The monitoring period covered the key growth stages and maturation of early rice in Southern China, while the sowing and transplanting of late rice have been completed. Overall, crop conditions were close to average, with regional variations.

CropWatch agroclimatic indicators showed that the RAIN for this period was 1537 mm, 16% higher than the 15-year average (15YA). The TEMP was 23.7°C, 1.0°C above average, while RADPAR was 3% below average. These factors combined resulted in a BIOMSS 1% higher than the 15YA.

The CALF reached 97%, consistent with the 5-year average. The VCIx for the region was 0.90, with most areas showing values between 0.8 and 1.0, indicating generally favorable crop growth. However, parts of the Pearl River Delta and western Yunnan showed VCIx values below 0.8. The CPI was 0.98, slightly below average levels.

NDVI departure clustering analysis revealed increasing spatial disparities in crop growth across the region, with deviations from average levels expanding in both directions. Crop growth in most areas was below average, possibly related to extreme precipitation events and regional flooding disasters. The biomass departure map further confirmed this: biomass variations in most areas were within ±10% of average, while parts of western Yunnan and western Guangxi showed below-average biomass (-20% to -10%).

In summary, crop conditions in Southern China were close to average but slightly lower, particularly in areas such as western Yunnan and western Guangxi. While above-average rainfall benefited crop growth in most areas, continuous heavy rainfall events led to localized flooding and crop damage in certain areas, especially in central and northern Guangxi, the BeiJiang river basin in northern Guangdong province, and Meizhou city in eastern Guangdong. Further close monitoring of these anomalous areas is necessary to assess the potential impact of these factors on final crop production.

Figure 4.12 Crop condition Southern China region, April - July 2024

(a) Crop condition development graph based on NDVI

(b) Time series rainfall profile

(c) Time series temperature profile

(d) Maximum VCI

(e) Spatial NDVI patterns compared to 5YA           (f) NDVI profiles

(g) Potential biomass departure from 5YA

(h) Crop condition classification

(i) CPI time series