An Investigation of Remote Sensing Vegetation Indices Ability in Drought Condition Prediction in Iran

Document Type : علمی - پژوهشی

Authors

1 M.Sc. of Geodesy and Geomatics Engineering Faculty, K.N.Toosi University of Technology

2 Professor, Dep. of Photogrammetry and Remote Sensing, College of Geodesy and Geomatics, K. N. Toosi University of Technology

3 Assistant prof., Dep. of Photogrammetry and Remote Sensing, College of Geodesy and Geomatics, K. N. Toosi University of Technology

4 M.Sc. of Remote Sensing and Member of Remote Sensing Centre, ISA, Tehran, Iran

Abstract

Iran as one of the countrieslocated in arid and semi-arid regions of the world, has been in drought danger. Shortage information about long-term weather conditions in many regions of the country, is one of the most important problems in drought monitoring. In this article, spectral vegetation indices (SVIs) have been employed in order to drought modeling and its forecast. To this end, SPI drought indicator (standardized precipitation index) used to represent period of drought and its intensity. Some broad band spectral vegetation indices including Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI) and Vegetation Condition Index (VCI) were extracted by using NOAA-AVHRR satellite imagery. These indices entered to SVM classifier model to gain the SPI index as its result. After comparing the results, TCI was diagnosed as the best index to predict drought condition via 3 months SPI (trimester SPI).

Keywords


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