This project was implemented on Zayandeh-Rud basin which is one of the most important and strategic regions of Iran. The main goal of the research was to monitor and evaluate the temporal land use/cover changes affected by drought episodes over a 10-year period (1992-2003). Primarily, raw weather data preparation activities were carried out to produce Standard Precipitation Index (SPI) spatial point thematic layer as a base map, then, satellite image pre-processing works applied on the remotely sensed data to generate the time series land use/cover maps. As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. The model works based on the seasonal values of Normalized-difference Vegetation Index (NDVI) in the study area. The algorithm was statistically compared with maximum likelihood supervised classification method. Results demonstrated an increase in overall accuracy from 74.34 to 90.07% and the Kappa index from 70.58 to 88.8%. Based on the statistical analysis results, drought had not statistically significant effect on the land use/cover changes. Therefore, there are more important factors other than natural weather drought in the study area and these could be summarized as a term of disorder on land management in the Zayandeh-Rud river basin. Results of the investigation provide a scientific tool enabling governmental land and water managers to monitor, make decision and manage the water crises due to drought upon the catchment.
A. Mokhtari, S.B. Mansor, A.R. Mahmud and Z.M. Helmi, 2011. Monitoring the Impacts of Drought on Land Use/Cover: A Developed Object-based Algorithm for NOAA AVHRR Time Series Data. Journal of Applied Sciences, 11: 3089-3103.