Journal
GEOJOURNAL
Volume 83, Issue 4, Pages 819-834Publisher
SPRINGER
DOI: 10.1007/s10708-017-9805-8
Keywords
Northern Great Plains; NDVI time-series; C3 and C4 classification; Grassland monitoring
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Temperate grasslands are a highly threatened global biome. Complicating management and conservation strategy development, modern grasslands can be difficult to characterize across landscapes since they range from native and semi-native to completely non-native species compositions such as those found in heavily managed pastures. Similar to methods used to differentiate C3 and C4 grasses, we investigate the ability of using temporal variations in growth characteristics as an alternative pathway to predicting native versus introduced species composition across grassland landscapes. To do this, we conducted an exploratory analysis using a time-series of Normalized Difference Vegetation Index values as a measure of vegetation greenness with Landsat 5 TM imagery across a growing season and performed an unsupervised classification. Results from the classification were compared with field observation to determine if we can differentiate between native and introduced grassland types in the Northwest Glaciated Plains subecoregion of northeastern Montana. Our results indicated that we predicted grassland cover with 81% accuracy within our 200 km(2) study area and 71% accuracy in our 5000 km(2) secondary study area. Further extrapolation of our methodology, combined with the refinement of vegetation indices of time-series imagery, classification algorithms and the availability of data from planned Landsat and Sentinel missions, may provide the spatial detail necessary to improve grassland monitoring and rangeland management over large areas.
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