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Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem (June 19, 2017)

Dates

Publication Date
Time Period
2017-06-19

Citation

Boyte, S.P., and Wylie, B.K., 2017, Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem (June 19, 2017): U.S. Geological Survey data release, https://doi.org/10.5066/F7M32TNF.

Summary

This dataset provides a near-real-time estimate of 2017 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through June 19, 2017. This is the second iteration of an early estimate of herbaceous annual cover for 2017 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/F7445JZ9). The pixel values for this most recent estimate ranged from 0 to100% with an overall mean value [...]

Contacts

Point of Contact :
Stephen P. Boyte
Originator :
Stephen P. Boyte, Bruce K. Wylie
Metadata Contact :
Stephen P. Boyte
Distributor :
U.S. Geological Survey - ScienceBase
USGS Mission Area :
Land Resources
SDC Data Owner :
Earth Resources Observation and Science (EROS) Center

Attached Files

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2017nrt_JuneAnnHerbaceous_metadata_FGDC.xml
Original FGDC Metadata

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14.54 KB application/fgdc+xml
2017_JuneAnnHerbaceous.jpg thumbnail 24.49 MB image/jpeg
2017nrt_JuneAnnHerbaceous.img 20.62 MB application/unknown
2017nrt_JuneAnnHerbaceous.rrd 7.06 MB application/unknown
2017nrt_JuneAnnHerbaceous.img.aux.xml 1.8 KB application/xml
2017nrt_JuneAnnHerbaceous.img.lyr 25.5 KB application/x-tika-msoffice

Purpose

These data were developed to provide land managers and researchers with near-real-time estimates of spatially explicit percent cover predictions of herbaceous annual vegetation cover in the study area. Appropriate use of the data should be defined by the user; however, this data comes with caveats. First, these estimates should be viewed as relative abundances. Second, each pixel in the dataset represent 250-meters and can include a geolocation error of up to 125 meters. Comparing this dataset to similar datasets with different spatial resolutions can lead to substantial differences between datasets.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/F7M32TNF

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