Comparison of NDVI Time Series between MISBAR and GEE Platforms: A Case Study of a High-Yield Wheat Field during the 2022/2023 Season

Abstract

Abstract— In this study, the most widely used vegetation index, the Normalized Difference Vegetation Index (NDVI), was used to extract NDVI time series data for a high-yield wheat field during the 2022/2023 season from two cloud computing platforms: MISBAR and Google Earth Engine (GEE), it was observed that although the MISBAR platform provides an option to filter satellite imagery based on a maximum cloud cover threshold, it calculates its indicator values without actually applying this condition. Therefore, temporal alignment was applied by selecting only the overlapping dates between the two platforms before performing the statistical analysis. Comparing the mean NDVI values from both platforms revealed that they are temporally and spatially consistent in tracking the growth stages of the wheat crop, with a correlation coefficient of 0.998 and a positive bias toward the GEE platform. A linear relationship was found between them, where the MISBAR platform tended to calculate lower NDVI values than the GEE platform, while both maintained a similar temporal trend throughout the crop growth stages.