AcreLens API

Overview

AcreLens offers a set of APIs for integrating agricultural intelligence into various applications. The platform provides data and analytics derived from satellite imagery, meteorological sources, and proprietary machine learning models to support decision-making in agriculture. Key offerings include tools for monitoring crop health, predicting harvest yields, assessing soil moisture levels, and delineating field boundaries programmatically.

The Crop Health API, for instance, processes satellite imagery to generate vegetation indices such as NDVI (Normalized Difference Vegetation Index), providing insights into plant vigor and stress levels across large agricultural areas. This data can be used by farm management systems to identify areas requiring specific attention, optimize fertilizer application, or detect early signs of disease. The Yield Prediction API utilizes historical data, weather forecasts, and satellite observations to forecast harvest outcomes, aiding in logistics planning and market analysis. Developers can integrate these predictions into supply chain management tools or financial models for agricultural commodities.

AcreLens is designed for use by agritech startups developing new solutions, established agricultural enterprises seeking to enhance operational efficiency, and research institutions conducting studies on agricultural productivity and environmental impact. Its capabilities are particularly relevant for precision agriculture applications, where granular data is crucial for optimizing resource use and maximizing output. The API documentation provides interactive examples and guides for common use cases, facilitating integration for developers working with Python and JavaScript SDKs. The free Developer Plan allows for initial prototyping and testing of the APIs with a limited number of calls and acres processed per month, enabling evaluation before committing to a paid plan.

The platform's focus on data-driven agriculture aligns with broader trends in the industry towards digitalization and automation. By providing structured access to complex agricultural data, AcreLens aims to lower the barrier for developing sophisticated applications that can address challenges such as food security, sustainable farming practices, and climate change adaptation. For example, the Soil Moisture API can inform irrigation scheduling, reducing water waste and improving crop resilience in drought-prone regions. Similarly, the Field Boundary API assists in automating land management tasks, such as parcel identification and area calculation, which are fundamental for many agricultural software platforms.

Key features

• Crop Health API: Provides vegetation indices (e.g., NDVI, EVI) and other metrics derived from satellite imagery for monitoring plant vigor and identifying stress areas within fields.
• Yield Prediction API: Offers forecasted harvest yields based on historical data, current growing conditions, and weather patterns to support planning and risk assessment.
• Soil Moisture API: Delivers estimates of soil moisture content, critical for optimizing irrigation schedules and managing water resources efficiently.
• Field Boundary API: Enables the detection and delineation of agricultural field boundaries from satellite imagery, useful for land management and spatial analysis.
• Historical Data Access: Access to historical satellite imagery and agricultural data for trend analysis and model training.
• Geospatial Analysis Tools: Built-in capabilities for processing and interpreting geospatial data relevant to agriculture.
• Developer SDKs: Officially supported client libraries for Python and JavaScript to streamline API integration.
• Interactive Documentation: Clear API reference with interactive examples to assist developers in implementation.

Pricing

AcreLens offers a free developer plan for evaluation and prototyping, with paid tiers scaling based on API call volume and acres processed. As of May 2026, the pricing structure is as follows:

For detailed and up-to-date pricing information, refer to the official AcreLens pricing page.

Common integrations

• Farm Management Information Systems (FMIS): Integrate AcreLens data into platforms like ArcGIS Field Maps for enhanced mapping and operational planning.
• Weather Data Providers: Combine AcreLens insights with detailed weather forecasts from services like AWS Data Exchange for more accurate yield predictions and irrigation scheduling.
• IoT Sensor Networks: Complement sensor-based soil moisture and environmental data with satellite-derived insights for a comprehensive view of field conditions.
• Geospatial Analysis Software: Export data for further analysis in GIS tools or custom mapping applications.
• Business Intelligence Dashboards: Visualize agricultural data and trends using tools such as Tableau or Power BI.

Alternatives

• Planet Labs: Offers daily satellite imagery and geospatial data for various industries, including agriculture.
• Descartes Labs: Provides a platform for geospatial intelligence and machine learning, with applications in agriculture and natural resources.
• Arable: Combines in-field sensing with remote sensing and machine learning for crop and weather insights.

Getting started

To begin using the AcreLens API, you typically need to obtain an API key and then use one of the provided SDKs or make direct HTTP requests. Below is a Python example demonstrating how to fetch crop health data for a specific field using the AcreLens Python SDK:

import os
from acrelens import AcreLensClient

# Replace with your actual API key from the AcreLens dashboard
API_KEY = os.environ.get("ACRELENS_API_KEY", "YOUR_ACRELENS_API_KEY")

client = AcreLensClient(api_key=API_KEY)

# Example field ID (replace with a valid field ID from your account)
field_id = "field_abc123"

try:
    # Fetch crop health data for the specified field
    crop_health_data = client.crop_health.get_field_health(field_id=field_id, date="2025-04-15")
    
    print(f"Crop Health Data for Field {field_id} on 2025-04-15:")
    print(f"NDVI: {crop_health_data.ndvi}")
    print(f"EVI: {crop_health_data.evi}")
    print(f"Stress Level: {crop_health_data.stress_level}")
    
    # You can access other attributes as defined in the API reference

except Exception as e:
    print(f"Error fetching crop health data: {e}")

# Example of fetching yield prediction for a field
try:
    yield_prediction = client.yield_prediction.get_field_prediction(field_id=field_id, season_year=2025)
    print(f"\nYield Prediction for Field {field_id} in 2025:")
    print(f"Predicted Yield (tons/acre): {yield_prediction.predicted_yield}")
    print(f"Confidence Interval: {yield_prediction.confidence_interval}")
except Exception as e:
    print(f"Error fetching yield prediction: {e}")

Before running this code, ensure you have the AcreLens Python SDK installed (pip install acrelens-sdk) and have set your ACRELENS_API_KEY environment variable or replaced the placeholder directly. The AcreLens API reference provides comprehensive details on all available endpoints and data models.