16 day customizable Landsat NDVI from Robinson et al. 2017.
Please see the information tab to learn more about image options.
Use the polygon drawing tool or upload a zipped shapefile to define the preview/download area.
On-the-fly image preview is available for areas less than 1,000 sq km. Smoothed images are not available for preview. Images that require more data (e.g., longer climatology or inclusion of SLC-off) will take longer to load. This feature is experimental.
Use slider to adjust image transparency
NDVI images within North America can be created for areas less than 25,000 sq km.
Data are processed as ordered. Please enter your email address and hit 'Submit order'. You will receive an email when the processing is complete.
The methods to produce these data are described in Robinson et al. 2017.
This application processes available Landsat 5, 7, and 8 surface reflectance images to create a 16 day, 30 meter NDVI product for North America. An average composite of all data within a 16 day time period is used.
Clouds and shadows (as determined from the Landsat surface reflectance product) are excluded from the composite. If pixels are unavailable during the time period, the median of a user specified climatology is used to fill in missing pixels (i.e., the median of the previous X years, for that specific time period). The user may also request the data be smoothed; if selected, a simple linear smoothing is applied. Note that smoothing may not be suitable for all areas or analyses.
Data are scaled by 100. A quality band is also provided, with the following values:
Filenames are: landsatNDVI[S or X][C##][SLC or XXX][YYYY][DOY] where
This application is maintained by Brady Allred.
sidebar-v2 theme by Tobias Bieniek.
Due to the return time of Landsat satellites, data may be limited during the 16 day period; cloudy pixels or the lack of surface reflectance images will reduce the overall data available for the composite. Additionally, due to the orbital paths of the Worldwide Reference System 2, a composite may be created from multiple scenes obtained from different dates within the 16 day period (e.g., different scenes that intersect an area of interest but are acquired at the beginning and end of the 16 day period). If data are incomplete (e.g., cloudy pixels, scan line corrector errors of Landsat 7 ETM+, etc.) within these scenes, it is possible that two adjacent pixels can be from two different dates; if data are unavailable within the time period then a user specified climatology is used for gap filling, further distancing the dates used in the composite. As a result, these data are best suited for local or regional applications, where incomplete data are minimized due to a smaller spatial extent.
Landsat 7 ETM+ SLC-off refers to Landsat 7 images collected after the scan line corrector (SLC) failure, May 31, 2003. These images will have data gaps across an image in a striping manner. Inclusion of SLC-off data will potentially include much more data in the composite, but may result in visual artefacts due to gap filling with different dates. Exclusion of SLC-off will exclude all Landsat 7 ETM+ images after May 30, 2003. Note that from May 2012 to April 2013, only Landsat 7 was operational.
Currently only NDVI is available. Other indices may be added in the future.
These data are not static, but rather dynamic based upon the specific requests of users. To reduce processing, storage, and delivery costs, data are processed and delivered only as requested.
Processing occurs within Google Earth Engine, a planetary-scale platform for earth science data and analysis.
Orders are limited to small spatial extents in order to reduce processing time and provide availability to a greater number of users. Additionally, limited funding restricts data delivery costs.
This service is in Beta, is not guaranteed, and is not subject to any service-level agreement (SLA). While we will do everything reasonable to maintain availability, downtime or failure may occasionally occur.
Please cite as:
Robinson, N.P., B.W. Allred, M.O. Jones, A. Moreno, J.S. Kimball, D.E. Naugle, T.A. Erickson, and A.D. Richardson. 2017. A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States. Remote Sensing 9:863.