Investigating the Indicators Resulting from Remote Sensing Technology in Drought Assessment using MODIS Images (Case Study: Qom, Isfahan, Chaharmahal and Bakhtiari, and Markazi Provinces)

جغرافیا و مخاطرات محیطی

Article 10, Volume 11, Issue 3 - Serial Number 43, November 2022, Pages 189-224   

Document Type: Research Article

DOI: 10.22067/geoeh.2021.72253.1102

Authors

Saleh Arekhi^{* 1}; Marzieh Barzegar Savasari²; Somia Emadaddian¹

¹Assistant Professor, Geography Department, Human Sciences College, Golestan University, Gorgan, Iran

²MSc Student, Human Sciences College, Golestan University, Gorgan, Iran

Abstract

Drought is a situation of lack of rainfall and rising temperatures that occurs in any geographical area and in any climate, even in humid areas. The frequency and severity of drought are higher in arid and semi-arid regions. Drought occurs without notice and has a wide range of impacts unlike other natural disasters. The damage caused by drought is intangible but very large and costly. Therefore, the basis of a regular program for better management according to past events requires drought monitoring. Meteorological drought indices are calculated directly from meteorological data such as rainfall. In the absence of such data, they will not be useful in monitoring drought. Therefore, remote sensing technique can be a useful tool in drought monitoring. In this study, the relationship between standardized precipitation index  (SPI index) and remote sensing indices of VCI, TCI and VHI in Isfahan, Chaharmahal and Bakhtiari, Markazi, and Qom provinces was investigated. Using satellite images of Modis Terra sensor and precipitation data of rain gauge and synoptic stations located in the studied area, the changes occurred over a period of 10 years was calculated. For this purpose, four months (April, May, June, and July) were selected as a sample by reviewing the data of existing stations and using the standardized precipitation index (SPI) model. In this study, due to time accuracy, high spectrum coverage, ease of access, no need for atmospheric correction and ground reference, images with code (MOD11A2 and MOD13A2) of Modis satellite sensor products related to the years 2011 to 2020 due to confidence of wet and drought phenomena was used and then SPI index was compared with VCI, TCI, and VHI indices in combination. The results of drought monitoring showed that during the ten-year period, there was severe drought in some years, and in the same year, less rainfall occurred. In 2020, for example, the drought was very severe, and in 2011 it was very wet. The results of the correlation between SPI index and remote sensing indices showed that SPI index has the highest correlation with VCI index at the level of 0.01. It was found that MODIS images and constructed indices have the necessary capability for drought monitoring. The results of this study can be a good option for decision makers to monitor, investigate and resolve drought conditions and double the need to define an index.

Keywords

Drought; SPI index; VCI index; TCI; VHI; Central Iran

References

امیدوار، کمال؛ ابراهیمی، رضا؛ راستی، فاطمه؛ 1393. ارزیابی برخی روش­های زمین­آمار در پهنه­بندی شدت خشکسالی؛ مطالعه موردی منطقه شمالغرب و مرکزی ایران. مهندسی آبیاری، 17 :30-43.

https://www.sid.ir/paper/247354/fa#downloadbottom

پرویز، لاله؛ خلقی، محمد­رضا؛ ولیزاده کامران، خلیل؛ 1388. پایش خشکسالی با استفاده از شاخص پوشش گیاهی و دمای سطح زمین حاصل ازتصاویر ماهواره‌ی Terra-MODIS، چهارمین کنفرانس سراسری آبخیزداری و مدیریت منابع آّب وخاک، آذر 1388، کرمان. 1073-1081.

پیش­نماز احمدی، مجید؛ هوشمند، علی؛  زمانی، فهیمه؛ 1396. پایش خشکسالی شمال­غرب کشور با استفاده از داده­های  MODIS و TRMM، بیست و چهارمین همایش ملی ژئوماتیک، اردیبهشت 1396.

https://www.sid.ir/paper/894192/fa

جهانبخش، سید؛ هادیانی، میر­امید؛ رضایی­بنفشه، مجید؛ دین­پژوه، یعقوب؛ 2010. مدل­سازی پارامترهای تغییر اقلیم در استان مازندران. مجموعه مقالات چهارمین کنگره بین المللی جغرافیدانان جهان اسلام (ICIWG) ، 13ص.

https://civilica.com/doc/82885

حمزه، سعید؛ فراهانی، زهرا؛ مهدوی، شهریار؛ چترآبگون، امید؛ غلام­نیا، مهدی؛ 1396. پایش زمانی و مکانی خشکسالی کشاورزی با استفاده از داده‌های سنجش‌ازدور، موردمطالعه: استان مرکزی ایران. نشریه تحلیل فضایی مخاطرات محیطی، سال چهارم، شماره 3. ص 70-53.

https://www.sid.ir/paper/264741/fa#downloadbottom

حجازی­زاده، زهرا؛ جوی­زاده، سعید؛ 1398. تحلیل آمار فضایی خشکسالی در ایران. نشریه تحقیقات کاربردی علوم جغرافیایی، دوره  19، شماره  53، از صفحه  251 تا صفحه 277.

https://www.sid.ir/paper/102201/fa#downloadbottom

صلاحی، برومند؛ خورشیددوست، علی­محمد؛  قویدل رحیمی، یوسف؛ 1386. ارتباط نوسان­های گردش جوی ـ اقیانوسی اطلس شمالی با خشکسالی­های آذربایجان شرقی. نشریه پژوهش­های جغرافیایی. شماره 60. صص 147-156.https://www.sid.ir/paper/5497/fa#downloadbottom

خدایی، مهسا؛ شـاد، روزبـه؛ مقصـودی­مهرانـی، یاسـر؛ قائمی، مرجان؛ 1395.  تعیین یک شاخص بهینـه چنـد سنسور سنجش‌ازدوری به‌منظور ارتقای فرایند پـایش زمان واقعی خشکسالی در مناطقی بـا پوشـش اراضـی ناهمگن. اکوهیدرولوژی، دوره سوم، شماره سوم، تهران.

https://ije.ut.ac.ir/article_60041_ab91f234cd0f3799738362c9e487963c.pdf

خوش‌اخلاق، فرامرز؛ رنجبر، فیروز؛ طولابی، سوسن؛ مقبل، معصومه؛ معصومپور­ سماکوش، جعفر؛ 1389. بررسی خشکسالی در سال آبی 1386-87 و اثرات آن بر منابع آب کشاورزی (نمونۀ موردی: شهرستان مرودشت)، مجلۀ جغرافیا، شمارۀ 24، صص 136-119.https://www.sid.ir/paper/5497/fa#downloadbottom

سلطانی، میلاد؛ سلطانی، عادل؛ کله­هوئی، مهین؛ سلیمانی، کریم؛ 1398. پایش خشکسالی منطقه­ای با استفاده از تصاویر لندست، منطقه موردمطالعه: شهرستان کرمانشاه، فصلنامه اطلاعات جغرافیایی (سپهر)،  دوره 28، شماره 109، ص 138-146.https://www.sid.ir/paper/253284/fa#downloadbottom

عزیزی، قاسم؛ سفرراد، طاهر؛ 1391. تحلیل ویژگی­های رودباد طی فازهایENSO ، مطالعه موردی؛ 1997، 2008 و 2010. نشریه پژوهش­های اقلیم شناسی، سال سوم، شماره 9، ص 82-70.

https://www.sid.ir/paper/403036/fa#downloadbottom

غفوریان، هادی؛ ثنائی­نژاد، سید­حسین؛ داوری، کامران؛ 1393. بررسی تعیین مناطق مناسب جهت پایش خشکسالی با استفاده از داده­های ماهواره TRMM (مطالعه موردی: استان خراسان رضوی (آب و خاک)، علوم و صنایع کشاورزی (3). 639-648.https://www.sid.ir/paper/141927/fa#downloadbottom

نوروزی، اصغر؛ محمدی، زهرا؛ 1395. برسی خشکسالی هیدرولوژیک و آثار آن بر کشاورزی منطقه لنجان. فصلنامه علمی-پژوهشی برنامه­ریزی فضایی (جغرافیا). سال ششم، شماره دوم (پیاپی 21)، 116-97.

 https://doi.org/10.22108/sppl.2016.21633

محمودزاده، عبدالحسین؛ ثقفیان، بهرام؛ مختاری، احمد؛ 1387. بررسی همبستگی شاخص خشکسالی SPI و شاخص NDVI منطقه فریدون شهر، سومین کنفرانس مدیریت منابع آب. دانشگاه تبریز. دانشکده مهندسی عمران. 8 صفحه.https://civilica.com/doc/50191/

 

Agnew, C.T., 2000. using the SPI to Identify Drought, Drought Network News, Vol. 12, No. 1, winter 1999-Spring 2000. https:// digitalcommons.unl.edu/ cgi/ viewcontent.cgi? article= 1000& context=droughtnetnews

Bayarjargal, Y., Karnieli, A., Bayasgalan, M., Khudulmur, S., Gandush, C., Tucker, C. J., 2006. A comparative study of NOAA–AVHRR derived drought indices using change vector analysis. Remote Sensing of Environment, 105(1), 9-22.‏ https:// www.sciencedirect.com/ science/ article/ abs/pii/S0034425706002185

Bonaccorso, B., Bordi, I., Cancelliere, A., Rossi, G., Sutera, A., 2003. Spatial variability of drought: an analysis of the SPI in Sicily. Water resources management, 17(4), 273-296.‏ https:// link.springer.com/ article/ 10.1023/A:1024716530289

Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., Gregoire, J.M., 2001. Detecting vegetation leaf water content using reflectance in the optical domain. Remote Sensing of Environment, 77, Pp. 22–33. https:// www.sciencedirect.com/ science/ article/ abs/ pii/S0034425701001912

Chen, Z., Grasby, S.E., Osadetz, K.G., 2004. Relation between climate variability and groundwater levels in the upper carbonate aquifer, southern Manitoba, Canada, Journal of Hydrology, No. 290, 43–62. https:// www.sciencedirect.com/ science/ article/ abs/ pii/ S0022169403004852

Elhag, K., Zhang, W., 2018. Monitoring and Assessment of Drought Focused on Its Impact on Sorghum Yield over Sudan by Using Meteorological Drought Indices for the Period 2001–2011, Remote Sensing, Vol 10 (8), 1231 p. https://www.mdpi.com/2072-4292/10/8/1231

Fiorillo, F., Guadagno, F.M., 2010. Karst spring discharges analysis in relation to drought periods, using the SPI. Water Resources Management, 24(9): 1867-1884. https://link.springer.com/ article/ 10.1007/ s11269-009-9528-9

Hodel, E., 2012. Analysing Land Cover Change in Mongolia Using Terra MODIS Satellite Data supervisor Hans Hurni, Masterarbeit der Philosophisch, Universität Bern.

https://www.scirp.org/journal/paperinformation.aspx?paperid=4981

Ji, L., Peters, A.J., 2003. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices, Remote Sensing of Environment, 87, 85-98pp. https:// www.sciencedirect.com/ science/ article/ abs/pii/S0034425703001743

Gu, Y., Brown, J., Verdin, J., Wardlow, B., 2007. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophysical Research Letters. 34. 551-560.https://www.sid.ir/FileServer/SF/7971392h01204

Karel, A.K., 1989. Response of Ootheca bennigseni (Coleoptera: Chrysomelidae) to extracts from neem. Journal of economic entomology, 82(6), 1799-1803.‏ https:// www. semanticscholar. org/ paper/ Response- of -Ootheca-bennigseni -(Coleoptera%3A-to-from- Karel/ 8bf42bb 7bfb36f3310beadd1a3cf06ae60f785f6

Kogan, F.N., 2000. Global drought detection and impact: Assessment from apace, In Wilhite Editor Drought a Global Assessment, 1: 197-206.https://web.iitd.ac.in/~sagnik/C2.pdf

Lein, J., 2003. Integrated Environmental Planning, Black well scinse Inc U.S.A. https:// www.amazon.com/ Integrated- Environmental- Planning- Landscape- Synthesis ebook/ dp/ B000VI62QM

Mckee, T.B., Doesken, N.J., Kleist, J., 1993. The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology. American Meteorological Society Boston, MA, Pp: 179-183. https:// www.droughtmanagement.info/ literature/ AMS_Relationship_Drought_Frequency_Duration_Time_Scales_1993.pdf

Owrangi, M.A., Adamowski, J.M., Rahnemaei, A., Mohammadzadeh, R., Sharifan, R.A., 2011. Drought monitoring methodology based on AVHRR images and SPOT vegetation maps. Journal of Water Resource and Protection, 3(5): 325-346.

Pei, F., Wu, C., Liu, X., Li, X., Yang, K., Zhou, Y., Xia, G., 2018. Monitoring the vegetation activity in China using vegetation health indices. Agricultural and forest meteorology, 248, 215-227. https://www.sciencedirect.com/science/article/abs/pii/S0168192317303210

Rostami, A., Bzane, M., Raini, M., 2016. Spatial and temporal monitoring of agricultural drought using Modis imagery and remote sensing technology. Journal of Soil and Water Science, 27: 213- 226 (in Persian). https://agry.um.ac.ir/ index.php/ article_ 37239. html?lang=en

Roswintiarti, O., Oarwati, S., Anggraini, N., 2010. Potential Drought Monitoring over Agriculture Area in Java Island, Indonesia, Indonesian National Institute of Aeronautics and Space (LAPAN), Progress Report of SAFE Prototype Year. http:// jurnal.lapan.go.id › article › download. PDF

Shahabfar, A., Ghulam, A., Eitzinger, J., 2012. Drought monitoring in Iran using the perpendicular drought indices. International Journal of Applied Earth Observation and Geoinformation, 18: 119-127. https:// www.sciencedirect.com/ science/ article/ abs/ pii/ S030324341200013X

Silva, V.P.R., 2003. On Climate Variability in Northeast Brazil, Journal of Arid Environment, 54 (2): 256-367. http:// text2fa.ir/ wp-content/ uploads/ Text2fa.ir- On- climate-variabilityin-Northeast-of-Brazil.pdf

Thenkabail, P.S., Gamage, M.S.D.N., Smakhtin, V.U., 2003. The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia. Research report 85. 1-34. https:// www.unisdr.org/ files/ 1871_VL102138.pdf

Tsakiris, G., Vangelis, H., 2004. Towards a drought watch system baesed on spatial SPI. Water resources management, 18(1), 1-12.‏ https:// link.springer.com/ article/ 10.1023/ B: WARM. 0000015410.47014.a4

Wu, H., Hayes, M.J., Weiss, A., Hu, Q., 2001. An evaluation of the Standardized Precipitation Index, the China‐Z Index and the statistical Z‐Score, International journal of climatology, Vol. 21, No. 6, pp. 745-758.https://rmets.onlinelibrary.wiley.com

Yıldırım, T., Aşık Ş., 2018. Index-based assessment of agricultural drought using remote sensing in the semi-arid region of Western Turkey. Journal of Agricultural Sciences, 24(4) : 510-516. https://dergipark.org.tr/tr/download/article-file/339519

Zambrano, F., Lillo-Saavedra, M., Verbist, K., Lagos, O., 2016. Sixteen years of agricultural drought assessment of the BioBío region in Chile using a 250 m resolution Vegetation Condition Index (VCI). Remote Sensing, 8(6): 530-549. https://www.mdpi.com/2072-4292/8/6/530