![Sample our Geography journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5937/TOC-Subject-Sample-2021-Geography.jpg"})
Abstract
Time series of satellite imagery are commonly used to study and model phenology. To use these models, their results must be compared with time series of areal field data, and vegetation condition must be assessed relative to model predictions. Field data and Moderate Resolution Imaging Spectroradiometer (MODIS) data for corn fields in Illinois, USA, were collected throughout the growing season, including vegetation cover fraction (VCF) derived from kite aerial photography (KAP). The mean height of corn on the estimated start of spring (SOS) date was just over 2 cm and the mean VCF on SOS was nearly 10%, indicating that satellite models of phenology lag behind field-based measures of phenology like crop emergence. The relationships between MODIS Normalized Difference Vegetation Index (NDVI) and both KAP NDVI (coefficient of determination (R 2) = 0.918, p < 0.000) and KAP VCF (R 2 = 0.920, p < 0.000) were strong, highlighting the importance of areal field data in phenology studies.