Weekly cloud free Harmonized Landsat Sentinel (HLS) Normalized Difference Vegetation Index (NDVI) estimates for western United States (2016 – 2019)
Dates
Publication Date
2021-04-22
Start Date
2016
End Date
2019
Citation
Dahal, D., Parajuli, S., Pastick, N.J., and Wylie, B.K., 2021, Weekly cloud free Harmonized Landsat Sentinel (HLS) Normalized Difference Vegetation Index (NDVI) estimates for western United States (2016 – 2019): U.S. Geological Survey data release, https://doi.org/10.5066/P9KKPT07.
Summary
In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks in sagebrush ecosystem [...]
Summary
In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks in sagebrush ecosystem and wildfire activity, that are not possible with coarse scale datasets (such as 250-m).
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Related External Resources
Type: Related Primary Publication
Pastick, N.J., Dahal, D., Wylie, B.K., Parajuli, S., Boyte, S.P., and Wu, Z., 2020, Characterizing Land Surface Phenology and Exotic Annual Grasses in Dryland Ecosystems Using Landsat and Sentinel-2 Data in Harmony: Remote Sensing, v. 12, no. 4, p. 725, https://doi.org/10.3390/rs12040725.
The goal of this research is to develop and analyze historic and rapid estimates of weekly cloud-free normalized difference vegetation index(NDVI) data (30-m spatial resolution) throughout rangeland ecosystems in the western United States, using harmonized Landsat and Sentinel-2(HLS) (https://hls.gsfc.nasa.gov/) data, remote sensing metrics, and data mining techniques.