A strategy for GIS-based 3-D slope stability modelling over large areas

Mergili, M.; Marchesini, I.; Alvioli, M.; Metz, M.; Schneider-Muntau, B.; Rossi, M.; Guzzetti, F.

doi:10.5194/gmd-7-2969-2014

Articles | Volume 7, issue 6

https://doi.org/10.5194/gmd-7-2969-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-7-2969-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 7, issue 6

Development and technical paper

|

15 Dec 2014

Development and technical paper |

| 15 Dec 2014

A strategy for GIS-based 3-D slope stability modelling over large areas

M. Mergili, I. Marchesini, M. Alvioli, M. Metz, B. Schneider-Muntau, M. Rossi, and F. Guzzetti

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Aug 2014	51	25	4	80
Sep 2014	25	30	2	57
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Nov 2014	10	27	3	40
Dec 2014	64	63	3	130
Jan 2015	23	42	2	67
Feb 2015	20	19	2	41
Mar 2015	34	15	4	53
Apr 2015	51	17	30	98
May 2015	29	14	12	55
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Oct 2015	18	19	3	40
Nov 2015	18	15	0	33
Dec 2015	13	20	2	35
Jan 2016	26	27	3	56
Feb 2016	17	5	2	24
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May 2016	13	7	4	24
Jun 2016	9	5	2	16
Jul 2016	11	9	5	25
Aug 2016	12	13	3	28
Sep 2016	8	3	0	11
Oct 2016	13	4	3	20
Nov 2016	12	11	2	25
Dec 2016	6	10	1	17
Jan 2017	28	10	1	39
Feb 2017	12	12	4	28
Mar 2017	24	50	9	83
Apr 2017	40	52	11	103
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Jun 2017	44	19	8	71
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Mar 2018	16	50	4	70
Apr 2018	22	40	2	64
May 2018	10	42	3	55
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Jul 2018	16	59	1	76
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Oct 2018	22	56	4	82
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Aug 2023	50	8	2	60
Sep 2023	48	14	1	63
Oct 2023	67	16	1	84
Nov 2023	41	8	1	50
Dec 2023	57	22	4	83
Jan 2024	57	16	1	74
Feb 2024	42	20	0	62
Mar 2024	58	27	4	89
Apr 2024	58	11	7	76
May 2024	36	23	4	63
Jun 2024	32	19	3	54
Jul 2024	24	18	3	45
Aug 2024	20	9	3	32
Sep 2024	20	14	1	35
Oct 2024	35	12	2	49
Nov 2024	23	6	3	32
Dec 2024	20	21	1	42
Jan 2025	17	20	1	38
Feb 2025	42	16	3	61
Mar 2025	28	14	1	43
Apr 2025	39	27	0	66
May 2025	40	19	1	60
Jun 2025	41	24	0	65
Jul 2025	36	29	2	67
Aug 2025	62	52	1	115
Sep 2025	44	42	0	86
Oct 2025	43	37	2	82
Nov 2025	46	45	6	97
Dec 2025	4	0	4

Cumulative views and downloads (calculated since 11 Aug 2014)

Month	HTML	PDF	XML	Total
Aug 2014	51	25	4	80
Sep 2014	25	30	2	57
Oct 2014	25	80	3	108
Nov 2014	10	27	3	40
Dec 2014	64	63	3	130
Jan 2015	23	42	2	67
Feb 2015	20	19	2	41
Mar 2015	34	15	4	53
Apr 2015	51	17	30	98
May 2015	29	14	12	55
Jun 2015	28	13	0	41
Jul 2015	30	16	0	46
Aug 2015	10	19	1	30
Sep 2015	14	25	0	39
Oct 2015	18	19	3	40
Nov 2015	18	15	0	33
Dec 2015	13	20	2	35
Jan 2016	26	27	3	56
Feb 2016	17	5	2	24
Mar 2016	17	16	0	33
Apr 2016	4	13	0	17
May 2016	13	7	4	24
Jun 2016	9	5	2	16
Jul 2016	11	9	5	25
Aug 2016	12	13	3	28
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Dec 2016	6	10	1	17
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Mar 2017	24	50	9	83
Apr 2017	40	52	11	103
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Oct 2018	22	56	4	82
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Nov 2022	45	17	0	62
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Jan 2023	48	18	1	67
Feb 2023	53	18	1	72
Mar 2023	74	9	1	84
Apr 2023	37	23	0	60
May 2023	35	14	1	50
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Aug 2023	50	8	2	60
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Oct 2023	67	16	1	84
Nov 2023	41	8	1	50
Dec 2023	57	22	4	83
Jan 2024	57	16	1	74
Feb 2024	42	20	0	62
Mar 2024	58	27	4	89
Apr 2024	58	11	7	76
May 2024	36	23	4	63
Jun 2024	32	19	3	54
Jul 2024	24	18	3	45
Aug 2024	20	9	3	32
Sep 2024	20	14	1	35
Oct 2024	35	12	2	49
Nov 2024	23	6	3	32
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Mar 2025	28	14	1	43
Apr 2025	39	27	0	66
May 2025	40	19	1	60
Jun 2025	41	24	0	65
Jul 2025	36	29	2	67
Aug 2025	62	52	1	115
Sep 2025	44	42	0	86
Oct 2025	43	37	2	82
Nov 2025	46	45	6	97
Dec 2025	4	0	4

Latest update: 02 Dec 2025

Short summary

The article deals with strategies to (i) reduce computation time and to (ii) appropriately account for uncertain input parameters when applying an open source GIS sliding surface model to estimate landslide susceptibility for a 90km² study area in central Italy. For (i), the area is split into a large number of tiles, enabling the exploitation of multi-processor computing environments. For (ii), the model is run with various parameter combinations to compute the slope failure probability.