REMOTE SENSING
AOIs Time Series
Requirements:
The AOIs Time Series endpoint provides preprocessed historical time series data for Areas of Interest (AOIs). This service analyzes crop trends with comprehensive temporal analysis of agricultural areas using NDVI statistics and other vegetation indices.
You can use the AOIs Time Series endpoint to retrieve temporal statistics for your fields.
When to use
Use AOIs Time Series when you need:
- Historical trend analysis: Track vegetation changes over time across multiple growing seasons
- Crop performance monitoring: Compare current season performance against historical averages
- Seasonal pattern identification: Understand typical vegetation cycles for your agricultural areas
- Data-driven decision making: Base agricultural decisions on long-term temporal data
How it works
The AOIs Time Series service aggregates satellite imagery data over time to create statistical summaries for your defined areas of interest. The service processes multiple satellite sources and provides clean, analysis-ready time series data.
Quick start
- Prerequisites: Ensure you have a valid Cropwise authentication token and Remote Sensing contract
- Define your AOI: Set up your Area of Interest using field boundaries
- Set time parameters: Specify start and end dates for your analysis period
- Choose data source: Select satellite data sources (Sentinel, Landsat, MODIS)
- Retrieve time series: Call the API to get preprocessed temporal statistics
Common use cases
- Crop yield prediction: Analyze historical NDVI patterns to predict current season yields using 5-year historical time series for yield modeling
- Irrigation scheduling optimization: Monitor vegetation stress patterns to optimize irrigation timing with weekly time series for current growing season
- Multi-field comparison: Compare vegetation performance across multiple fields using time series data for multiple AOIs
Response format
The API returns time series data with statistical aggregations:
- Index Mean: Average vegetation index values
- Index Standard deviation: Variability within the AOI
- Cloud coverage: Cloud cover indicators
- Data coverage: Scene coverage percentage
- Histogram: Pixel value distribution
Next steps
- Image Zone Generation - Create prescription zones from time series analysis
- Vegetation Change Reports - Generate automated change detection reports
- Field Classification - Classify field priorities based on temporal patterns