نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری بیابان زدایی دانشگاه سمنان

2 هیأت علمی مؤسسه علمی کاربردی جهاد کشاورزی

3 استادیار دانشکده کویر شناسی دانشگاه سمنان

4 استادیار پژوهشکده حفاظت خاک و آبخیزداری سازمان تحقیقات،آموزش و ترویج کشاورزی

چکیده

خشکسالی پدیده ای است طبیعی که تقریباً در تمامی اقالیم جهان رخ میدهد. اثرات این پدیده خزنده و آرام در مناطق خشک و نیمه خشک به دلیل بارندگی سالانه کمتر شان، بیشتر است. در تحقیق حاضر برای پایش مکانی خشکسالی، از سریهای زمانی NDVIو LSTسنجنده MODISماهواره Terraدر ماههای فصول رشد (فروردین تا شهریور) سالهای 1379 الی 1393 در استان مرکزی استفاده شد. برای این منظور، شاخص VCIو TCIبترتیب بر اساس سریهای زمانی 15 ساله NDVIو LSTبه صورت ماهانه ایجاد گردید و در ادامه شاخص VHIبر اساس ترکیب دو شاخص مذکور استخراج شد. درنتیجه نقشههای درجات شدت خشکسالی بر اساس شاخص VHIدر پنج طبقه:1- خیلی شدید 2- شدید 3- متوسط 4- ملایم 5- بدون خشکسالی، استخراج گردیده و تغییرات این طبقات در سریهای زمانی VHIمورد بررسی قرار گرفت. بررسی سریهای زمانی حاصل از VCIو TCIنشان داد که ارتباط معنی داری میان تغییرات NDVIو LSTوجود دارد. مطابق نتایج نقشههای طبقه بندی شدت خشکسالی، شاخص VHI، سال 1379 و 1380 دارای بیشترین شدت و سالهای 1383 و 1386 دارای کمترین شدت خشکسالی بوده اند. همچنین ماه اردیبهشت دارای بیشترین شدت خشکسالی و شهریور دارای کمترین شدت خشکسالی بوده است. بیشترین درصد مساحت طبقات خشکسالی بترتیب مربوط به طبقه بدون خشکسالی (56%)، ملایم (19%)، متوسط (%15)، شدید (8%) و خیلی شدید (2%) بوده است. مقایسه نتایج حاصل از این تحقیق و گزارش سازمان هواشناسی، دقت بسیار خوب روش استفاده از شاخص سنجش از دوری VHI درپایش خشکسالی کشاورزی را نشان میدهد. نتیجه آنکه شاخصهای سنجش از دوری پایش خشکسالی (مانند VHI) میتوانند با برطرف کردن نقاط ضعف روشهای نقطهای، در پایش خشکسالی کشاورزی به تصمیم سازان و برنامه ریزان کمک شایانی نمایند.

کلیدواژه‌ها

عنوان مقاله [English]

Spatial Monitoring of Agricultural Drought through Time Series of NDVI and LST indices of MODIS data (Case study: Markazi Province)

نویسندگان [English]

  • Ali Akbar Damavandi 1 2
  • Mohammad Rahimi 3
  • Mohammad Reza Yazdani 3
  • Ali Akbar Noroozi 4

1 ITVHE Academic Member, Ph.D. Student in Combat Desertification, Semnan University, Iran

2 ITVHE Academic Member, Ph.D. Student in Combat Desertification, Semnan University, Iran

3 Assistant Prof. Semnan university, Semnan,Iran

4 Assistant Prof .soil conservation and Watershed management research Institute, Tehran.Iran

چکیده [English]

Abstract
Drought is a natural phenomenon that occurs in almost all climates of the world. The effects of this creeping and gentle phenomenon are higher in arid and semi-arid regions due to their less annual rainfall. In the present research, in order to monitor the location of drought, time series NDVI ((Normalized Difference Vegetation Index)) and LST (land surface temperature) of the Terra satellite’s MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used during the growing seasons (March, 21 to September, 21) of the years 2000 to 2014 in Markazi province. For this purpose, the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index) indices were created on a monthly basis based on the NDVI and LST 15-year time series, and the VHI (Vegetation Health Index) index was extracted based on the combination of the two indices. As a result, drought severity maps based on the VHI index were extracted in five categories: 1- Very severe 2- Severe 3- Moderate 4- Mild 5- no drought, and variations of these classes were investigated in VHI time series. A review of time series resulted from VCI and TCI showed that there was a meaningful relationship between NDVI and LST variations. According to the results of drought severity classification maps, VHI index had the highest drought intensity in the years of 2000 and 2001 and the years of 2004 and 2007 had the lowest drought severity. Also, the highest and the lowest drought severity were observed in May and September, respectively. The highest percentage of the areas of drought classes belonged to drought-free (56%), mild (19%), moderate (15%), severe (8%) and very severe (2%). Comparing the results of this research and the report of the Meteorological Organization shows the high precision of the method of using the VHI remote sensing index in agricultural drought monitoring. The result is that, remote sensing indicators of drought monitoring (such as VCI, TCI and VHI) can greatly help decision-makers and planners in monitoring agricultural drought  by eliminating the weaknesses of point-based approaches.

کلیدواژه‌ها [English]

  • Agricultural Drought
  • MODIS
  • VCI
  • TCI
  • VHI
1-  فاضل دهکردی، لیلا ؛(1392) ؛ هشدار خطر خشکسالی بمنظور مدیریت بهینه مراتع، پایان نامه دکتری، دانشکده منابع طبیعی دانشگاه تهران.
2- مرکز ملی خشکسالی و مدیریت بحران سازمان هواشناسی کشور. (1393)، تحلیل خشکسالی کشور طی 23 سال گذشته.
3- مهدوی، مریم؛(1393)؛ پیش بینی خشکسالی با استفاده از تصاویر ماهواره‌ای و زنجیره مارکوف، پایان نامه کارشناسی ارشد، پردیس ابوریحان دانشگاه تهران.
4-AghaKouchak, A. A. Farahmand,F. S. Melton, J. Teixeira, M. C.Anderson, B. D. Wardlow, and C. R. Hain., 2015, Remote sensing of drought: Progress,challenges and opportunities,Rev. Geophys. 53, 452–480, doi: 10.1002/2014RG000456.
5- Chen, W. -Y. Xiao, Q. -G., and Sheng, Y. -W.,1994, Application of the anomaly vegetation index to monitoring heavy drought in 1992 (In Chinese). China Remote Sensing of Environment, 9, 106-112.
6-Hayes, M.J., 2004, Drought indices, National Drought Mitigation Center, Nebraska, USA.http://drought.unl. edu/whatis/indices.htm.
7- Justice, C., J. Townshend, E. Vermote, E. Masuoka, R. Wolfe, N. Saleous, D. Roy, and J. Morisette.,2002, An overview of MODIS Land data processing and product status, Remote Sens. Environ., 83(1), 3–15, doi:10.1016/ S0034-4257(02)00084-6.
8-Khalil1 A.A.; M.M. Abdel-Wahab; M. K. Hassanein; B.Ouldbdey ; B. Katlan; and Y.H.,2013, Essa. Drought Monitoring over Egypt by using MODIS Land Surface Temperature and Normalized Difference Vegetation Index. Nature and Science,11(11):116-122]. (ISSN: 1545-0740). http://www.sciencepub.net.
9- Kogan FN., 1990, Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int. J. Remote Sens. 11(8): 1405-1419 CrossRef.
10- Kogan, F. N.,1995, Droughts of the late 1980s in the United States as derived from NOAA polar orbiting satellite data. Bulletin of the American Meteorological Society, 76: 655–668.
11-Liu, W. T., and Kogan, F. N., 1996, Monitoring regional drought using the Vegetation Condition Index. International Journal of Remote Sensing, 17, 2761–2782.
12-Lozano-Garcia, D. F., Fernandez, R. N., Gallo, K. P., and Johannsen, C. J.,1995, Monitoring the 1988 severe drought in Indiana, U.S.A. using AVHRR data. International Journal of Remote Sensing, 16, 1327-1340.
13-Menenti, M., Azzali, S. A., Verhoef, W., and van Swol, R.,1993, Mapping agro ecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images. Advances in Space Research, 13, 233–237.
14-Moran JF, Becana M, Iturbe-Ormaetxe I, Frechilla S, Klucas reductase and ascorbate peroxidase. In: Foyer CH, RV, Aparicio-Tejo P., 1994. Drought induces oxidative stress Mullineaux PM, eds. Causes of photooxidative stress and in pea plants. Planta 194, 346–352.
15-Parida, B.R., 2006, Analysing the effect of severity and duration of agricultural drought on crop performance using Terra/MODIS satellite data and meteorological data, Indian Institute of Remote Sensing.
16-Patel, P. K., Hemantaranjan, A., Sarma, B. K., and Singh, R.,2011,Growth and antioxidant system under drought stress in Chickpea (Cicer arietinum L.) as sustained by salicylic acid. J Stress Physiol Biochem 7: 130-144.
17- Prince, S.D., 1990, High temporal frequency remote sensing of primary production using NOAA AVHRR, Applications of Remote Sensing in Agriculture (M.D. Steven and J.A. Clark, editors), Butterworths, London, U.K.,4 :169-183.
18-Rahimzadeh Bajgiran,P., Darvishsefat,A.A., 2008, Using AVHRR-based vegetation indices for drought monitoring in the Northwest of Iran, Journal of Arid Environments; 72, 1086–1096.
19-Sharma , Aditi .,2006 , Spatial Data Mining for Drought Monitoring: An Approach Using temporal NDVI and Rainfall Relationship , ITC & IIRS , Thesis for the degree of Master of Science in Geo-information Science and Earth Observation in Hazard & Risk Analysis , no. 87.
20-Shareful Hassan,M., and Mahmud-ul-islam,S.,2013, Drought Vulnerability Assessment in the High Barind Tract of Bangladesh Using MODIS NDVI and Land Surface Temperature (LST) Imageries, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064
21-Singh, R. P., S. Roy, and F. Kogan.,2003, Vegetation and Temperature Condition Indices from NOAA AVHRR Data for Drought Monitoring over India. International Journal of Remote Sensing 24 (22): 4393–4402. doi:10.1 080/0143116031000084323.
22-Thenkabail, P. S., Gamage, M. S. D. N., Smakhtin, V. U., 2004, The use of remote sensing data for drought assessment and monitoring in Southwest Asia, Research Report 85, International water management Institute.
23-Wan, Z., Wang, P. and Li, X.,2004, Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA. Int.J. Remote Sens., 25(1): 61-72.
24-Wan, Z., 2008, New Refinements and Validation of the MODIS Land-Surface Temperature/Emissivity Products.Remote Sensing of Environment 112 (1): 59– 74. doi:10.1016/j.rse.2006.06.026.
25-Wang, P. -X., and Wei, Y. -M.,1998, Research, Demonstration and Extension of Sustainable Farming Systems for Rain fed Agriculture (UNDP-CPR/91/114 Project Final Report), (Xi’an, PR China: World Publishing Corporation).
26-Wang, J.; Price, K. P.; Rich, P. M., 2001, Spatial patterns of NDVI in response to precipitation and  temperature in the central Great Plains. International Journal of Remote Sensing 22: 3827–3844.
27-Wang L,Qu J. ,2009, Satellite remote sensing applications for surface soil moisture monitoring, Earth Sci. China, 3,2,pp 237–247.
28-Wilhite, D.A., and Glantz, M., 1985, Understanding the drought phenomenon: the role of definitions. Water Int. 10 (3): 111–120.doi:10.1080/02508068508686328.
29-Wilhite, D.A.,2005, Drought and Water Crises. Science, Technology, and Management Issues.Taylor & Francis Group.
30-Zhang X., Friedl M.A., Schaaf C.B., Strahler AH., Hodges J.C.F., Gao F., Reed B.C., Huete A., 2003, Monitoring vegetation phenology using MODIS. Remote sensing of environment, 84, pp. 471-475.