Early cotton yield assessment by the use of the NOAA/AVHRR derived Vegetation Condition Index (VCI) in Greece

Satellite data can significantly contribute to agricultural monitoring. The reflected radiation, as recorded by satellite sensors, provides an indication of the type, density and condition of canopy. A widely used index for vegetation monitoring is the Normalized Difference Vegetation Index (NDVI) derived from the National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data provided in high temporal resolution. An extension of the NDVI is the Vegetation Condition Index (VCI). VCI is a tool for monitoring agrometeorological conditions, providing a quantitative estimation of weather impact to vegetation. The primary objective of this paper is the quantitative assessment of the cotton yield before the end of the growing season by examining the weather effects as they are depicted by the VCI. The study area comprises several cotton producing areas in Greece. Ten-day NDVI maximum value composites (MVC) are initially utilized for the period 1982-1999. The correlation between VCI images as extracted from NDVI and the 10-day intervals during the growing season is examined to identify the critical periods associated mostly with the yield. Empirical relationships between VCI and yield are developed. The models are tested on an independent dataset. The results show that an early estimation of the cotton yield trend is feasible by the use of the VCI