مدل‌سازی فرونشست دشت ابرکوه با استفاده از روش تداخل‌سنجی راداری و هوش مصنوعی

[1] Afifi, M. A. (2017). Assess the potential of land subsidence and its related factors (Case study: Plain Saidan Farouk Marvdasht). Quantitative Geomorphological Research, 5(3), 121- 132.

[2] Al-Halbouni, D., Holohan, E., Saberi, L., Alrshdan, H., Sawarieh, A., Closson, D., Walter, T. R. and Dahm, T. (2017). Sinkholes, subsidence and subrosion on the eastern shore of the Dead Sea as revealed by a close-range photogrammetric survey. Geomorphology, 285, 305-324.

[3] Azarakhsh, Z., Azadbakht, M. and Matkan, A. (2022). Estimation, modeling, and prediction of land subsidence using Sentinel-1 time series in Tehran-Shahriar plain: A machine learning-based investigation. Remote Sensing Applications: Society and Environment, 25,1-17.

[4] Bagheri, M., Dehghani, M., Ali Esmaeily, A. and Akbari, V. (2019). Assessment of land subsidence using interferometric synthetic aperture radar time series analysis and artificial neural network in a geospatial information system: case study of Rafsanjan Plain. Journal of Applied Remote Sensing 13(4), 21-42.

[5] Castellazzi, P., Arroyo-Domínguez, N., Martel, R., Calderhead, A. I., Normand, J. C., Gárfias, J. and Rivera, A. (2016). Land subsidence in major cities of Central Mexico: Interpreting InSAR-derived land subsidence mapping with hydrogeological data. International Journal of Applied Earth Observation and Geoinformation, 47, 102-111.

[6] Choopani, A., Dehghani, M. and Nikoo, M. R. (2020). Determining hydrogeological parameters of an aquifer in Sirjan Basin using Envisat ASAR interferometry and groundwater modelling. International Journal of Remote Sensing, 41(2), 655-682.

[7] Daniel, R., Maisons, C., Carnec, S., Le Mouelic, C., King, C. and Hosford, S.  (2003). Monitoring of slow ground deformation by ERS radar interferometry on the Vauvert salt mine (France) Comparison with ground-based measurement. Remote Sensing of Environment, 88(4), 468-478.

[8] Dehghani, M. (2014). An Enhanced Algorithm based on Radar Interferometry for Monitoring Land Subsidence Caused by Over-Exploitation of groundwater. Journal of Geospatial Information Technology 2(2), 61-73.

[9] Dehghani, M., Valadanzoej, M. J., Hooper, A., Hanssen, R. F., Entezam, I. and Saatchi, S. (2013). Hybrid conventional and persistent scatterer SAR interferometry for land subsidence monitoring in the Tehran Basin, Iran. ISPRS Journal of Photogrammetry and Remote Sensing, 79, 157-170.

[10] Dehghani, M., Valadanzoej, M. J., Entezam, I., Saatchi, S. and Shemshaki, A. (2011). Interferometric measurements of ground surface subsidence induced by overexploitation of groundwater. Journal of Applied Remote Sensing, 4(1), 56-73.

[11] Galloway, D. L., Erkens, G., Kuniansky, E. l. and Rowland, J. C. (2016). Preface: Land subsidence processes. Hydrogeology Journal, 24 (3), 547-550.

[12] Haddad, A. and Khorasani, E. (2019). Groundwater level changes effect on the subsidence in Semnan plain Scientific Quarterly Journal of Geosciences, 28(112), 181-190.

[13] Haghighatmehr, P., Valadanzouj, M. J., Tajik, R., Jabari, S., Sahebi, M. R., Eslami, R., Ganjiyan, M. and Dehghani, M. (2012). Time Series Analysis of Hashtgerd Subsidence Using Radar Interferometry and Global Positioning System. Scientific Quarterly Journal of Geosciences, 22(85), 105-114.

[14] Herrera, G., Tomas, R., Monells, D., Centolanza, G., Mallorqui, J., Vicente, F., Navarro, V., Lopez Sanchez, J., Sanabria, M., Cano, M. and Mulas, J. (2010).  Analysis of subsidence using TerraSAR-X data: Murcia case study. Engineering Geology, 116(3-4), 284-295.

[15] Karunasingha, D. S. K. (2022). Root mean square error or mean absolute error? Use their ratio as well. Information Sciences, 585, 609-629.

[16] Knoben, W. J., Freer, J. E. and Woods, R. A. (2019). Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores. Hydrology and Earth System Sciences, 23(10), 4323-4331.

[17] Kumar, V., Venkataramana, G. and Høgda, K. (2011). Glacier surface velocity estimation using SAR interferometry technique applying ascending and descending passes in Himalayas. International Journal of Applied Earth Observation and Geoinformation, 13(4), 545–551.

[18] Maleki, A. and Rezaee, P. (2016). Forecast locations at risk of subsidence plain Kermanshah. The Journal of Spatial Planning, 20(1), 235-251.

[19] Mokhtari, D., Ebrahimy, H. and Salmani, S. (2019). Land subsidence susceptibility modeling using random forest approach (Case study: Tasuj plane catchment). Journal of RS and GIS for Natural Resources, 10(3), 93-105.

[20] Pourab Consulting Engineers, (2012). Geology and Hydrogeology Report (Abarkouh), Regional Water Company of Yazd. 173 Pp.

[21] Pourkhosravani, M. (2014). Geoduality Theory. Geography and Environmental Planning, 25(1), 25-36.

[22] Reich, N. G., Lessler, J., Sakrejda, K., Lauer, S. A., Iamsirithaworn, S. and Cummings, D. A. (2016). Case study in evaluating time series prediction models using the relative mean absolute error. The American Statistician, 70(3), 285-292.

[23] Saffari, A., Jafari, F., and Tavakoli Sabour, S. M.  (2016). Monitoring its land subsidence and its relation to groundwater harvesting case study: Karaj Plain – Shahriar. Quantitative Geomorphological Research, 5(2), 82-93.

[24] Sousa, J.J., Ruiz, A.M., Bakon, M., Lazecky, M., Hlavacova, I., Patrício, G., Delgado, J.M. and Perissin, D., (2016). Potential of C-Band SAR interferometry for dam monitoring. Procedia Computer Science, 100, 1103–1114.

[25] USGS. (2017). https://ca.water.usgs.gov/land_subsidence/

[26] Wang, W. and Lu, Y. (2018). Analysis of the mean absolute error (MAE) and the root mean square error (RMSE) in assessing rounding model. In IOP conference series: materials science and engineering, 324(1), 1-10. 

[27] Zhu, L., Gong, H., Li, X., Li, Y., Su, X. and Guo, G. (2013). Comprehensive analysis and artificial intelligent simulation of land subsidence of Beijing, China. Chinese Geographical Science, 23(2), 237-248.