SpaceEye

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Agriculture

It is required accurate information collected on a regular basis for precise farmland operation, such as detecting changes in farmland, observing productivity, and predicting yield levels. Through satellite images, you can predict the yield of crops according to the farmland boundary or check the growth status of crops through the difference in NIR (Near Infrared) data that is reflected according to crop conditions. It can also measure the condition of soil moisture to make farmland more efficient.

Sample Imagery

Applications

Operating Farmland

The precisely calibrated optical sensors of our sub-meter class high-resolution imagery deliver the foundational data required for advanced precision agriculture. Continuous observation of mega-scale farmlands allows operators to manage agricultural assets efficiently by detecting localized drought zones early and deploying proactive irrigation. Furthermore, the sharp clarity of this data assists in classifying crop varieties, measuring exact cultivation acreage, and accurately forecasting the regional supply and demand of agricultural commodities.

Monitoring Growth Status of Crops

Healthy vegetation reflects a high amount of Near-Infrared (NIR) energy. By combining images captured in the NIR, Red, and G bands into a false-color composite, areas with vigorous plant growth stand out in vibrant red. Because thriving crops heavily absorb visible light for photosynthesis while intensely reflecting NIR light, their overall vitality can be assessed visually and quantitatively. Leveraging this spectral feature, our sub-meter class high-resolution imagery enables agribusinesses to assess crop health at scale and mathematically calculate vegetation vitality indexes.

Smart Farm

Supported by satellite-based remote sensing, our sub-meter class high-resolution imagery drives maximum efficiency in agricultural water management by meticulously analyzing crop conditions across vast fields. This data powers next-generation smart farming by identifying anomalies early—such as pest infestations or nutrient deficiencies—allowing farmers to apply targeted treatments or fertilizers only where needed. Additionally, by integrating historical sowing and harvesting schedules with periodic vegetation vitality data, you can build predictive crop maps to estimate yields with high confidence.