Part 10/12:
Challenges and Future Directions
Despite the exciting potential, PRP candidly discusses hurdles:
Data Quality and Consistency: Cloud cover, haze, and other atmospheric factors impact imagery.
Ground Truth Collection: Accurate ground data remains essential for model validation and trust-building, requiring substantial effort and resources.
Market Development: Since AI models are highly localized and domain-specific, extensive pilot projects and customer education are necessary.
Cost and Infrastructure: Building indigenous satellite payloads involves high capital but promises long-term gains in cost control and data sovereignty.