Crop Type Classification & Mapping

Feiyan delivers crop classification and acreage mapping using the Swift4D Platform and SwiftAI engine, analyzing spectral data from satellites and the AIMS system. By capturing unique spectral responses across key phenological stages, we enable precise identification to support subsidy compliance, supply chain traceability, and land-use auditing.

Our Differentiated Solution Framework

Built on Swift4D, the framework integrates data acquisition, spectral intelligence, and mapping:

Multi-Source Acquisition: AIMS captures large-format imagery, hyperspectral, and LiDAR in one flight; combined with Y-1 UAVs and satellite data for full coverage.

Spectral Intelligence: Analyzes phenological spectral/textural signatures to distinguish wheat, corn, rice, and other major crops.

SwiftAI Classification: Automates crop typing and acreage extraction, generating distribution polygons and statistics with field-level accuracy validation.

Multi-Temporal Comparison: Tracks rotation and land-use changes for compliance and end-to-end supply chain traceability.

Application Scenarios & Client Value

Application Scenarios

Acreage statistics and subsidy compliance (e.g., CAP)

Supply chain traceability and origin certification

Land-use change auditing (abandonment, conversion)

Agricultural insurance underwriting and loss assessment

Precision farming (variable-rate fertilization, yield prediction)

Client Value

Objective: AI eliminates subjective bias, enhancing audit credibility.

Efficient: Thousand-km² mapping compressed from months to weeks.

Reusable: Serves statistics, subsidies, insurance, and auditing—avoiding duplication.

Traceable: Multi-temporal archiving meets regulatory and trade requirements.

Yield-Optimized: Classification outputs empower precision agriculture, guiding input application and harvest forecasting.