Problem Statement
A Singapore-based geospatial analytics firm was struggling to aggregate satellite imagery from multiple providers. As a result, analysts had to operate across fragmented platforms, which made it difficult to deliver timely and accurate insights. Moreover, switching between different systems was time-consuming, often leading to delays in analysis and reduced operational efficiency. Consequently, the company needed a unified satellite imagery platform that could bring together both live and historical imagery, provide a single interface for comparison, and scale as data demands grew.

Challenges Faced
The primary challenges included:

• Fragmented access to satellite imagery from multiple providers.
• Difficulty comparing live and historical data efficiently.
• Complex workflows that required specialized knowledge.
• Limited scalability for handling large datasets and future expansion.

Solution Provided
To address these challenges, a Unified Satellite Imagery Platform was developed. This platform, therefore, aggregated REST APIs from multiple vendors, enabling analysts to access diverse imagery through a single, seamless interface. In addition, it provided live previews and historical imagery, simplifying the comparison process for users.

Key Features of the Solution:

• Aggregated APIs: Combined data from multiple satellite providers into a single unified interface.
• Live and Historical Previews: Allowed users to view both current and past satellite imagery efficiently.
• Modular Backend Architecture: Ensured scalability, performance, and future extensibility.
• User-Friendly Interface: Made satellite data accessible even to non-specialists, reducing reliance on experts.

Tools / Tech Stack
The platform leveraged modern technologies to ensure flexibility and robustness:

• Frontend: Angular
• Backend: Node.js
• Data Processing & Analytics: Python

Results & Business Impact
The Unified Satellite Imagery Platform significantly improved operational efficiency and user experience. For example, users could now easily access satellite data, previously restricted to specialists. Furthermore, comparing and selecting imagery from multiple providers became simple and intuitive. In addition, workflows were streamlined, reducing time spent on data collection and analysis, which allowed analysts to focus on generating actionable insights. Ultimately, the platform empowered the firm to scale operations, respond faster to data requests, and deliver more timely geospatial intelligence.

In summary, the platform provided a single, unified interface for live and historical satellite imagery, simplified complex workflows, and enhanced decision-making capabilities. Moreover, its modular architecture ensures that the system can continue to evolve and handle future data demands, making it a scalable, long-term solution for geospatial analytics.