The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its impact can be considerably reduced if in-season spatio-temporal information related to crop status is available to the decision makers and they use it judiciously to manage agricultural resources. Satellite imagery is an effective tool that provides spatial information regularly in a timely manner. The Normalised Difference Vegetation Index (NDVI) and Normalised Difference Water Index (NDWI) developed using band combination of satellite imagery are used for monitoring the status of vegetation. Using MODIS 250 m,16 day maximum NDVI and NDWI composited product, VCI is used to assess crop growing situations. It focuses on assessment of vegetation growth by noting vegetation changes and comparing them with historical values. It is expected that the span should cover atleast one very good (conducive) and one very bad (adverse) agricultural year.

The Vegetation Condition Index (VCI) compares the current NDVI to the range of values observed in the same period in previous years. The VCI is expressed in % and gives an idea where the observed value is situated between the extreme values (minimum and maximum) in the previous years. Lower values indicate bad and higher values good vegetation conditions, respectively. This is a examples how to calculate VCI with Google Earth Engine (GEE)Javascript API. If you are already have an account in GEE, just copy and paste my code in the GEE API . In this example VCI is computed for June to Octobers months during 2000 to 2021 from modis NDVI in Google Earth Engine platform. More information about the data set is available here.

where VCIijk is the VCI value for the pixel i during week/month/DOY j for year k, Viijk is the weekly/monthly/DOYs VI value for pixel i in week/month/DOY j for year k whereby both the NDVI or EVI can utilized as VI, VIi, min and Vii,max are the multiyear minimum and maximum VI, respectively, for pixel i.