DOI: 10.1016/j.jag.2016.06.012
Scopus记录号: 2-s2.0-85032070587
论文题名: Cattle stocking rates estimated in temperate intensive grasslands with a spring growth model derived from MODIS NDVI time-series
作者: Green S ; , Cawkwell F ; , Dwyer E
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 166
结束页码: 174
语种: 英语
英文关键词: NDVI
; Pasture
; Stocking rate
; Time-series
Scopus关键词: cattle
; error analysis
; grassland
; grazing
; growth response
; MODIS
; NDVI
; pasture
; pixel
; spring (season)
; temperate environment
; time series
; Ireland
; Animalia
; Bos
英文摘要: There is an identified need for high resolution animal stocking rate data in temperate grassland systems. Here is presented a 250 m scale characterization of early spring vegetation growth (DOY 32–DOY 120) from 2003 to 2012 based on MODIS NDVI products for this period for Ireland. The average rate of grass growth is determined locally as a simple linear model for each pixel, using only the highest quality data for the period. These decadal spring growth model coefficients, start of season cover and growth rate, are regressed against log of stocking rate (r2 = 0.75). This model stocking rate is used to map grassland use intensity in Ireland, which, when tested against an independent set of stocking rate data, is shown to be successful with an RMSE error of 0.13 for a range of stocking densities from 0.1 to 3.0 LSU/Ha. This model provides the first validated high resolution approach to mapping stocking rates in intensively managed European grassland systems. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80044
Appears in Collections: 气候变化事实与影响
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作者单位: Teagasc, Ashtown, Dublin, Ireland; Dept. of Geography, NUI, University College, Cork, Ireland; EurOcean, Avenida D. Carlos I, 126-2°, Lisbon, Portugal
Recommended Citation:
Green S,, Cawkwell F,, Dwyer E. Cattle stocking rates estimated in temperate intensive grasslands with a spring growth model derived from MODIS NDVI time-series[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,52