Assessing Sensitivity to Desertification Using the Fuzzy Overlay Method in Mashhad, Iran
محورهای موضوعی : Desertification
1 - Assistant Professor Faculty of Geography and Environmental Science Hakim Sabzevari University, Sabzevar, Iran
کلید واژه: Degradation, Salinity, Vegetation, Khorasan, Land-use,
چکیده مقاله :
In this research, we used six MODIS remote sensing products to evaluate the vulnerability to desertification in Mashhad, Iran in 2020. The Enhanced Vegetation Index (EVI), Vegetation Condition Index (VCI), Salinity Index (SI), Synthetized Drought Index (SDI), Temperature Condition Index (TCI), and precipitation were considered in May, 2020 when vegetation growth reaches its maximum size. Data layers were standardized using the Fuzzy Transform Function and scaled using the Analytical Hierarchy Process (AHP). Regarding TCI, VCI, and SDI, the greatest proportion of the area fell under the no drought to mild drought category indicating a lower risk of desertification. However, the Synthetized Desertification Index (SDI) was mainly distributed around the moderate and mild classes (~39%). The results of the EVI index also indicated that most of the area had a suitable vegetation density and low risk of desertification. As for the SI index, ~98% happened under the low salinity risk. Based on the results of the Analytical Hierarchy Process (AHP) method, precipitation (0.25), VCI (0.25), EVI (0.18), and SDI (0.13) obtained the greatest weights. The final vulnerability score ranged between 0.29 and 0.63. The results showed that the greatest parts of the area belong to the moderate risk (~68%) and high risk (30.1) classes of desertification. The highest values were obtained in the eastern and southeastern parts of the area with the lowest level of vegetation density, and high-temperature indices. Naturally, the elevations received the lowest values (~0.29) showing an increasing gradient towards the middle plain. The comparison between the results and the ground truth data indicated high compatibility (kappa value of >0.70). Mashhad City as the major population centre of the area is located in the low-risk category; therefore, desertification doesn’t seem to be threatening the city at the moment.
Abdollahi, A., Nezhad, M. P., Pradhan, B., 2019a. Determining the desertification risks of the Mashhad regions using integrated indices based on the AHP method. 2019 13th International Conference on Sensing Technology (ICST), 2-4 Dec. 2019. 1-6.
Abdollahi, A., Nezhad, M. P., Pradhan, B., 2019b. Investigation of the Vegetation Cover and the Vulnerability of the Mashhad Regions to Desertification by Using MODIS Image and EVI. 2019 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom), 22-24 Aug. 2019. 46-49.
Aixia, L., Changyao, W., Jing, W., Xiaomei, S., 2007. Method for remote sensing, monitoring of desertification based on MODIS and NOAA/AVHRR data. Trans. Chin. Soc. Agric. Eng, 23 145-150.
Akbari, M., Memarian, H., Neamatollahi, E., Jafari Shalamzari, M., Alizadeh Noughani, M., Zakeri, D., 2021. Prioritizing policies and strategies for desertification risk management using MCDM–DPSIR approach in northeastern Iran. Environ. Dev. Sustain., 23 (2), 2503-2523.
Akbari, M., Shalamzari, M. J., Memarian, H., Gholami, A., 2020. Monitoring desertification processes using ecological indicators and providing management programs in arid regions of Iran. Ecol. Indic., 111 106011.
Alamdarloo, E. H., Manesh, M. B., Khosravi, H., 2018. Probability assessment of vegetation vulnerability to drought based on remote sensing data. Environmental monitoring and assessment, 190 (12), 1-11.
Albalawi, E. K., Kumar, L., 2013. Using remote sensing technology to detect, model and map desertification: A review. J. Food Agric. Environ., 11 (2), 791-797.
Bezerra, F. G. S., Aguiar, A. P. D., Alvalá, R. C. S., Giarolla, A., Bezerra, K. R. A., Lima, P. V. P. S., do Nascimento, F. R., Arai, E., 2020. Analysis of areas undergoing desertification, using EVI2 multi-temporal data based on MODIS imagery as an indicator. Ecol. Indic., 117 106579.
Daliakopoulos, I., Tsanis, I., Koutroulis, A., Kourgialas, N., Varouchakis, A., Karatzas, G., Ritsema, C., 2016. The threat of soil salinity: A European scale review. Sci. Total Environ., 573 727-739.
Davari, S., Rashki, A., Akbari, M., Talebanfard, A., 2017. Assessing intensity and risk of desertification and management programs (Case study: Ghasemabad plain of Bajestan, Khorasan Razavi Province). Desert Manage., 5 (9), 91-106.
Didan, K., Munoz, A. B., Solano, R., Huete, A. 2015. MODIS vegetation index user’s guide (MOD13 series). University of Arizona: Vegetation Index and Phenology Lab.
Du, L., Tian, Q., Yu, T., Meng, Q., Jancso, T., Udvardy, P., Huang, Y., 2013. A comprehensive drought monitoring method integrating MODIS and TRMM data. Int J Appl Earth Obs Geoinf, 23 245-253.
Egidi, G., Salvati, L., 2020. Desertification risk, economic resilience and social issues: From theory to practice. Chinese Journal of Population, Resources and Environment, 18 (2), 155-163.
Elhadi, E. M. A., Dano, U. L., 2020. Desertification Assessment and Mapping in Northern Shaanxi Province: A GIS-based and Remote Sensing Approach. Disaster Adv., 13 (2), 1-10.
Fathi, A., Jafari, R., Soltani, S., 2015. Performance comparison of MEDALUD, MICD and FAO-UNEP desertification mapping models in the desertification hotspot of Jarghoyeh region, Isfahan province. J. Agr. Sci. Tech-Iran, 19 (71), 299-310.
Fathizad, H., Ardakani, M. A. H., Mehrjardi, R. T., Sodaiezadeh, H., 2018. Evaluating desertification using remote sensing technique and object-oriented classification algorithm in the Iranian central desert. J. Afr. Earth Sci. 145 115-130.
Feyzi Koushki, F., Akbari, M., Memarian, H., Azamirad, M., 2019. Identifying and ranking important factors of desertification in Khorasan Razavi Province using Delphi method. J. Geogr. Environ. Hazards, 8 (3), 225-205.
Gad, A., Lotfy, I., 2008. Use of remote sensing and GIS in mapping the environmental sensitivity areas for desertification of Egyptian territory. Solid Earth Discuss, 3(2), 41-85.
Görener, A., 2012. Comparing AHP and ANP: an application of strategic decisions making in a manufacturing company. Int. J. Bus. Soc. Sci. Res., 3 (11), 194-208.
Jafari, H., Akbari, M., Kashki, M., Badiee Nameghi, S., 2019. An efficiency comparison of the IMDPA and ESAs models on desertification risk management in arid regions of southern Khorasan Razavi, Iran. Arid Biome Sci. Resour. J., 9 (1), 39-54.
Jafari, M., Gholami, A., Khalighi Sigaroudi, S., Alizadeh Shabani, A., Arzani, H., 2018. Site selection for rainwater harvesting for wildlife using multi-criteria evaluation (MCE) technique and gis in the kavir national park, Iran. J. Rangel. Sci., 8 (1), 77-92.
Jafari Shalamzari, M., Zhang, W., Gholami, A., Zhang, Z., 2019. Runoff Harvesting Site Suitability Analysis for Wildlife in Sub-Desert Regions. Water, 11 (9), 1944.
Jain, A., Nandakumar, K., Ross, A., 2005. Score normalization in multimodal biometric systems. Pattern Recogn., 38 (12), 2270-2285.
Kacem, H. A., Fal, S., Karim, M., Alaoui, H. M., Rhinane, H., Maanan, M., 2021. Application of fuzzy analytical hierarchy process for assessment of desertification sensitive areas in North West of Morocco. Geocarto Int., 36 (5), 563-580.
Kjellen, B., 2003. The saga of the Convention to Combat Desertification: the Rio/Johannesburg process and the global responsibility for the drylands. Rev. Eur. Comp. & Int'l Envtl. L., 12 127.
Kogan, F. N., 1995. Application of vegetation index and brightness temperature for drought detection. Adv. Space Res., 15 (11), 91-100.
Kosmas, C., Kirkby, M. J., Geeson, N. (eds.) 1999. Medalus Project: Mediterranean Desertification and Land Use. Manual on key indicators of Desertification and Mapping Environmentally Sensitive Areas., Brussels, Belgium: Publication of European Union.
Kumar, B. P., Babu, K. R., Rajasekhar, M., Ramachandra, M., 2019. Assessment of land degradation and desertification due to migration of sand and sand dunes in Beluguppa Mandal of Anantapur district (AP, India), using remote sensing and GIS techniques. J. Indian Geophys. Union, 23 (2), 173-180.
Lin, M. L., Chen, C. W., Wang, Q. B., Cao, Y., Shih, J. Y., Lee, Y. T., Chen, C. Y., Wang, S., 2009. Fuzzy model‐based assessment and monitoring of desertification using MODIS satellite imagery. Eng. Comput., 26 (7), 745-760.
Liu, Y., Dang, C., Yue, H., Lyu, C., Dang, X., 2021. Enhanced drought detection and monitoring using sun-induced chlorophyll fluorescence over Hulun Buir Grassland, China. Sci. Total Environ., 770 145271.
Ma, H., Zhao, H., 1994. United Nations: Convention to combat desertification in those countries experiencing serious drought and/or desertification, particularly in Africa. Int. Legal Mater, 33 1328-1382.
Mehta, M., Saha, S., Agrawal, S., 2013. Evaluation of Indices and Parameters Obtained from Optical and Thermal Bands of Landsat 7 ETM+ for Mapping of Salt-Affected Soils and Water-Logged Areas. Asian J. Geoninf., 12 (4).
Mouat, D. A., Hutchinson, C. F. 2012. Desertification in Developed Countries: International Symposium and Workshop on Desertification in Developed Countries: Why Can’t We Control It?, Springer Science & Business Media.
Murray, N. J., Keith, D. A., Bland, L. M., Ferrari, R., Lyons, M. B., Lucas, R., Pettorelli, N., Nicholson, E., 2018. The role of satellite remote sensing in structured ecosystem risk assessments. Sci. Total Environ., 619 249-257.
Nikou, S., 2017. Impacts of land use changes on Technogenic desertification in Mashhad city. Desert Ecosys. Eng. J., 5 (13), 81-90.
Oldeman, L., Hakkeling, R., Sombroek, W., Batjes, N. 1991. Global assessment of human-induced soil degradation (GLASOD). World map of the status of human-induced soil degradation. Wageningen, Netherlands: Winand Staring Centre–ISSSFAO–ITC.
Pashaei, M., Rashki, A., Sepehr, A., 2017. An integrated desertification vulnerability index for Khorasan-Razavi, Iran. Nat. Resour. Conserv., 5 (3), 44-55.
Saaty, T. L., 2008. Decision making with the analytic hierarchy process. Int. J. Serv. Sci., 1 (1), 83-98.
Sepehr, A., Parvian, N., 2012. Desertification vulnerability mapping and prioritize confronting strategies in Khorasan Razavi province based on the Nartbh Pramsh algorithm. Earth Sci. Res. J., 8 58-71.
Sepehr, A., Zucca, C., Nowjavan, M. R., 2014. Desertification Inherent Status Using Factors Representing Ecological Resilience. Brit. J. Env. Clim. Change, 4 (3), 279.
Shihab, T. H., Al-hameedawi, A. N., 2020. Desertification Hazard Zonation in Central Iraq Using Multi-criteria Evaluation and GIS. J. Indian Soc. Remote. Sens., 48 (3), 397-409.
Shiravi, M., Sepehr, A., 2017. Fuzzy Based Detection of Desertification-Prone Areas: A Case Study in Khorasan-Razavi Province, Iran. Nat. Res. Conserv.
Sivakumar, M., 2007. Interactions between climate and desertification. Agric. For. Meteorol., 142 (2-4), 143-155.
Sörensson, A. A., Ruscica, R. C., 2018. Intercomparison and uncertainty assessment of nine evapotranspiration estimates over South America. Water Resour. Res., 54 (4), 2891-2908.
Tervonen, T., Sepehr, A., Kadziński, M., 2015. A multi-criteria inference approach for anti-desertification management. J. Environ. Manage., 162 9-19.
Vogt, J., Safriel, U., Von Maltitz, G., Sokona, Y., Zougmore, R., Bastin, G., Hill, J., 2011. Monitoring and assessment of land degradation and desertification: towards new conceptual and integrated approaches. Land Degrad. Dev, 22 (2), 150-165.
Wang, L., Seki, K., Miyazaki, T., Ishihama, Y., 2009. The causes of soil alkalinization in the Songnen Plain of Northeast China. Paddy Water Environ., 7 (3), 259-270.
Yari, R., Gholami, A., Jafari Shalamzari, M., Heshmati, G. A., 2018. Evaluation of Distance and Quadratic Indices for Determination of Plant Species Distribution Pattern in Khoosef Rangelands, Birjand, Iran. J. Rangel. Sci., 8 (4), 373-382.
Zadeh, L. A., 1996. Fuzzy sets. Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh. World Scientific.
