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Drought Impacts on vegetation cover an emphasis on Remote Sensing (Case Study: Salafchegan – Neizar Watershed) | ||
| تحقیقات مرتع و بیابان ایران | ||
| Article 16, Volume 26, Issue 3, September 2019, Pages 704-716 PDF (1.12 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/ijrdr.2019.120018 | ||
| Authors | ||
| Vahid Veisi1; Mansoureh Ghavam* 2; Omolbanin bazrafshan3 | ||
| 1Former M.Sc. Student in Combat Desertification, University of Kashan, Iran | ||
| 2Assistant Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Earth Sciences, University of Kashan, Iran. | ||
| 3Assistant Professor, Department of Natural Resources Engineering , Faculty of Agriculture and Natural Resources, University of Hormozgan, Iran | ||
| Abstract | ||
| Rangeland vegetation is one of the most important components of arid ecosystems and it is necessary to determine changes in rangeland vegetation under drought and wet years. The present study aimed to investigate the relationship between satellite indices and SPI index in Qom rangelands. For this purpose, the SPI index was calculated in moving averages of 1, 3, 5 and 7 years. In the next step, using Landsat images and after making the necessary adjustments to the images, the vegetation map was prepared using NDVI, MSAVI and EVI indices. Finally, correlation coefficients were used to investigate the relationship between satellite image indices and SPI index. The results showed a moderate and good correlation between MSAVI satellite indices and SPI index at peak vegetation growth months with a one month moving average of SPI index. The results of this study show that to estimate agricultural drought through remote sensing, the MSAVI index is a very suitable method and can be used for estimating drought in areas where meteorological stations are scattered (or nonexistent). Because the number of sampling points in satellite images is far greater than the number of meteorological stations. | ||
| Keywords | ||
| Drought monitoring; Satellite images; Vegetation index; Landsat images; Rangland | ||
| References | ||
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