Background:
Precision farming in agriculture is nowadays gaining attention as it helps to address the growing demand for food by optimizing resource usage and providing sustainable solutions. This helps combat climate change and reduces economic strain. The integration of satellite data into farming practices is revolutionizing the industry by providing real-time, high-resolution data on crop health, soil conditions, and weather patterns, allowing for more informed decision-making and improved productivity.
Farmers and agribusinesses were facing challenges due to the lack of precise information about soil moisture, crop health, and optimal harvesting times, resulting in under-utilization of resources and inconsistent yields. There was a growing need for an innovative solution that could offer actionable insights based on real-time data to enhance productivity and profitability.
Action
To address this issue, ASQI introduced an advanced satellite data integration solution designed to enhance crop yield predictions based on several parameters like soil moisture, NVDI, ET, leaf N, etc. The solution combines high-resolution satellite imagery, weather data, and soil monitoring tools to deliver precise insights on field conditions. Here’s how it works:
- Satellite-based crop monitoring: Satellite imagery helps farmers monitor crop and soil health at different growth stages, identify problem areas, and optimize interventions such as irrigation and fertilization.
- Predictive analytics for yield forecasting: Integrating machine learning models to process satellite data, providing farmers with accurate yield predictions and respective suggestions to maximize the benefit.
Results:
This integration led to significant improvements in crop management and yield outcomes.
- Real-time monitoring and timely interventions helped X% increase in overall crop yields,
- Y% reduction in water usage, with precise soil moisture monitoring preventing over-irrigation.
- Farmers reported a Z% decrease in input costs (fertilizers, pesticides, etc.) through optimized usage and targeted application.
- The solution helped reduce crop losses by up to A%, as farmers were able to address problem areas in the field more effectively and prevent issues like drought stress and pest infestation.
