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:: Volume 12, Issue 2 (1-2023) ::
JGST 2023, 12(2): 152-166 Back to browse issues page
Analysis of the effect of drought on the phenology parameters of vegetation indexes from the time series of MODIS sensor images (case study: Hamadan province)
Vida Sharifi , Salman Ahmadi * , Mehdi Gholamnia
Abstract:   (936 Views)
Drought is one of the consequences of climate change that slowly and over a relatively long period of time affects climate, environment, agriculture, vegetation, water resources and even economic and social sectors. The serious outcome of drought is the reduction of vegetation cover. In this research, using MODIS sensor satellite images of 2001-2020 (20-year period) and CHIRPS monthly rainfall data in Hamedan province, to analyze the effect of drought on phenology parameters (maximum NDVI value, range, base values) NDVI vegetation index has been discussed. For this purpose, the phenology parameters of the NDVI vegetation index were first extracted through the TIMESAT software, next the changes of these parameters were analyzed in relation to the elevation data and the land cover map of the region, and the correlation and RMSE error between the phenology parameters and the elevation data of the region were estimated. Moreover, through CHIRPS raster rainfall data, the annual SPI index was calculated. The results obtained from the analysis of these parameters in different elevations and uses have shown that in 2008, the maximum value of NDVI and the range of NDVI vegetation index have decreased 2008 compared to other years. On the other hand, in 2019, these parameters had higher values compared to other years. In addition, among other phenological parameters, the parameter of base values with a correlation of 0.925 has the highest correlation with the elevation data of the region, and its RMSE is 0.021. Furthermore, through monthly rainfall data for the years 2001 to 2020, it has been shown that in 2008, the average annual rainfall was lower than in other years, and the value of the annual SPI index was -1.79. Therefore, in 2008, a moderate drought occurred in the region, and on the other hand, according to the average rainfall in the years 2007, 2018 to 2020 and the value of the SPI index, during these years, a very severe drought occurred in the region.
 
Article number: 11
Keywords: Drought, Phenological parameters of vegetation index NDVI, TIMESAT software, MATLAB, DEM, Landcover, Standardized Precipitation Index (SPI)
Full-Text [PDF 1083 kb]   (747 Downloads)    
Type of Study: Research | Subject: Photo&RS
Received: 2022/08/16
References
1. Mohammadi Shaygani, A. and Asmaili, A. (2014), "Evaluation of agricultural drought using satellite images, combined indices and meteorological data (study area: Kermanshah province)". The first national conference on geospatial information technology engineering.
2. Nguyen, L. B., Li, Q. F., Ngoc, T. A., & Hiramatsu, K. (2015), "Adaptive Neuro-Fuzzy Inference System for Drought Forecasting in the Cai River Basin in Vietnam". Journal of the Faculty of Agriculture Kyushu University, 60(2), 405. [DOI:10.5109/1543403]
3. Mostafa Dasturani, Abbas Ali Vali, Sepehr, Adel, and Chooghi Bayram Kamkami. (2014)," Investigating the effect of drought on vegetation using MODIS sensor in Razavi Khorasan". Desert ecosystem engineering, 4.
4. Mirmousavi, Seyed Hossein and Karimi, Hamideh. (2012)," Studying the effect of drought on vegetation using MODIS sensor images, case: Kurdistan province".
5. Mbatha, N., & Xulu, S. (2018)," Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought". Climate, 6(4), 95. [DOI:10.3390/cli6040095]
6. Hayes, M.J. (2000)," Drought Indices, National Drought Mitigation Center", www.Drought.unl.edu
7. Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., Hodges, J. C., Gao, F., ... & Huete, A. (2003)," Monitoring vegetation phenology using MODIS". Remote sensing of environment, 84(3), 471-475. [DOI:10.1016/S0034-4257(02)00135-9]
8. Vicente-Serrano, S. M. (2007)," Evaluating the impact of drought using remote sensing in a Mediterranean, semi-arid region". Natural Hazards, 40(1), 173-208. [DOI:10.1007/s11069-006-0009-7]
9. Lesica, P. & Kittelson, P.M. (2010)," Precipitation and temperature are associated with advanced flowering phenology in semi-arid grassland". Journal of Arid Environments, 74:1013-1017. [DOI:10.1016/j.jaridenv.2010.02.002]
10. Butt, B., Turner, M.D., Singh, A. and Brottem, L. (2011)," Use of MODIS NDVI to evaluate changing latitudinal gradients of rangeland phenology in Sudano-Sahelian West Africa". [DOI:10.1016/j.rse.2011.08.001]
11. Ivits, E., M. Cherlet., G. Tóth., S. Sommer., W. Mehl., J. Vogt & F. Micale, (2012)," Combining satellite derived phenology with climate data z for climate change impact assessment". Global and Planetary Change, 88-89: 85-97. [DOI:10.1016/j.gloplacha.2012.03.010]
12. Senf, C., Pflugmacher, D., Van Der Linden, S., & Hostert, P. (2013)," Mapping rubber plantations and natural forests in Xishuangbanna (Southwest China) using multi-spectral phenological metrics from MODIS time series". Remote Sensing, 5(6), 2795-2812. [DOI:10.3390/rs5062795]
13. Jia, K., Liang, S., Wei, X., Yao, Y., Su, Y., Jiang, B., & Wang, X. (2014)," Land cover classification of Landsat data with phenological features extracted from time series MODIS NDVI data". Remote sensing, 6(11), 11518-11532. [DOI:10.3390/rs61111518]
14. Tang, H., Li, Z., Zhu, Z., Chen, B., Zhang, B. and Xin, X. (2015)," Variability and climate change trend in vegetation phenology of recent decades in the Greater Khingan Mountain area, Northeastern China". Remote sensing, 7(9), pp.11914-11932. [DOI:10.3390/rs70911914]
15. Yaghmaei, L., S. Soltani., R. Jafari., H. Bashari & H. Jahanbazi, (2017)," An investigation on impact of drought on rangeland and forest vegetation changes in Chaharmahal & Bakhtiari province using MODIS satellite data". Iranian Journal of Forest and Range Protection Research, 15(1): 91-108.
16. Karami, M., B. U. Hansen., A. Westergaard-Nielsen., J. Abermann., M. Lund., N.M. Schmidt & B. Elberling, (2017)," Vegetation phenology gradients along the west and east coasts of Greenland from 2001 to 2015". Ambio, 46(1): 94-105. [DOI:10.1007/s13280-016-0866-6]
17. Luo, Z., & Yu, S. (2017)," Spatiotemporal variability of land surface phenology in China from 2001-2014". Remote Sensing, 9(1), 65. [DOI:10.3390/rs9010065]
18. Malairi, F., D. Ashurlo, A. Shakiba, A. A. Matkan and H. agate (2017)," Investigating the effects of climate change on vegetation phenology using time series of AVHRR data". Journal of Ecological Agriculture 8(2): 117-98.
19. Zhang, Q., Kong, D., Shi, P., Singh, V. P., & Sun, P. (2018)," Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982-2013)". Agricultural and forest meteorology, 248, 408-417. [DOI:10.1016/j.agrformet.2017.10.026]
20. Mo, Y., Chen, S., Jin, J., Lu, X., & Jiang, H. (2019)," Temporal and spatial dynamics of phenology along the North-South Transect of Northeast Asia". International Journal of Remote Sensing, 1-19. [DOI:10.1080/01431161.2019.1608390]
21. Lebrini, Y., Boudhar, A., Hadria, R., Lionboui, H., Elmansouri, L., Arrach, R, & Benabdelouahab, T. (2019)," Identifying agricultural systems using SVM classification approach based on phenological metrics in a semi-arid region of Morocco". Earth Systems and Environment, 3(2), 277-288. [DOI:10.1007/s41748-019-00106-z]
22. Gholamnia, M., Khandan, R., Bonafoni, S., & Sadeghi, A. (2019)," Spatiotemporal Analysis of MODIS NDVI in the Semi-Arid Region of Kurdistan (Iran)". Remote Sensing, 11(14), 1723. [DOI:10.3390/rs11141723]
23. West, H., Quinn, N., & Horswell, M. (2019)," Remote sensing for drought monitoring & impact assessment: Progress, past challenges and future opportunities". Remote Sensing of Environment, 232, 111291. [DOI:10.1016/j.rse.2019.111291]
24. Zhang, X and Zhang, B.(2019)," The responses of natural vegetation dynamics to drought during the growing season [DOI:10.1016/j.jhydrol.2019.04.084]
25. across China". Journal of Hydrology,706-714.
26. Jönsson, P. and Eklundh, L. (2004)," TIMESAT - a program for analysing time-series of satellite sensor data, Computers and Geosciences", 30, 833-845. [DOI:10.1016/j.cageo.2004.05.006]
27. Haddadi, Farzaneh. Ashurlo, Davod. Shakiba, Alireza. Metkan, Ali Akbar. (2018)," The effect of climate change on the vegetation phenology of Urmia lake basin using time series of NOAA-AVHRR images", 6th regional climate change conference.
28. Jönsson, P. and Eklundh, L. (2004)," TIMESAT - a program for analysing time-series of satellite sensor data, Computers and Geosciences", 30, 833-845. [DOI:10.1016/j.cageo.2004.05.006]
29. Joyzadeh, S. Qamarzadeh, M. Brahimi, M. Shamsabadi, A. (2016)," ENVI practical training book (introductory and advanced)", Kian University Press.
30. Nasirizadeh, S. (2016)," Investigating the effect of drought on vegetation in the Middle Zagros region using MODIS satellite data", Master's Thesis, Faculty of Literature and Human Sciences.
31. Mckee,T.B.Doesken, N.J.and Kleist, J. (1993)," The relationship of drought frequency and duration to time scale". Proceedings of the Eight Conference on Applied Climatology American Meteorological Society,179-184.
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Sharifi V, Ahmadi S, Gholamnia M. Analysis of the effect of drought on the phenology parameters of vegetation indexes from the time series of MODIS sensor images (case study: Hamadan province). JGST 2023; 12 (2) : 11
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Volume 12, Issue 2 (1-2023) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology