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Full catalog/OPERA_L3_DIST-ALERT-HLS_V1
OPERA_L3_DIST-ALERT-HLS_V1·v1·dataset

Alerts where land was suddenly disturbed (Landsat+Sentinel-2)

OPERA Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 product (Version 1)
land NASA LPCLOUD Level 3 active COG
In plain English

What it measures. Alerts flagging places where vegetation cover has suddenly dropped, signaling disturbances like deforestation, fire, or land clearing, at 30-meter detail.

How it's made. Generated from combined Landsat 8/9 and Sentinel-2 imagery (the Harmonized Landsat Sentinel-2 dataset), which together revisit the same spot every couple of days, by spotting drops in reflected light that indicate vegetation loss.

How & where you'd use it. Useful for quickly catching land changes such as forest loss or damage, supporting conservation, monitoring, and rapid response.

What's measured

LAND SURFACE › LAND USE/LAND COVERHUMAN DIMENSIONS › ENVIRONMENTAL IMPACTS › MECHANICAL DISTURBANCELAND SURFACE › LAND USE/LAND COVER › DISTURBANCE

Coverage & cadence

  • Time span2022-01-01 → ongoing
  • Measured bySentinel-2A (Sentinel-2 MSI) · Sentinel-2B (Sentinel-2 MSI) · Sentinel-2C (Sentinel-2 MSI) · LANDSAT-8 (OLI) · LANDSAT-9 (OLI)
  • Processing levelLevel 3
  • Spatial extent-180, -90, 180, 90
  • FormatsCOG
  • StatusACTIVE

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

The Observational Products for End-Users from Remote Sensing Analysis ([OPERA](https://www.jpl.nasa.gov/go/opera)) Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 (HLS) product Version 1 maps vegetation disturbance alerts that are derived from data collected by Landsat 8 and Landsat 9 Operational Land Imager (OLI) and Sentinel-2A, Sentinel-2B, and Sentinel-2C Multi-Spectral Instrument (MSI). A vegetation disturbance alert is detected at 30 meter (m) spatial resolution when there is an indicated decrease in vegetation cover within an HLS pixel. The Level-3 data product also provides additional information about more general disturbance trends and auxiliary generic disturbance information as determined from the variations of the reflectance through the HLS scenes. [HLS](https://lpdaac.usgs.gov/product_search/?collections=HLS&status=Operational&view=list) data represent the highest temporal frequency data available at medium spatial resolution. The combined observations will provide greater sensitivity to land changes, whether of large magnitude/short duration or small magnitude/long duration. The OPERA_L3_DIST-ALERT-HLS (or DIST-ALERT) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate file. There are 19 layers contained within the DIST-ALERT product. The layers for both vegetation and generic disturbance include disturbance status, loss or anomaly, maximum loss anomaly, disturbance confidence layer, date of disturbance, count of observations with loss anomalies, days of ongoing anomalies, and day of last disturbance detection. Additional layers are vegetation cover percent, historical percent vegetation cover, and data mask. See the Product Specification Document (PSD) for a more detailed description of the individual layers provided in the DIST-ALERT product. The OPERA project is funded by NASA’s Satellite Needs Working Group (SNWG) which provides data products developed to meet the needs of stakeholders from US government agencies. The OPERA_L3_DIST-ALERT-HLS product contains modified Copernicus Sentinel data (2020-2025). Known Issues * Additional usage constraints are provided under Section 5 of the Algorithm Theoretical Basis Document (ATBD).

Get the data

opera_l3_dist-alert-hls_v1_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="OPERA_L3_DIST-ALERT-HLS_V1",
    version="1",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from LPCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.