الگوی فضایی آسیب پذیری محیط زیست در ایران

جغرافیا و مخاطرات محیطی

مقاله 1، دوره 13، شماره 3 - شماره پیاپی 51، آبان 1403، صفحه 1-34   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/geoeh.2023.84603.1417

نویسندگان

حبیب الله صادقی^{* 1}؛ افشین دانه کار^{* 2}؛ محمدجلال عباسی شوازی^{3، 4، 5}

¹دانشجوی دکتری جمعیت شناسی، دانشکده علوم اجتماعی، دانشگاه تهران، تهران، ایران.

²استاد گروه محیط‌زیست، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران.

³عضو آکادمی، موسسه جمعیت شناسی وین، اتریش

⁴استاد گروه جمعیت شناسی، دانشکده علوم اجتماعی، دانشگاه تهران، تهران، ایران

⁵استاد مدعو، موسسه مطالعات جمعیتی، دانشگاه ملی استرالیا، کانبرا، استرالیا

چکیده

شناخت سطح خرد آسیب­ پذیری محیط­ زیست از لحاظ فنی و نظری به‌عنوان نقشه راه دقیق در پایداری محیط­ زیست عمل می ­کند. با­وجود این ضعف داده و عدم قطعیت روشی فهم درست مسائل ناشی از آن را مغفول گذاشته است. مقاله پیش­رو با استفاده از تصاویر ماهواره ­ای کدنویسی شده گوگل ­ارث­ انجین (GEE) و روش خودهمبستگی فضایی گتیس در قالب نظریه ­ی «آسیب ­پذیری» به بررسی و تحلیل الگوهای فضایی آسیب‌پذیری محیط‌زیست 397 شهرستان ایران طی ­سال­ های 1390 تا 1400 می­ پردازد. نتایج آزمون گتیس نشان دهنده توزیع نابرابر و الگوهای متنوع آسیب‌پذیری شهرستان‌های ایران در ابعاد مختلف ازجمله آلودگی هوا، گازهای گلخانه‌ای، تغییرات دما و بارش، کاهش آب‌های زیرزمینی، تهدید تنوع زیستی و فرسایش خاک، به‌ویژه در مناطق مرکزی، جنوب، شرق و نوار شمالی خواهد بود. به همین ترتیب، این پژوهش با تأکید بر نقش الگوهای فضایی متفاوت در ابعاد «حساسیت» و «قرار گرفتن در معرض خطر»، پیشنهاد می‌کند که سیاست‌گذاری‌های محیط‌زیستی در ایران باید با توجه به نابرابری‌های فضایی و متناسب با ویژگی‌های جمعیتی و بوم‌شناختی هر منطقه تنظیم شوند. این رویکرد می‌تواند به بهبود ظرفیت سازگاری و کاهش آسیب‌پذیری محیط­زیستی در مناطق بحرانی کمک کند. استفاده از تکنیک‌های الگوریتمی برای شاخص‌سازی آسیب‌پذیری محیط­زیستی و تلفیق داده‌های فضایی با تحلیل‌های جمعیتی، چارچوبی مؤثر برای پژوهش‌های آینده ارائه می‌دهد که می‌تواند در برنامه‌ریزی‌های ملی و منطقه‌ای به‌منظور کاهش فشارهای محیطی و بهبود پایداری محیط­ زیستی به کار گرفته شود.

کلیدواژه‌ها

آسیب‌ پذیری محیط‌ زیستی؛ موتور گوگل‌ارث انجین (GEE)؛ خودهمبستگی مکانی؛ راهبردهای پایداری؛ تفاوت‌های منطقه‌ای؛ ظرفیت سازگاری

مراجع

Abbasi Shavazi, M. J., & Sadeghi, H. A. (2022). The impact of population dynamics on environmental hazards and issues: A scoping review. Environmental Management Hazards, 9(4), 325-339. [In Persian] http://dx.doi.org/10.22059/jhsci.2023.354442.763

Adger, W. N. (2000). Social and ecological resilience: are they related? Progress in Human Geography, 24(3), 347-364. https://doi.org/10.1191/030913200701540465

Adger, W. N. (2006). Vulnerability. Global Environmental Change, 16(3), 268-281. https://doi.org/10.1016/j.gloenvcha.2006.02.006

Ahmadi, M., & Darvish, D. (2022). Investigation of changes in air pollutants in major metropolises of Iran using the optical depth of satellite images. Journal of Natural Environment, 75(1), 165-176. [In Persian] https://doi.org/10.22059/jne.2022.338515.2387 

Alwang, J., Siegel, P. B. & Jorgensen, S. L. (2001). Vulnerability: a view from different disciplines. Social Protection Discussion Papers Series, The World Bank, Washington DC.

Ashouri, H., Hsu, K. L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., … & Prat, O. P. (2015). PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society, 96(1), 69-83. https://doi.org/10.1175/BAMS-D-13-00068.1

Azmi, A., & Motiee Langroudi, H. (2011). Review on Rural Environmental Problems in Iran and Solutions in Resolving These Problems. Journal of Housing and Rural Environment, 30(133), 101-115. [In Persian] http://jhre.ir/article-1-20-fa.html  

Bardsley, D. K., & Wiseman, N. D. (2012). Climate change vulnerability and social development for remote indigenous communities of South Australia. Global Environmental Change, 22(3), 713-723. https://doi.org/10.1016/j.gloenvcha.2012.04.003

Bohle, H. G. (2001). Vulnerability and criticality: perspective from social geography. International Human Dimensions Programme on Global Environmental Change. Journal of Environmental Protection, 2(6), 3–5.

Carroll, M. C., Reid, N., & Smith, B. W. (2008). Location quotients versus spatial autocorrelation in identifying potential cluster regions. The Annals of Regional Science, 42(2), 449-463. https://doi.org/10.1007/s00168-007-0163-1

Chambers, R. (1989). Vulnerability, Coping and Policy. IDS Bulletin, 20(2), 1-7.

Chen, Z., Wang, L., Wei, A., Gao, J., Lu, Y., & Zhou, J. (2019). Land-use change from arable lands to orchards reduced soil erosion and increased nutrient loss in a small catchment. Science of the Total Environment, 648, 1097-1104. https://doi.org/10.1016/j.scitotenv.2018.08.141

Chudnovsky, A. A. (2021). Monitoring Air Pollution in the Urban Environment by Remote Sensing. Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment. https://doi.org/10.1002/9781119625865.ch18

Cunningham, A. B., Sharp, R. R., Hiebert, R., & James, G. (2003). Subsurface biofilm barriers for the containment and remediation of contaminated groundwater. Bioremediation Journal, 7(3-4), 151-164. https://doi.org/10.1080/713607982

Cutter, S. L. (1996). Vulnerability to environmental hazards. Progress in Human Geography, 20(4): 529-539. https://doi.org/10.1177/030913259602000407

De Jong, R., Verbesselt, J., Schaepman, M. E., & De Bruin, S. (2012). Trend changes in global greening and browning: contribution of short‐term trends to longer‐term change. Global Change Biology, 18(2), 642-655. https://doi.org/10.1111/j.1365-2486.2011.02578.x

Diwediga, B., Le, Q. B., Agodzo, S. K., Tamene, L. D., & Wala, K. (2018). Modelling soil erosion response to sustainable landscape management scenarios in the Mo River Basin (Togo, West Africa). Science of the Total Environment, 625, 1309-1320. https://doi.org/10.1016/j.scitotenv.2017.12.228

Eskandari, S., Ahmadloo, F., Pourghasemi, H. R., Ahangaran, Y., & Rezapour, Z. (2023). Temporal and Spatial Analysis of the Relationship Between Climate Parameter Changes and Fire in the Forests and Rangelands in the Province of Gilan. Iranian Journal of Forest and Range Protection Research, 21(1), 164-186. [In Persian]  https://dorl.net/dor/20.1001.1.17350859.1402.21.1.10.1

Famiglietti, J. S., Lo, M., Ho, S. L., Bethune, J., Anderson, K. J., Syed, T. H., & Rodell, M. (2011). Satellites measure recent rates of groundwater depletion in California's Central Valley. Geophysical Research Letters, 38(3). https://doi.org/10.1029/2010GL046442

Farokhnia, A., & Morid, S. (2014). Assessment of GRACE and GLDAS capabilities for estimation of water balance in large scale areas, a case study of Urmia Lake Watershed. Iran-Water Resources Research, 10(1), 51-62. [In Persian] https://www.iwrr.ir/article_13418.html?lang=en

Feyisa, G. L., Meilby, H., Fensholt, R., & Proud, S. R. (2014). Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sensing of Environment, 140, 23-35. https://doi.org/10.1016/j.rse.2013.08.029

Forootan, E., Rietbroek, R., Kusche, J., Sharifi, M. A., Awange, J. L., Schmidt, M., ... & Famiglietti, J. (2014). Separation of large scale water storage patterns over Iran using GRACE, altimetry and hydrological data. Remote Sensing of Environment, 140, 580-595. https://doi.org/10.1016/j.rse.2013.09.025

Füssel, H. M. (2007). Vulnerability: A generally applicable conceptual framework for climate change research. Global Environmental Change, 17(2), 155-167. https://doi.org/10.1016/j.gloenvcha.2006.05.002

Gallopín, G. C. (2006). Linkages between vulnerability, resilience and adaptive capacity. Global Environmental Change, 16(3), 293-303. https://doi.org/10.1016/j.gloenvcha.2006.02.004

Getis, A. & Ord, J. K. (1996). Local spatial statistics: an overview. In P. Longley & M. Batty (eds) Spatial analysis: Modelling in a GIS Environment. Cambridge: Geoinformation International.

Ghajarnia, N., Liaghat, A., & Arasteh, P. D. (2015). Comparison and evaluation of high resolution precipitation estimation products in Urmia Basin-Iran. Atmospheric Research, 158, 50-65. https://doi.org/10.1016/j.atmosres.2015.02.010

Ghannadi, M. A., Shahri, M., & Moradi, A. (2022). Air pollution monitoring using Sentinel-5 (Case study: big industrial cities of Iran). Environmental Sciences, 20(2), 81-98. [In Persian] https://doi.org/10.52547/envs.2022.1026

Guzmán, J. M., & de México, C. (2013). The demography of adaptation to climate change. G. Martine, & D. Schensul (Eds.). New York, London and Mexico City: UNFPA, IIED, and El Colegio de México. https://www.iied.org/g03554

Han, L., Zhou, W., Li, W., Meshesha, D. T., Li, L., & Zheng, M. (2015). Meteorological and urban landscape factors on severe air pollution in Beijing. Journal of the Air & Waste Management Association, 65(7), 782-787. https://doi.org/10.1080/10962247.2015.1007220

Hinman, S. E. (2017). Comparing spatial distributions of infant mortality over time: Investigating the urban environment of Baltimore, Maryland in 1880 and 1920. Applied Geography, 86, 1-7. https://doi.org/10.1016/j.apgeog.2017.06.015

IPCC. (2013). Managing the risks of extreme events and disasters to advance climate change adaptation. In C. B. Field, V. M. Barros, T. F. Stocker, D. Qin, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, ..., & P. M. Midgley (Eds.), A special report of working groups I and II of the intergovernmental panel on climate change. Cambridge: University Press Cambridge. http://dx.doi.org/10.13140/2.1.3117.9529

Issazadeh, V., & Argany, M. (2021). Changes in Water Surface of Aquifers Using GRACE Satellite Data in the Google Earth Engine: A Study of the Urmia Lake Watershed From 2002 to 2017. Town and Country Planning, 13(1), 193-214. [In Persian] https://doi.org/10.22059/jtcp.2020.304748.670127

Jiao, J. J., Zhang, X., & Wang, X. (2015). Satellite-based estimates of groundwater depletion in the Badain Jaran Desert, China. Scientific Reports, 5(1), 8960. https://doi.org/10.1038/srep08960

Jones, R. N., & Preston, B. L. (2011). Adaptation and risk management. Wiley Interdisciplinary Reviews: Climate Change, 2(2), 296-308. https://doi.org/10.1002/wcc.97

Karimian, H., Li, Q., Li, C., Jin, L., Fan, J., & Li, Y. (2016). An improved method for monitoring fine particulate matter mass concentrations via satellite remote sensing. Aerosol and Air Quality Research, 16(4), 1081-1092. https://doi.org/10.4209/aaqr.2015.06.0424

Kirschbaum, D. B., Huffman, G. J., Adler, R. F., Braun, S., Garrett, K., Jones, E., ... & Zaitchik, B. F. (2017). NASA’s remotely sensed precipitation: A reservoir for applications users. Bulletin of the American Meteorological Society, 98(6), 1169-1184. https://doi.org/10.1175/BAMS-D-15-00296.1

Kloog, I., Sorek-Hamer, M., Lyapustin, A., Coull, B., Wang, Y., Just, A. C., ... & Broday, D. M. (2015). Estimating daily PM2. 5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data. Atmospheric Environment, 122, 409-416. https://doi.org/10.1016/j.atmosenv.2015.10.004

Lafortezza, R., Carrus, G., Sanesi, G., & Davies, C. (2009). Benefits and well-being perceived by people visiting green spaces in periods of heat stress. Urban Forestry & Urban Greening, 8(2), 97-108. https://doi.org/10.1016/j.ufug.2009.02.003

Lee, M., & Diop, S. (2009). Millennium ecosystem assessment. An Assessment of Assessments: Findings of the Group of Experts Pursuant to UNGA Resolution 60/30, 1, 361.

Lee, S., Chu, M. L., Guzman, J. A., & Botero-Acosta, A. (2021). A comprehensive modeling framework to evaluate soil erosion by water and tillage. Journal of Environmental Management, 279, 111631. https://doi.org/10.1016/j.jenvman.2020.111631

McCarthy, J. J. (2001). Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change (Vol. 2). Cambridge University Press.

Mohammadi, S., Karimzadeh, H., Pourmanafi, S., & Soltani, S. (2018). Spatial and Temporal Evaluation of Soil Erosion using RUSLE model Landsat satellite image time series (Case Study: Menderjan, Isfahan). Journal of Range and Watershed Managment, 71(3), 759-774. [In Persian] https://doi.org/10.22059/jrwm.2018.221162.1073

Moshayedi, Z., & Jahangir, M. H. (2021). Qualitative evaluation of surface water resources using satellite images in Seymareh dam reservoir. Iranian journal of Ecohydrology, 8(4), 925-939. [In Persian] https://doi.org/10.22059/ije.2021.328294.1530

Najafi, Z., Darvishsefat, A. A., Fatehi, P., & Attarod, P. (2020). Time series analysis of vegetation dynamic trend using Landsat data in Tehran megacity. Iranian Journal of Forest, 12(2), 257-270. [In Persian] http://www.ijf-isaforestry.ir/article_114056.html

Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Arsenault, K. R., Li, B., & Getirana, A. (2019). Assimilating GRACE into a land surface model in the presence of an irrigation‐induced groundwater trend. Water Resources Research, 55(12), 11274-11294. https://doi.org/10.1029/2019WR025363

Paul, C., Techen, A. K., Robinson, J. S., & Helming, K. (2019). Rebound effects in agricultural land and soil management: Review and analytical framework. Journal of Cleaner Production, 227, 1054-1067. https://doi.org/10.1016/j.jclepro.2019.04.115

Proag, V. (2014) The concept of vulnerability and resilience. Procedia Economics and Finance, 18, 369-376. https://doi.org/10.1016/S2212-5671(14)00952-6

Raispour, K. (2021). Evaluation of Spatiotemporal Column Particulate Matter Concentration (PM2.5) Due to Dust Events in Iran Using Data from NASAN / MERRA-2 Reanalysis Model. Journal of the Earth and Space Physics, 47(2), 333-354. [In Persian] https://doi.org/10.22059/jesphys.2021.316499.1007273

Ramezani Khojeen, A., Kheirkhah Zarkesh, M. M., & Daneshkar Arasteh, P. (2016). Calculating and Calibrating Land Surface Temperature Using Landsat8 Thermal bands. Iranian Journal of Remote Sensing & GIS, 7(3), 49-64. [In Persian] https://gisj.sbu.ac.ir/article_95869.html

Rannow, S., & Neubert, M. (2014). Managing protected areas in central and eastern Europe under climate change. Springer Nature. https://doi.org/10.1007/978-94-007-7960-0

Reed, M. S. (2008). Stakeholder participation for environmental management: a literature review. Biological Conservation, 141(10), 2417-2431. https://doi.org/10.1016/j.biocon.2008.07.014

Rockström, J., Steffen, W., Noone, K., Persson, Å., Chapin, F. S., Lambin, E. F., ... & Foley, J. A. (2009). A safe operating space for humanity. Nature, 461(7263), 472-475. https://doi.org/10.1038/461472a

Rozenstein, O., Qin, Z., Derimian, Y., & Karnieli, A. (2014). Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors, 14(4), 5768-5780. https://doi.org/10.3390/s140405768

sabziparvar, A. A., & Nazemosadat, M. J. (2016). Validation of Land surface Temperature (LST) from Landsat-5 and MODIS Images (Case study: Wheat fields of Marvdasht Plain). Journal of Water and Soil Conservation, 23(4), 25-43. [In Persian] https://doi.org/10.22069/jwfst.2016.8864.2260

Sadeghi, H. A. (2023). Explanation of the spatial pattern of environmental degradation in Iran with emphasis on demographic and economic determinants. Ph.D. thesis, University of Tehran. [In Persian]

Sadeghi, H. A., Azizi, A., & Sadeghi, R. (2022). The Impact of Gender Gaps on the Environmental Performance in Selected Countries. Woman in Development & Politics, 20(3), 389-413. [In Persian] .https://doi.org/10.22059/jwdp.2022.339832.1008173

Sadeghi, H., Mohamadi Masiri, A., & mohammadi, S. (2022). Environmental Governance and Government Efficiency in Iran. State Studies of Contemporary Iran, 8(2), 31-57. [In Persian] https://dorl.net/dor/20.1001.1.27831914.1401.8.2.2.7

Saxena, P., & Naik, V. (2019). Air pollution: sources, impacts and controls. CAB International. https://doi.org/10.1079/9781786393890.0000

Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., ... & Wunch, D. (2019). A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor. Atmospheric Measurement Techniques, 12(12), 6771-6802. https://doi.org/10.5194/amt-12-6771-2019

Segnon, A. C., Totin, E., Zougmoré, R. B., Lokossou, J. C., Thompson-Hall, M., Ofori, B. O., ... & Gordon, C. (2021). Differential household vulnerability to climatic and non-climatic stressors in semi-arid areas of Mali, West Africa. Climate and Development, 13(8), 697-712. https://doi.org/10.1080/17565529.2020.1855097

Shayesteh, K., & Gharibi, S. (2022). Application of GEE in Dust Actual Sources Detection using Sentinel-5 and Modis. Journal of Natural Environmental Hazards, 11(34), 1-16. [In Persian] https://doi.org/10.22111/jneh.2022.38729.1813

Sherbinin, A. D., Carr, D., Cassels, S., & Jiang, L. (2007). Population and environment. Annual Review Environment and Resources, 32(1), 345-373. https://doi.org/10.1146/annurev.energy.32.041306.100243

Solomon, S. (2007). Climate change 2007-the physical science basis: Working group I contribution to the fourth assessment report of the IPCC (Vol. 4). Cambridge university press.

Tang, G., Clark, M. P., Papalexiou, S. M., Ma, Z., & Hong, Y. (2020). Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets. Remote sensing of environment,  240, 111697. https://doi.org/10.1016/j.rse.2020.111697

Teng, H., Rossel, R. A. V., Shi, Z., Behrens, T., Chappell, A., & Bui, E. (2016). Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia. Environmental Modelling & Software, 77, 156-167. https://doi.org/10.1016/j.envsoft.2015.11.024

Thomas, J., Joseph, S., & Thrivikramji, K. P. (2018). Assessment of soil erosion in a tropical mountain river basin of the southern Western Ghats, India using RUSLE and GIS. Geoscience Frontiers, 9(3), 893-906. https://doi.org/10.1016/j.gsf.2017.05.011

Torabi, F., Saravani, K., Sadeghi, H. A., & Jahanbazian, S. (2024). A comparative study of household vulnerability: A scoping review of the areas and measurement methods. refahj. 24(94), 2. [In Persian] https://doi.org/10.32598/refahj.24.94.4424.1

Turner, B. S. (2015). Vulnerability and human rights. University Park, USA: Penn State University Press. https://doi.org/10.1515/9780271030449

Vanacker, V., Ameijeiras-Mariño, Y., Schoonejans, J., Cornélis, J. T., Minella, J. P., Lamouline, F., ... & Opfergelt, S. (2019). Land use impacts on soil erosion and rejuvenation in Southern Brazil. Catena, 178, 256-266. https://doi.org/10.1016/j.catena.2019.03.024

Vogel, C., Susanne, C. M., Roger, E. K., & Geoffrey, D. D. (2012). Linking vulnerability, adaptation, and resilience science to practice: pathways, players and partnerships1. In Integrating science and policy. London: Routledge.

Weng, Q., Fu, P., & Gao, F. (2014). Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data. Remote Sensing of Environment, 145, 55-67. https://doi.org/10.1016/j.rse.2014.02.003

Yoshida, Y., Ota, Y., Eguchi, N., Kikuchi, N., Nobuta, K., Tran, H., ... & Yokota, T. (2011). Retrieval algorithm for CO 2 and CH 4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite. Atmospheric Measurement Techniques, 4(4), 717-734. https://doi.org/10.5194/amt-4-717-2011

Yuan, F., Wang, B., Shi, C., Cui, W., Zhao, C., Liu, Y., ... & Yang, X. (2018). Evaluation of hydrological utility of IMERG Final run V05 and TMPA 3B42V7 satellite precipitation products in the Yellow River source region, China. Journal of Hydrology, 567, 696-711. https://doi.org/10.1016/j.jhydrol.2018.06.045

Zabihi, M., Sadeghi, S. H., & Vafakhah, M. (2015). Spatial analysis of rainfall erosivity index patterns at different time scales ‎in Iran. Watershed Engineering and Management, 7(4), 442-457. [In Persian] https://doi.org/10.22092/ijwmse.2015.103089