Remote sensing indicators for crop growth monitoring at different scales

Crop growth monitoring is critical in yield estimation and prediction. In this paper, the authors investigated several indicators for crop growth monitoring by remote sensing at different scales. The experiments were conducted in a study area in Hebei province in North China Plain. The target crop in this research is winter wheat, which is one of the important grain crops in China. The study at canopy scale is based on field experiment with different fertilizer supply treatments to winter wheat to get different crop growth gradients. The canopy spectra and LAI data of different crop growth situation were collected and analyzed. The correlation coefficients between vegetation indices and LAI were calculated. The best growth monitoring indicators at canopy scale for each phenological stage were determined by the correlation coefficients. The best indicator in early elongation stage is SAVI (L=0.3). While in jointing stage, the best indicator is SAVI (L=0.2). In the heading and milk stages, the best indicator is NDVI. At the regional scales, the multi-spectral remote sensing data from HJ-IA satellite were used to study the crop growth monitoring indicators. The performances of the vegetation indices at different spatial scales for crop growth monitoring were studied in different phenological stages by comparing the correlation coefficients of vegetation indices and LAI data. The result shows that the vegetation indices which have a function to decrease soil-effect are suitable for the region in different crop coverage in early elongation stage and for the region in low crop coverage, but they have limitations in dense crop coverage while in booting and heading stages.