期刊
ROYAL SOCIETY OPEN SCIENCE
卷 4, 期 2, 页码 -出版社
ROYAL SOC
DOI: 10.1098/rsos.160443
关键词
vegetation patterns; morphology; morphometrics; ecohydrology; computational vision
资金
- Marie Curie International Incoming Fellowship within the 7th European Community Framework Programme [PIIF-GA-2012-328245]
- National Science Foundation [NSF DMS-1418007, NSF DBI-1262351]
- Royal Society Wolfson Research Merit Award
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1262351] Funding Source: National Science Foundation
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1418007] Funding Source: National Science Foundation
Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.
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