Many regions of the world are experiencing an increase in the frequency and intensity of droughts. The province of Fars, Iran, has faced particularly severe drought and ground water problems over the course of the last decade. However, previous research on the subject reveals a lack of useful information regarding droughts in this province. This paper presents a fast, efficient and reliable method that can be used to produce drought maps in which Advanced Very High Resolution Radiometer (AVHRR) images are processed and then compared with SPOT vegetation maps. Ten-day maximum Normalized Difference Vegetation Index (NDVI) maps were produced and vegetation drought indices such as the Vegetation Condition Index (VCI) were calculated. Furthermore, a Temperature Condition Index (TCI) was extracted from the thermal bands of AVHRR images in order to produce the Vegetation Health Index (VHI). Remotely sensed data was then compared with hydrological and meteorological data from 1998 to 2007. The Standardized Precipitation Index (SPI) was used to quantify the precipitation deficit while the Standard Water Level Index (SWI) was developed to assess the groundwater recharge deficit. Instead of correlation coefficients, spatial correlation through visual comparison was found to provide better and more meaningful pictures. The highest correlation values were obtained when VHI or Drought Severity Index (DSI) values were correlated with the current month’s SWI data. DSI maps showed strong vegetation conditions existing for the majority of the study period. For most counties in Fars, strong Pearson correlations observed between the DSI and the SWI of the same month reflect high rates of ground water consumption. The results of this study indicate that the proposed method is a potentially promising method for early drought awareness which can be used for drought risk management in semi-arid climates such as in Fars, Iran. This study also recommends that the Iranian government develop programs to help decrease the consumption of ground water resources in the province of Fars to ensure the long term sustainability of the watersheds in this province.
In the past few decades, both the frequency and intensity of droughts have increased in a number of regions in the world [1,2]. This recurring trend has negatively impacted many of these areas in terms of the large annual losses in vegetation it causes. Because of the serious social, economic, and environmental ramifications, drought monitoring has become a high priority for many countries, and especially developing ones. Since the late 1980s, satellites have been used for detecting and monitoring droughts as well as assessing their impact on agriculture [
One of the most efficient monitoring methods involves the use of Remote Sensing Technology. With this technique, sensors operating in several spectral bands are mounted on satellites in order to rapidly obtain and distribute drought information over large geographic areas. While the satellite is in orbit, it is able to explore the earth’s surface where in just a matter of a few days it is able to identify, monitor, and assess drought conditions. Using this technology, one can not only investigate the effect of droughts on vegetation cover but also their effects on ground water, surface temperature, and precipitation. In this way, a better understanding of temporal and spatial characteristics of the drought for a specific region can be achieved.
By monitoring droughts over a long period of time (i.e., 10 years or more) early drought warning systems can be developed. These early warning systems are important because they are being relied upon more and more to ensure global food security [
Singh et al. (2003) used NDVI, VCI and TCI to monitor droughts as well as estimate vegetation health. In their research, they used both vegetation and temperature condition indices to monitor droughts in India [
The aim of this research was to develop drought maps specifically for the southwest region of Iran, with a particular focus on the province of Fars, an area that has been suffering from disastrous hydrological drought since 2001. Despite the existence of previous research on the development of drought maps, a special method for extracting exact drought estimates for this particular Iranian region has yet to be developed. Previous research has typically relied on only one or two meteorological or hydrological indices. In our study, however, we incorporated remote-sensing data, related data from the NOAA-AVHRR sensor, and SPOT vegetation data (to verify extracted vegetation indices) to draw our conclusions.
In this study, analyses of monthly drought dynamics were calculated to identify drought configurations within hydrological, meteorological and vegetative domains. Making both quantitative and visual comparisons of drought dynamics in meteorological, hydrological, and vegetative domains in the province of Fars allowed us to generate more useful and reliable results. To verify the vegetation indices extracted from the NOAA-AVHRR images, SPOT-VEG images from the same time period (1998-2007) were used. The Standardized Water Level Index (SWI) and the Standard Precipitation Index (SPI) were used to monitor and analyze hydrological and meteorological drought, respectively. Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI) were used to assess vegetative drought. The development of VHI was done using VCI and TCI indices because they are more effective at monitoring vegetative drought than are other indices [6,10,11]. Given that the province of Fars is the most important agricultural region of Iran, the effects of its ground water consumption on NDVI were also investigated. The hydrological and meteorological stations of Fars are well distributed (geographically) throughout the province, and temporal analysis was carried out over a span of 10 years. This specific time frame was used so that the long-term effects of precipitation and changing ground water levels could be studied. Compared with traditional in-situ measurements, the results obtained from remote-sensing methods are capable of providing more reliable drought maps. Chapter 3 explains our implementation methodology while Chapter 4 provides a comprehensive presentation and analysis of our results. Finally, concluding remarks are given in Chapter 5.
Located in the southern part of the country, Fars is one of the 30 provinces that comprise present day Iran (
The image data taken by the Local Area Coverage Advanced Very High Resolution Radiometer (LAC AVHRR) aboard the National Oceanic and Atmospheric Administration (NOAA) 14-16-17 satellite were preprocessed using ENVI. For temporal analysis, a 10-year period was chosen in order to study the long-term effects of precipitation and groundwater levels on the vegetation coverage. This research was limited to ten years due to the inability to access any data records prior to 1998.
Initial examination of AVHRR data collected from the NOAA satellite database [
In order to study the vegetation cover in Fars, 10-day composite NDVI data (derived from the sensor VEGETATION on board the SPOT satellite platforms) was acquired from the “Vlaamse Instelling Voor Technologish Onderzoek” [
1 km2 and were derived from primary SPOT-VGT products; the composites were corrected for reflectance, scattering, water vapor, ozone, and other gas absorption using the procedures described by Achard et al. and Duchemin et al. [14,15].
The maximum value compositing (MVC) procedure as described by Holben (1986) was used to merge NDVI values over the course of ten days [
Typical NDVI-values range between 0.1 and 0.7 for vegetated areas, with a higher (composite) NDVI value equating to denser, greener vegetation. The temporal evolution of NDVI-values is considered to be an effective way to analyze the impact of 1) natural seasonal variations, 2) extreme climatic events, and 3) human activities on ecosystems [