Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1088/1748-9326/aacc7a |
Combining satellite data and agricultural statistics to map grassland management intensity in Europe | |
Estel, Stephan1; Mader, Sebastian2; Levers, Christian1; Verburg, Peter H.3,5; Baumann, Matthias1; Kuemmerle, Tobias1,4 | |
2018-07-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS |
ISSN | 1748-9326 |
出版年 | 2018 |
卷号 | 13期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Netherlands; Switzerland |
英文摘要 | The world's grasslands, both natural and managed, provide food and many non-provisioning ecosystem services. Although most grasslands today are used for livestock grazing or fodder production, little is known about the spatial patterns of grassland management intensity, especially at broad geographic scales. Using the European Union as a case study, we mapped mowing frequency as a key indicator of grassland management intensity. We used MODIS NDVI time series from 2000-2012 to map mowing frequency using a spline-fitting algorithm that detects up to five mowing events within a single growing season. We combined mowing frequency maps with existing maps of livestock distribution and grassland management frequency to identify clusters of similar grassland management intensity across Europe. Our results highlight generally high mowing frequency in areas of high grassland productivity, especially in Ireland, northern and central France, and the Netherlands. Our analyses also show distinct clusters of similar grassland management, representing different grassland-management intensity regimes. High intensity clusters occurred particularly in western and southern Europe, especially in Ireland, in the northern and central parts of France and Spain, and the Netherlands but also in northern and southern Germany and eastern Poland. Low intensity clusters were found mainly in central and eastern Europe and in mountainous regions but also in Extremadura in Spain, Wales and western England (UK). Generally, our analyses emphasize the usefulness of jointly using satellite time series and agricultural statistics to monitor grassland intensity across broad geographic extents. Our maps allow for a new, spatially-detailed view of management intensity in grassland systems and may help to improve regionally targeted land-use and conservation policies. |
英文关键词 | livestock distribution MODIS NDVI time series mowing frequency self-organizing maps |
领域 | 气候变化 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000437771900002 |
WOS关键词 | LAND-USE INTENSITY ; MODIS TIME-SERIES ; FARMLAND ABANDONMENT ; SPATIAL-DISTRIBUTION ; PASTURE MANAGEMENT ; SWISS MOUNTAINS ; CHALLENGES ; AREA ; INTENSIFICATION ; CONSERVATION |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/34311 |
专题 | 气候变化 |
作者单位 | 1.Humboldt Univ, Geog Dept, Linden 6, D-10099 Berlin, Germany; 2.Trier Univ, Fac 6, Environm Remote Sensing & Geoinformat, Geog Earth Sci, D-54286 Trier, Germany; 3.Vrije Univ Amsterdam, Dept Earth Sci, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands; 4.Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Linden 6, D-10099 Berlin, Germany; 5.Swiss Fed Res Inst WSL, Birmensdorf, Switzerland |
推荐引用方式 GB/T 7714 | Estel, Stephan,Mader, Sebastian,Levers, Christian,et al. Combining satellite data and agricultural statistics to map grassland management intensity in Europe[J]. ENVIRONMENTAL RESEARCH LETTERS,2018,13(7). |
APA | Estel, Stephan,Mader, Sebastian,Levers, Christian,Verburg, Peter H.,Baumann, Matthias,&Kuemmerle, Tobias.(2018).Combining satellite data and agricultural statistics to map grassland management intensity in Europe.ENVIRONMENTAL RESEARCH LETTERS,13(7). |
MLA | Estel, Stephan,et al."Combining satellite data and agricultural statistics to map grassland management intensity in Europe".ENVIRONMENTAL RESEARCH LETTERS 13.7(2018). |
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