https://doi.org/10.2478/sgem-2018-0024

Palabras clavegeographic information system, probabilistic methods, information value, weight of evidence, frequency ratio

© 2018 Nabil Manchar, Chaouki Benabbas, Riheb Hadji, Foued Bouaicha, Florina Grecu published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Spatial relationship between landslide and conditioning factors in the study.

LD in different susceptibility zones of the study area (IV, WoE, FR)..

Palabras clave
geographic information system, probabilistic methods, information value, weight of evidence, frequency ratio