Satellite NDVI, moisture and snow indices since the 1980s, plus growing-season phenology, at up to 10 m for crop, range and wildland monitoring

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Indices & Seasonality is terraPulse's set of satellite-derived index and phenology datasets for monitoring crop-, range- and wildland systems, which need frequently updated data on plant health and condition, surface moisture and snow. terraPulse computes satellite-based indices at up to 10-metre spatial resolution, interpolated to daily resolution, with records from the mid-1980s to the present and a latency of roughly 10 days. Standard products include the Normalized Difference Vegetation Index (NDVI), wetness/moisture indices (NDWI, NDMI), the Normalized Difference Snow Index (NDSI) and the Normalized Burn Ratio (NBR), together with differences over time and long-term summaries of historical conditions and their variability. Seasons & Phenology layers derived from the index time series map the start, peak, end, length and total of each growing season at up to 10 m from 2001 onward, and a separate snow-cover dataset maps snow on the ground at daily, 500-metre resolution.
The indices are viewed in the terraView dashboard, which shows the latest daily NDVI on the map and the full time series for a pinned location; terraView draws on the Landsat archive (1984 to present) and Sentinel-2 (10 m, 2017 to present). terraPulse data are also delivered through the subscription terraServe API (CSV, JSON or GeoTIFF values, or XYZ map tiles for ArcGIS, QGIS, Leaflet and OpenLayers) and by SFTP. Pixel- and regional-level uncertainty statistics are available on request.
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Data Fusion & Analytics
Combines data sources and applies analytics to uncover patterns.
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Data Visualisation
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terraPulse
terraPulse maps and monitors the status, history and potential of large landscapes through satellite-based measurements of forest, crop, range and wildland productivity. Its data cube of ecosystem cover, structure and function, from 1984 to the present, is delivered as datasets, through the terraView browser platform and through the terraServe API. The company was founded in 2014 by scientists from the University of Maryland Global Land Cover Facility.
2014
Founded
1-10
Team size
United States of America
Country
Displays data in interactive dashboards, charts, or graphs.