OPERA DIST-ANN: Annual Vegetation Disturbance from Landsat and Sentinel-2

Global satellite data from the Harmonized Landsat Sentinel-2 (HLS) program is processed to map annual vegetation disturbance at a 30-meter resolution. The dataset contains 21 layers, including vegetation disturbance status, confidence, date of initial disturbance, and duration, derived from the higher-frequency DIST-ALERT product. It tracks confirmed decreases in vegetation cover, with results dependent on subsequent cloud-free observations for confirmation.

Use Cases

• Monitoring deforestation and forest degradation based on the vegetation disturbance status layer.
• Assessing post-wildfire vegetation recovery timelines using the disturbance duration and date of initial disturbance.
• Analyzing trends in agricultural land abandonment or intensification from annual disturbance maps.
• Validating other land cover change products with the independent confidence and anomaly value layers.

Strengths

• Provides a confirmed annual disturbance product, reducing false positives from ephemeral changes.
• Contains 21 distinct data layers offering detailed auxiliary information like confidence and anomaly values.
• Uses a high-resolution (30m) grid aligned with the global Military Grid Reference System (MGRS).
• Available on multiple major data platforms (AWS, NASA, Data.gov), indicating reliability and broad access.

Limitations

• Key metadata like row count, file size, and specific temporal coverage are unreported across all sources.
• There is a noted latency in product generation as disturbances require confirmation from subsequent cloud-free scenes.
• License information conflicts between sources (CC-BY-4.0 on AWS vs. 'other-license-specified' on Data.gov).

Provenance

Source

OPERA (Observational Products for End-Users from Remote Sensing Analysis), likely involving NASA JPL.

Collection Method

Derived from the DIST-ALERT product, which analyzes Harmonized Landsat Sentinel-2 (HLS) Version 2 data.

Freshness

2026-04-09 23:26:04.363246 (from AWS Open Data and Data.gov)

Geography

Global, gridded to the HLS V2 tiling system.