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Monitoring of Agricultural Drought in the Middle Euphrates Area, IraqUsing Landsat Dataset | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 37, 7A, 2019, Pages 222-226 PDF (807.17 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.30684/etj.37.7A.1 | ||
| Authors | ||
| Imzahim A. Alwan1; Abdul Razzak T. Ziboon1; Alaa G. Khalaf2 | ||
| 1University of Technology, Civil Engineering Department - Iraq | ||
| 2Ministry of Science and Technology, Space and Communication Directorate - Iraq | ||
| Abstract | ||
| This study was conducted to monitor the agricultural drought in the Middle Euphrates area, Iraq during the period from 1988 to 2018. Multispectral Landsat TM, ETM+, and OLI images were used. The images dated 1988, 1993, 2000, 2005, 2010, and 2018, which obtained during growth months of plants (January, February, March, November, and December).A computerized drought monitoring was adopted using ERDAS Imagine 2015, ENVI 3.2, and ArcGIS 10.5 environments to process and analysis the data. The spectral indices, which used in this study were: The Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI). The change analysis presented in this study is based on the statistics extracted from the six resultant drought maps. The final results were illustrated that drought area in the region had a noticeable increase compared with no drought area. The results revealed that percentage of nodrought area ranged between (7%) and (17%) during the period from 1988 to 2018. The extremely and severely drought classes recorded high percentage followed by moderately and mild drought in the region. From this study can be concluded that there is a high rate of drought in the region, especially in its southern and western parts. | ||
| Keywords | ||
| Agricultural drought; Landsat; NDVI; VCI; Middle Euphrates | ||
| References | ||
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[1] W. Jiao, L. Zhang, Q. Chang, D. Fu, Y. Cen, and Q. Tong, “Evaluating an Enhanced Vegetation Condition Index (VCI) Based on VIUPD for Drought Monitoring in the Continental United States,” Rem. Sens., Vol. 8, No. 224, 2016, doi: 10.3390/rs8030224. [2] H. Murad and A.K.M. Saiful Islam, “Drought Assessment Using Remote Sensing and GIS in NorthWest Region of Bangladesh,” 3rd International Conference on Water & Flood Management (ICWFM), 2011. [3] H.T. Tran, J.B. Campbell, T.D. Tran, and H.T. Tran, “Monitoring drought vulnerability using multispectral indices observed from sequential remote sensing, Case Study: Tuy Phong, Binh Thuan, Vietnam,” GI Science & Rem. Sens., Volume 54, No. 2, pp.167–184, 2017, http://dx.doi.org/10.1080/15481603.2017.1287838. [4] T.L.T. Du, D.D. Bui, M.D. Nguyen, and H. Lee, “Satellite-Based Multi-Indices for Evaluation of Agricultural Droughts in a Highly Dynamic Tropical Catchment, Central Vietnam,” Water, Vol. 10, No. 659, 2018, doi: 10.3390/w10050659. [5] G.S. Canto, S. Horion, A. Singleton, H. Carrao, and J. Vogt, “Development of a Combined Drought Indicator to detect agricultural drought in Europe,” Nat. Hazards Earth Syst. Sci., Vol. 12, pp.3519–3531, 2012, doi: 10.5194/nhess-12-3519-2012. [6] R.I. Sholihah, B.H. Trisasongko, D. Shiddiq, L.O.S. Iman, S. Kusdaryanto, Manijo, and D.R. Panuju, “Identification of agricultural drought extent based on vegetation health indices of Landsat data: case of Subang and Karawang, Indonesia,” Procedia Env. Sci., Vol. 33, pp.14 – 20, 2016. [7] T. Borowik, N. Pettorelli, L. Sönnichsen, and B. Jędrzejewska, “Normalized difference vegetation index (NDVI) as a predictor of forage availability for ungulates in forest and field habitats,” Eur. J. Wildl. Res., Vol. 59, pp.675–682, 2013, doi: 10.1007/s10344-013-0720-0. [8] F. Jurecka, P. Hlavinka, V. Lukas, M. Trnka, and Z. Zalud, “Crop Yield Estimation in the Field Level Using Vegetation Indices, Mendelnet, pp.90-95, 2016. [9] R.P. Singh, N. Singh, S. Singh, and S. Mukherjee, “Normalized Difference Vegetation Index (NDVI) Based Classification to Assess the Change in Land Use/Land Cover (LULC) in Lower Assam, India,” Inter. J. of Adv. Rem. Sens. and GIS, Vol. 5, Issue 10, pp. 1963-1970, 2016, https://doi.org/10.23953/cloud.ijarsg.74. [10] S. V. Gaikwad and K.V. Kale, “Agricultural Drought Assessment of Post Monsoon Season of Vaijapur Taluka Using LandsatT8,” Inter. J. of Res. in Eng. and Tech.(IJRET), Vol. 4, Issue 4, 2015, http://www.ijret.org. [11] Y. Uttaruk and T. Laosuwan, “Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology,” J. of Ecol. Eng.,Vol. 18, Issue 6, pp. 115–121, 2017, doi: 10.12911/22998993/76326. [12] F. Ghaleb, M. Mario, and A.N. Sandra, “Regional Landsat-Based Drought Monitoring from 1982 to 2014,” Climate, Vol. 3, pp. 563-577, 2015, doi: 10.3390/cli3030563. | ||
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