Local Convex Hull (LoCoH) — Standard
Summary
Estimates an animal's home range and utilization distribution by the Standard (fixed-k) Local Convex Hull method of Getz and Wilmers (2004): every location's local hull is the convex hull of that point and its k − 1 nearest neighbors. Hulls are sorted by area from smallest to largest and merged cumulatively into density isopleths — the 95% isopleth approximates the home-range boundary while excluding outlying excursions. Outputs are the dissolved cumulative isopleths and, optionally, the individual hulls.
How k shapes the hulls
k counts the points in each hull, including the focal point itself — so each hull is a point plus its k − 1 nearest neighbors, and k must be at least 3 (the smallest hull that can be a polygon) and no greater than the number of points. Small k produces tighter, more fragmented hulls that capture fine structure and hard boundaries — rivers, cliffs, habitat edges — while large k produces smoother, more contiguous ranges; k equal to the number of points reduces to the minimum convex polygon.
Choosing k. Getz et al. (2007) suggest k = √n as a starting value — about 10 for a hundred locations. From there, the minimum spurious hole covering rule guides refinement: pick the smallest k that fills the holes you judge spurious, keeping the real ones. Plotting isopleth area against k across a handful of runs shows where the area levels off — and begins to over-inflate — which is the empirical procedure the T-LoCoH package recommends (Lyons, Turner and Getz 2013). You do not have to build those runs by hand: our LoCoH Parameter Explorer window sweeps k across a range of values in one click and charts the 50%, 75% and 95% isopleth areas against it, with k₁ = √n marked — run it first, then bring the k it suggests to this tool. Screen out obvious location errors first; LoCoH is sensitive to outliers.
What you get
The primary output holds the dissolved cumulative isopleths: each feature stores its dissolved area (Area), the number of input points it encloses (Point_Count), the proportion of all points (Point_Proportion), and the point density in points per square kilometer (Pts_per_SqKm) — the feature nearest 0.95 is the conventional home range, the one nearest 0.50 the core areas. The optional second output holds the individual local hulls, each with its own area, its own point count (always k) and proportion, and its own point density. Geographic inputs use Haversine distances and WGS84 spheroidal areas; projected inputs use planar measures. Area is in square meters for geographic inputs and in square map units for projected inputs. The Output Coordinate System environment is honored for the final polygons.
A tour of the dialog
A run needs the points, k, and an output name for the cumulative isopleths; the individual hulls are one optional output more.
ModelBuilder
Both outputs chain onward in a model — the isopleth polygons feed clip, overlay, or reporting steps directly, and a Select on Point_Proportion pulls the 95% or 50% isopleth out of the stack for the next tool.
Parameters
| Label | Explanation | Data type |
|---|---|---|
| Input point featuresRequired · in_features | The point features (GPS or VHF telemetry fixes, for example) the local hulls are built from. Geographic or projected; empty geometries are ignored. Every point of a multipoint feature is used. | Feature Layer |
| Number of nearest neighbors (k)Required · k | Points per hull, including the focal point — each hull is a point plus its k−1 nearest neighbors. At least 3, at most the number of points. | Long |
| Cumulative LoCoH [Standard] HullsRequired · out_isopleths | The dissolved cumulative isopleths, each with Area, Point_Count, Point_Proportion, and Pts_per_SqKm. | Feature Class |
| Output individual hulls (optional)Optional · out_hulls | The individual local convex hulls, each with its own area, point count, proportion and density. | Feature Class |
Python
A 10-neighbor Standard LoCoH with both outputs:
import arcpy
arcpy.ImportToolbox(r"C:\path\to\JennessEnterprisesTools.pyt") # your install path
arcpy.jenness.LoCoHStandard(
in_features=r"D:\data\telemetry.gdb\owl_fixes",
k=10,
out_isopleths=r"D:\data\telemetry.gdb\owl_isopleths_k10",
out_hulls=r"D:\data\telemetry.gdb\owl_hulls_k10")
Recommended citation
Credits and references
By Jeff Jenness, Jenness Enterprises (www.jennessent.com), implementing the fixed-k LoCoH method of Getz and Wilmers. Full references on the About LoCoH page.
- Getz, W. M., and C. C. Wilmers. 2004. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27:489–505. doi.org/10.1111/j.0906-7590.2004.03835.x
- Getz, W. M., S. Fortmann-Roe, P. C. Cross, A. J. Lyons, S. J. Ryan, and C. C. Wilmers. 2007. LoCoH: nonparametric kernel methods for constructing home ranges and utilization distributions. PLoS ONE 2(2):e207. doi.org/10.1371/journal.pone.0000207
- Lyons, A. J., W. C. Turner, and W. M. Getz. 2013. Home range plus: a space-time characterization of movement over real landscapes. Movement Ecology 1:2. doi.org/10.1186/2051-3933-1-2
Licensing information
Works at every ArcGIS Pro license level (Basic, Standard, Advanced). No extension licenses are required.
Related tools and pages
- About LoCoH home-range analysis — the shared theory.
- LoCoH (Adaptive) — a cumulative distance budget instead of a fixed count; adapts best when fix density varies strongly.
- LoCoH (Fixed Sphere) — a fixed radius, when a biologically meaningful distance should set the scale.
- LoCoH Parameter Explorer — sweep the parameter and chart the leveling-off curves before committing to a value.
- Concave Hull — one clean footprint polygon instead of a utilization distribution.