Local convex hull
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Described in Getz and Wilmers, LoCoH (Local Convex Hulls) is a method for generating utilization distributions (homeranges) that finds the UD by following a number of simple steps:
- Locate the k-1 nearest neighbors for each point in the dataset.
- Construct a convex hull for each set of nearest neighbors and the original data point.
- Merge these hulls together from smallest to largest.
- Divide the merged hulls into isopleths where the 10% isopleth contains 10% of the original data points, the 100% isopleth contains all the points, etc.
The LoCoH method has a number of strong points:
- It generates a density distribution denoting.
- As more data is added, the homerange because more accurate.
- It is handles 'sharp' features such as lakes and fences well.
- The generated homerange has a finite region.
LoCoH has a number of implementations including a LoCoH Web Application.
LoCoH was formerly known as k-NNCH, for k-Nearest Neighbor Convex Hulls.
References
Getz, W. and C. Wilmers. 2004. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27: 489-505. View PDF