Document Type : Original Article
Highlights
آقایاری، لیلا؛ عابدینی، موسی؛ اصغری سراسکانرود، صیاد. (1401). برآورد میزان فرونشست با استفاده از تکنیک تداخل سنجی راداری و پارامترهای آبهای زیرزمینی و کاربری اراضی (مطالعه موردی: دشت اردبیل). پژوهشهای ژئومورفولوژی کمّی، 11(1)، 117-132. doi: 10.22034/gmpj.2022.304999.1302
المدرسی، سیدعلی؛ حشمتی، شیما. (1394). مدلسازی فرونشست دشت نیشابور با استفاده از سریهای زمانی و تکنیک DINSAR. مجله جغرافیا و برنامهریزی محیطی، 26 (1)، ۸۴-۶۷.
آمیغپی، معصومه؛ عربی، سیاوش؛ طالبی، علی. (1388). بررسی فرونشست یزد با استفاده از روش تداخل سنجی راداری و ترازیابی دقیق. مجله علوم زمین، 20 (77)، 164-157.
بابایی، سیدساسان؛ خزایی، صفا؛ قاصرمبارکه، فروزان. (1396). پردازش سری زمانی تداخل سنجی تصاویر راداری COSMO-SkyMed به منظور محاسبه نرخ فرونشست در محدوده سازههای زمینی و زیرزمینی در شهر تهران. نشریه علوم و فنون نقشه برداری، 7 (1)، ۶۷-۵۵.
صالحیمتعهد، فهیمه: حافظی مقدس، ناصر؛ لشکری پور، غلامرضا؛ دهقانی، مریم. (1398). ارزیابی فرونشست زمین به کمک تلفیق روش تداخل سنجی راداری و اندازهگیریهای میدانی و مطالعه دلایل و اثرات آن بر شهر مشهد. نشریه زمین شناسی مهندسی، 13 (3)، 463-435.
صفاری، امیر؛ جعفری، فرهاد؛ توکلی صبور، سیدمحمد. (1395). پایش فرونشست زمین و ارتباط آن با برداشت آبهای زیرزمینی (مطالعه موردی: دشت کرج-شهریار). پژوهشهای ژئومورفولوژی کمی، 5 (2)، ۹۳-۸۲.
گنجائیان، حمید. (1399). مخاطرات ژئومورفولوژیک مناطق شهری، روشهای مطالعه و راهکارهای کنترل آن. نشر انتخاب، 114 صفحه.
گنجائیان، حمید؛ منبری، فاطمه؛ قاسمی، افشان؛ نصرتی، مژگان. (1401). ارزیابی و تحلیل مخاطره فرونشست در دشت کبودرآهنگ-فامنین. مجله سپهر، 31 (124)، 86-75.
مقصودی، یاسر؛ امانی، رضا؛ احمدی، حسن. (1398). بررسی رفتار فرونشست زمین در منطقه غرب تهران با استفاده از تصاویر سنجنده سنتینل ۱ و تکنیک تداخلسنجی راداری مبتنی بر پراکنشگرهای دائمی. مجله تحقیقات منابع آب ایران، 15 (1)، ۳۱۳-۲۹۹.
مهرابی، علی؛ کریمی، صادق؛ خالصی، مهران. (1402). تحلیل فضایی فرونشست دشت جیرفت با استفاده از تکنیک پیکسلهای کوهرنس (CPT). جغرافیا و برنامهریزی محیطی، 34(1)، 99-116. doi: 10.22108/gep.2022.133667.1525
Agarwal, V., Kumar, A., Gee, D., Grebby, S., Gomes, R. L., Marsh, S. 2021. Comparative Study of Groundwater-Induced Subsidence for London and Delhi Using PSInSAR. Remote Sens, 13 (23). http://dx.doi.org/10.3390/rs13234741
Bokhari, R., Shu, H., Tariq, A., Al-Ansari, N., Guluzade, R., Chen, T., Jamil, A., Aslam, M. 2023. Land subsidence analysis using synthetic aperture radar data, Heliyon, 9 (3). https://doi.org/10.1016/j.heliyon.2023.e14690
Bozzano, F., Esposito, C., Franchi, S., Mazzanti, P., Perissin, D., Rocca, A. 2015. Understanding the subsidence process of a quaternary plain by combining geological and hydrogeological modelling with satellite InSAR data: the acque albule plain case study. Remote Sens. 168, 219–238. https://doi.org/10.1016/j.rse.2015.07.010
Chen, M., Tomás, R., Li, Zh., Motagh, M., Li, T., Hu, L., Gong, H., Li, X., Yu, J., Gong, X. 2016. Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry, Remote Sens, 8(6), 468. http://dx.doi.org/10.3390/rs8060468
Chen.C., Wang.C., Chen Kuo. L. 2010. Correlation between groundwater level and variations in land subsidence area of the Choshuichi Alluvial Fan. Taiwan. Geology, 115, 122–131. http://dx.doi.org/10.1016/j.enggeo.2010.05.011
Dong, S., Samsonov, S., Yin, H., Ye, S., Cao, Y. 2014. Time-series analysis of subsidence associated with rapid urbanization in Shanghai, China measured with SBAS InSAR method. Environmental earth sciences, 72(3), 677-691. http://dx.doi.org/10.1007/s12665-013-2990-y
Eastman,J. R. (2006). IDRISI Andes. Guide to GIS and Image Processing. Clark Labs, Clark University, Worcester, MA. https://www.researchgate.net/profile/Ronald-Eastman-2/publication/242377547
Higgins, S., Overeem, I., Tanaka, A., & Syvitski, J. M. 2013. Land subsidence at aquaculture facilities in the Yellow River delta, China. Geophysical Research Letters, 40, 3898–3902. http://dx.doi.org/10.1002/grl.50758
Hsieh, C., Shih, T., Hu, J., Tung, H., Huang, M., Angelier, J. 2011. Using differential SAR interferometry to map land subsidence: A case study in the Pingtung Plain of SW Taiwan. Nat. Hazards. 58, 1311–1332. http://dx.doi.org/10.1007/s11069-011-9734-7
Khorsandi Aghai, A. 2015. Survey of land subsidence– case study: The land subsidence formation in artificial recharge ponds at South Hamadan Power Plant, northwest of Iran, Indian Academy of Sciences, J. Earth Syst. 1, 261–268. http://dx.doi.org/10.1007/s12040-014-0532-y
Li, Y., Zuo, X., Xiong, P., Chen, Z., Yang, F., Li, X., 2022. Monitoring Land Subsidence in North-central Henan Plain using the SBAS-InSAR Method with Sentinel-1 Imagery Data, Journal of the Indian Society of Remote Sensing, V 50, pp: 635–655. https://ui.adsabs.harvard.edu/link_gateway/2022JISRS..50..635L/doi:10.1007/s12524-021-01484-6
Malik, K., Kumar, D., Perissin, D., Pradhan, B. 2022. Estimation of ground subsidence of New Delhi, India using PS-InSAR technique and Multi-sensor Radar data, Estimation of ground subsidence of New Delhi, India using PS-InSAR technique and Multi-sensor Radar data, Advances in Space Research, 69 (4), 1863-1882. https://doi.org/10.1016/j.asr.2021.08.032
Raucoules, D., le Mouelic, S., Carnec, C., Maisons, C., King, C. 2003. Urban subsidence in the city of Prato (Italy) monitored by satellite radar interferometry. Int. J. Remote Sens. 24 (4), pp: 891–897. http://dx.doi.org/10.1109/IGARSS.2002.1025896
Sheng, H., Zhou, L., Huang, C., Ma, S., Xian, L., Chen, Y., Yang, F. 2023. Surface Subsidence Characteristics and Causes in Beijing (China) before and after COVID-19 by Sentinel-1A TS-InSAR, Remote Sensing, 15 (5). http://dx.doi.org/10.3390/rs15051199
Shi, X., Chen, C., Dat, K., Deng, J., Wen, N., Yin, Y., Dong, X. 2022. Monitoring and Predicting the Subsidence of Dalian Jinzhou Bay International Airport, China by Integrating InSAR Observation and Terzaghi Consolidation Theory. Remote Sens. 14 (10). https://doi.org/10.3390/rs14102332
Wang, H., Jia, C., Ding, P., Feng, K., Yang, X., Zhu, X., 2022. Analysis and Prediction of Regional Land Subsidence with InSAR Technology and Machine Learning Algorithm, Journal of Civil Engineering, (25). http://dx.doi.org/10.1007/s12205-022-1067-4
Zhou, Z. 2013. The applications of InSAR time series analysis for monitoring long-term surface change in peatlands, University of Glasgow. https://theses.gla.ac.uk/4875/1/2013
Usually, land subsidence is referred to as vertical downward movements of the earth's surface, which a small horizontal vector can accompany. This phenomenon is a global and morphological problem affected by human activities and natural factors. The increasing trend of population and the development of constructions, as well as the overexploitation of underground resources, have caused the risk of subsidence to be raised as one of the critical risks in many countries, including Iran, in recent years. Considering that no special measures have been taken in Iran to prevent subsidence, the risk of subsidence will be one of the most critical challenges for advancing Iranian cities, especially cities in arid and semi-arid regions. Landslides are one of the most important natural hazards that have many consequences, but they have received less attention due to low human casualties compared to other natural disasters. The occurrence of this phenomenon in the plains and especially in urban areas causes much damage. Among the areas at risk of subsidence are the cities of Tehran province, including Pishva. Pishva is located in the Varamin Plain, a semi-arid region that has been associated with the increasing trend of population and industrial development in recent years due to its proximity to the city of Tehran. Since the increasing trend of population and human activities in this region has not been proportional to its environmental capabilities, the Pishva Plain has faced the risk of subsidence in recent years. Considering the issue's importance, in this research, the amount of subsidence in the urban area and the urban periphery of Pishva and the analysis of the factors influencing its occurrence have been evaluated.
In this research, Landsat satellite images, Sentinel 1 radar images, and library information were used as research data to achieve the desired goals. The essential tools used in the research include ENVI, IDRISI, GMT, and ArcGIS, which were used to prepare land use maps, analyze land use changes, prepare subsidence maps, and prepare final maps, respectively. Also, the models used in the research included the maximum likelihood model, LCM model, and SBAS time series model, which were used to prepare land use maps, analyze land use changes, and prepare the final subsidence map, respectively. This research has been done in two stages. In the first stage, using Landsat satellite images from 1991, 2001, 2011, and 2021, the trend of land use changes in the study area has been evaluated. In the second stage, the amount of subsidence in the studied area was evaluated using Sentinel 1 radar images, radar interferometry method, and SBAS time series.
Pishva is located in the east of Tehran. This city is located in the Varamin Plain and has faced the phenomenon of subsidence in recent years. The importance of subsidence and its imperceptible process caused this research to evaluate the subsidence rate of this plain using the SBAS time series method. The results obtained from this research have shown that the urban area and outskirts of Pishva have subsided between 107 and 411 mm during a period of 2 years. The investigations carried out in this research have shown that the main reason for the subsidence that occurred in the region was human activities. However, the geomorphological situation of the region has also provided the ground for its subsidence. The natural and human geography of Pishva city has caused this city and its adjacent areas to be associated with much development in recent years. The geomorphological situation of this region has caused it to be devoid of obstacles and limited landforms for the development of manufactured uses and agricultural lands. Also, the location of Pishva near Tehran has provided the basis for the increase in population and the development of industries in the areas adjacent to Pishva. According to the mentioned cases, natural and human factors have caused this area to undergo much development in recent years, and changes in land use have accompanied this development.
The results of this research have shown that the studied area has subsided between 107 and 411 mm during a 2-year period (2020 to 2022), based on which it can be said that the maximum annual subsidence of the area is more than 20 cm. In this research, to evaluate the effective factors in the subsidence of the region, the geomorphology and land use changes of the region from 1991 to 2021 have been investigated. The results of evaluating the region's geomorphology show that the study area corresponds to the plain and has no limiting obstacles. This problem has provided the basis for developing manufactured uses and regional agricultural lands. Also, the results of the evaluation of land use changes in the region have shown that during the 30-year period (1991 to 2021), manufactured areas have faced a significant increase, so this use had an area of 2.2 square kilometers in 1991. (Equivalent to 5.5% of the region's area), which has increased to 6.9 square kilometers (equivalent to 17.2% of the region's area) in 2021. Considering that the development of manufactured uses is associated with an increase in the pressure on the earth's surface, and also the development of residential and industrial areas is associated with an increase in the use of underground water resources, the changes in land uses during recent years, the context has provided for subsidence in the region. According to the mentioned cases, one of the main reasons for subsidence in the urban area and outskirts of Pishva has been human activities, including the development of manufactured uses.