Suitability of the vegetation indices normalized difference index (NDVI), blue (BNDVI), and yellowness (NDYI) obtained by means UAV at flowering stage oil seed rape for prediction yield usability these in identification anomalies condition growth were verified based on regression analysis. Correlation analysis was performed to find degree dependence values NDVI, BNDVI, NDYI indices, which revea...

The current study aimed to evaluate the potential of normalized difference vegetation index (NDVI), and yellowness (NDYI) derived from red–green–blue (RGB) imaging monitor growth status winter oilseed rape seeding ripening stage. Subsequently, collected values were used their correlations with yield rape. Field trials three seed densities nitrogen rates conducted for two years in Salzdahlum, Ge...

As a major oilseed crop with high ornamental value, Accurate and timely determination of their distribution area under cultivation is essential to ensure food security achieve sustainable development goals. The bright yellow flowers are unique feature rapeseed compared other crops. Therefore, the flower index was previously used detect on aerial images or medium-resolution satellites. However, ...

Canola (Brassica napus), with its prominent yellow flowers, has unique spectral characteristics and necessitates special indices to quantify the flowers. This study investigated four for high-resolution RGB images segmenting flower pixels. The compared vegetation digitally canola area develop a seed yield prediction model. A small plot (2.75 m × 6 m) experiment was conducted at Kernen Research ...

Precise and timely information on crop spatial distribution over large areas is paramount to agricultural monitoring, food security, policy development. Currently, automatically classifying types at a scale challenging due the scarcity of ground data. Although previous studies have indicated that transductive transfer learning (TTL) promising method address this problem, it performs poorly with...

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...