Monitoring and
Assessment of Drought using Remote Sensing and association rules
Kumar Sanjeet, Reddy Madhusudhan M., Isukapatla Meena and Vijay Kumar A.
Disaster Advances; Vol. 16(10); 30-40;
doi: https://doi.org/10.25303/1610da030040; (2023)
Abstract
Drought is a natural threat that exists in all climatic zones around the globe.
There is a need to categorize drought events and the probability of occurrence for
better planning and management of relief and rehabilitation. In this study, drought
monitoring indices namely the Standard Precipitation Index (SPI) and Vegetation
Condition Index (VCI) were used to analyse the observed variability of monsoon droughts
over Andhra Pradesh State. Precipitation data between 1991-2019 was used to evaluate
the SPI and to evaluate the VCI from NDVI data collected from 2011 to 2019 using
multi-temporal Terra MODIS Vegetation Indices Product (MOD13Q1). In this analysis,
more often drought events occurred in 3 and 6 months SPI during monsoon season.
In this study, data mining techniques (such as the Association Rules) are used to
explain the association between VCI and SPI to predict the probability of occurrence
of drought. The association rules formed by the VCI and the 3-month SPI with 77
percentage of confidence and 1.11 of lift indicate the higher accuracy of the rules
and the effect on vegetation ford rainfall accumulation. This research incorporated
the various software and dataset levels used to predict the probable occurrence
and severity of drought using the current situation. The analysis revealed the advantages
of NDVI and rainfall for indices of spatial and multitemporal drought to identify
and forecast the characteristics of drought.
