A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping

Figures & data

Figure 1. Study area: (a) north of Iran; (b) Amol County; (c) surface deformation map.

Table 1. Lithology of Amol County.

Groups	Geo-units	Descriptions
Group 1	$Q_2$, $Q_{Haraz}$, $Q_1$	Old/young fans and terraces.
Group 2	${\mathrm{Q}}^{\mathrm{m}\mathrm{b}}$, ${\mathrm{Q}}^{\mathrm{c}\mathrm{p}}$	Coastal deposit with gravel and shell fragments.
Group 3	${\mathrm{Q}}^{\mathrm{a}\mathrm{l}}$	River beds and flood plain deposits.
Group 4	$Jd$, ${\mathrm{M}}^{\mathrm{m}\mathrm{s}}$, ${\mathrm{P}}^{\mathrm{l}\mathrm{q}}$	Marl, limestone and sandstone.
Group 5	$Tr{e}_2$, $K_2^{l,m}$, ${\mathrm{P}}^{\mathrm{e}\mathrm{m}}$	Thick bedded dolomitic, limestone/gypsum with marl and sandstone.

Figure 2. Nine input land subsidence factors used in the ANFIS model: (a) land use/cover; (b) ground water level; (c) aspect; (d) DEM; (e) distance to streams; (f) rainfall; (g) density of wells; (h) slope; (i) lithology.

Figure 3. ANFIS architecture (Asadpour et al. 2013).

Figure 4. The flowchart of the integrated methodology for land subsidence susceptibility mapping and accuracy assessment.

Figure 5. The extracted values of the surface deformation map to the GPS points. The first number represents the point number and the second number indicates the surface deformation map’s value at its corresponding point.

Table 2. Description of MFs and statistical criteria for RMSE, R².

No	Type of MF	Descriptions	R^2	RMSE
1	Gauss MF	Gaussian curve membership function.	0.9253	0.1531
2	Pi MF	Pi-shaped membership function.	0.9037	0.1569
3	Tri MF	Triangular-shaped membership function.	0.9195	0.1673
4	Trap MF	Trapezoidal-shaped membership function.	0.9048	0.1507
5	Dsig MF	Difference of two sigmoid membership functions.	0.9032	0.1702
6	Gbell MF	Generalized bell curve membership function.	0.913	0.1701

Figure 6. Training and validation data, with the location of GPS points.

Figure 7. Land subsidence susceptibility maps using the ANFIS model with six different MFs, namely: (a) Dsig MF; (b) Gauss MF; (c) Gbell MF; (d) Pi MF; (e) Trap MF; (f) Tri MF.

Figure 8. ROC curves for the resulting maps of the six MFs.

Asadpour, V., Ravanfar, M.R., and Fazel-Rezai, R., 2013. Adaptive network fuzzy inference systems for classification in a brain computer interface. In: R. Fazel-Rezai, ed. Brain-computer interface systems: Recent progress and future prospects. London: IntechOpen, 43–59.

 Google Scholar