Development of a Spectral Index for the Detection of Yellow-Flowering Vegetation

Floral phenology as a special indicator of climate change and vegetation dynamics is drawing more attention. The long-term observations flowering events collected at scattered ground sites have accumulated valuable priority on the understanding floral phenology, but with insufficient investigation spatio-temporal regional scale, which mainly induced by lack effective ways to capture pixel-based flower from remote sensing images. existing yellowness indices are constructed for rape (Brassica napus L.) less suppression bright background dark green vegetation, further inadequate consideration physiological characteristics temporal spectral signature investigated vegetation. In this paper, we examined several other representative types determine features yellow-flower period within growing season, then selected visible near-infrared bands construct Novel Yellowness Index (NYI) an enhancement mechanism plants. proposed NYI were discussed variation mathematical properties instances, cross-compared three typical indices—Ratio (RYI), Normalized Difference (NDYI), Ashourloo Canola (ACI) —over various yellow-flowering species multiple scales, validated available PhenoCam network stations field phenological Görlitz, Sachsen, Germany. addition, applied detect using Sentinel-2 image Görlitz area case study. Results show that exhibits potential increased sensitivity density, reduction noise introduced or different scales. As density increases 33% 78%, relative differences captured can reach up 74%, compared no than 57%. cross-comparison indicates performs better higher consistent observation Deutscher Wetterdienst station in capturing yellow density. study application identification good accuracy overall 97.5%, Kappa coefficient 0.94, F score 0.96. Consequently, satellite-derived index will be means investigate planting range such rape.