In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
199 
REMOTE SENSING FOR DROUGHT ASSESSMENT IN ARID REGIONS 
(A CASE STUDY OF CENTRAL PART OF IRAN, ” SHIRKOOH-YAZD") 
M. Ebrahimi a , A. A. Matkan a , R. Darvishzadeh a 
a RS & GIS Department, Faculty of Earth Sciences, Shahid Beheshti University (SBU), Tehran, Iran- 
(mohsen_ebrahimi@hotmail.com; a-matkan@sbu.ac.ir; r_darvish@sbu.ac.ir) 
Commission VII 
KEY WORDS: Vegetation, Application, Monitoring, Precipitation, LANDSAT, Spectral 
ABSTRACT: 
Rainfall, soil moisture, increasing temperature and changes in vegetation cover are the most important parameters effecting drought. 
Therefore, analysis of vegetation fraction and soil spectral signature, especially in red and infra red bands, are essential in drought 
estimation using remote sensing. In this study, Modified Perpendicular Drought Index (MPDI), which uses Vegetation Fraction (VF) 
and Perpendicular Drought Index (PDI) (computed based on the amount of rainfall and the soil moisture) has been used for 
monitoring and drought assessment in arid regions in central part of Iran during a time interval of three years (1999-2002). To do so, 
ETM+ images of LANDSAT 7 for the years 1999 and 2002 and the rainfall statistics of 23 years have been used. Analysis of 
vegetation cover using NDVI, RVI, SAVI, MSAVI, SAVI2 and PVI indices demonstrated that in arid regions changes in vegetation 
cover were best mapped using SAVI2 index. Also, in comparison with PDI and VSWI indices, drought severeness was best 
demonstrated by MPDI index. Further, the results were analyzed and evaluated using Run-test model and metrological data of the 
existing stations in the region. The results of the study indicated that in the year 2002 although in comparison to year 1999, the 
amount of rainfall has been increased, vegetation fraction has been decreased and consequently, drought has been increased in the 
rangelands of the study area. This is due to the existence of a severe drought and decrease in seeding of rangeland vegetations in 
previous years (2000, and 2001). 
1. INTRODUCTION 
Drought is a severe dilemma which influences different aspects 
of mankind’s life. It can cause many economic and eco- 
environmental problems especially in the agriculture sector 
(Goddard 2003). In the last three decades, remote sensing has 
provided a useful tool for drought monitoring and a variety of 
remotely sensed drought indices based on vegetation indices, 
land surface temperature (LST), albedo, etc have been 
developed. Several drought indices have been proposed based 
on normalised different vegetation index (NDVI, Rouse et al., 
1974) to monitor drought severity such as Anomaly Vegetation 
Index (AVI) and Vegetation Condition Index (VCI) (Chen 
1994; Kogan 1995a), Vegetation Condition Albedo Drought 
Index (VCADI) (Ghulam et ah, 2006), Temperature Drought 
Vegetation Index (TDVI) and Vegetation Temperature 
Condition index (VTCI) (Wang 2001; Sandholt 2002). 
Since there is a lag-time between the drought occurrence and 
the change of NDVI, the indices which are based on NDVI may 
not be appropriate for the real time drought monitoring. 
In addition, retrieval of the surface albedo and the LST contains 
uncertainties rooted in the atmospheric correction of satellite 
data, decomposition of mixed pixel information, BRDF 
modeling and the spectral remedy by a narrowband to 
broadband conversion (Zhao 2000; Pokrovsky 2002; Liang 
2003). As a consequence, the final error associated with the 
extraction and quantification of drought information would be 
magnified. 
In 2007 Ghulam et ah, presented the Modified Perpendicular 
Drought Index (MPDI) as a real time index for drought 
monitoring based on vegetation fraction (estimated using 
NDVI) and Perpendicular Drought Index (PDI). 
In arid areas, background soil has a considerable effect on the 
recorded reflectance by the sensor. Therefore, the indices, 
which consider background soil reflectance, may signify 
vegetation characteristics more accurately than the indices such 
as NDVI (Kallel 2007; Darvishzadeh 2008). In Iran, many 
studies have been conducted for monitoring drought disaster, in 
which, mostly AVHRR images and NDVI have been used 
(Serajian 2000; Baaqide 2007). As AVE1RR images have a 1 km 
resolution it can give a poor estimation for arid areas. 
The main objective of this study was to assess the drought 
severity in central arid areas of Iran by using MPDI as a real 
time index and ETM+ images which have a higher spatial 
resolution comparable to the AVHRR images. We examined the 
substitution of NDVI with another vegetation index (SAVI2, 
MSAVI, SAVI, PVI and RVI) for accurate estimation of the 
vegetation fraction which is used for MPDI calculation. Since 
in this study, the aim is to calculate the drought severity based 
on single image, three drought indices which needs only one 
image were selected (Vegetation Supply Water Index(VSWI), 
MPDI and PDI). 
2. MATERIALS 
2.1 Study Area 
Shirkooh basin is located in the central part of Iran and expands 
from longitude of 54° 3' to 54° 18' in East and latitude of 31° 
27' to 31° 43' in north. It covers a total area of 525 km 2 . The 
altitude varies between 1600 and 4055 meters. The basin is