Explore Agricultural Understanding data with Google Earth

Google Earth offers an intuitive way to explore Agricultural Understanding data, allowing you to see agricultural landscapes and perform basic visual analysis by overlaying datasets on high-resolution satellite imagery. This page describes how to get started using Agricultural Understanding data with Google Earth.

Capabilities and limitations

Capabilities:

  • Field boundary visualization: The Agricultural Understanding layer displays machine-learning-derived boundaries for various landscape features, including agricultural fields, trees, farm ponds, dug wells, and other water bodies.
  • Contextual understanding: Overlay Agricultural Understanding data on Google Earth's base imagery to see field shapes and types in the context of terrain, roads, and other geographical features.
  • Basic measurement: Use Google Earth's built-in tools to get approximate measurements of distances and areas to complement the data provided by the landscape understanding layer.
  • Historical imagery analysis: Use the Google Earth historical imagery slider to view how the landscape has changed over time against current Agricultural Understanding boundaries.

Limitations:

  • Snapshot data: Accessing historical versions of boundaries is limited, as Historical Imagery does not dynamically filter custom layers.
  • Crop monitoring data not available: Time-series seasonal crop predictions and historical crop monitoring data are not available as visual layers in Google Earth.
  • Zoom level display: At lower zoom levels, data will be aggregated into hexagonal bins.
  • Styling and rendering order: The layer uses predefined styling and limited restyling options are supported. Filtering of features is not supported for this Earth layer.
  • Limited interactivity: Clicking a feature shows basic attributes. To access full GeoJSON payloads or crop monitoring, use the REST API.
  • Regional coverage: The layer is available in portions of APAC, including India.
  • Non-agricultural exclusions: By default, the system excludes non-agricultural areas like deserts and urban regions.

Setup

  1. Open Google Earth.
  2. Follow the Google Earth Data Layers setup guide to locate layers.
  3. Find the layer titled Agricultural Landscape Understanding.
  4. Enable the layer to overlay boundaries on the map.

Data mapping

Visual features in the Google Earth layer correspond to Agricultural Understanding dataset properties:

  • Type: Corresponds to properties.alu_type in the API (for example, field, farm_pond, trees).
  • Area: Derived from properties.area_sq_m.
  • Confidence: Corresponds to properties.class_confidence.
  • ID: The feature id (the Plus Code of the feature centroid).
  • Capture date: Corresponds to capture_timestamp_sec.

Example usage

  1. Visualize farm layouts: Search for an agricultural location by latitude and longitude or Plus Code (for example, 7J9W7QG9+463M) to inspect field boundaries.
  2. Compare boundaries with historical imagery: Enable the historical imagery slider to observe landscape changes over time against fixed boundary footprints.
  3. Identify irrigation sources: Inspect features styled as farm_pond, dug_well, or other_water adjacent to field parcels.
  4. Estimate surface areas: Use Google Earth's measurement tools to measure field perimeters or distances to infrastructure.