calculate_area_intersection_weights: Area Weighted Intersection

In USGS-R/ncdfgeom: 'NetCDF' Geometry and Time Series

Area Weighted Intersection

Description

Returns the fractional percent of each feature in x that is covered by each intersecting feature in y. These can be used as the weights in an area-weighted mean overlay analysis where x is the data **source** and area- weighted means are being generated for the **target**, y.

This function is a light weight wrapper around the functions aw_intersect aw_total and aw_weight from the areal package.

Usage

calculate_area_intersection_weights(x, y, normalize, allow_lonlat = FALSE)

Arguments

x	sf data.frame source features including one geometry column and one identifier column
y	sf data.frame target features including one geometry column and one identifier column
normalize	logical return normalized weights or not. Normalized weights express the fraction of **target** polygons covered by a portion of each **source** polygon. They are normalized in that the area of each **source** polygon has already been factored into the weight. Normalized weights are intended to be used with _intensive_ variables. Un-normalized weights express the fraction of **source** polygons covered by a portion of each **target** polygon. This is a more general form that requires knowledge of the area of each **source** polygon to derive area-weighted statistics from **source** to **target. Un-normalized weights are intended to be used with either _intensive_ or _extensive_ variables. See details and examples for more regarding this distinction.
allow_lonlat	boolean If FALSE (the default) lon/lat target features are not allowed. Intersections in lon/lat are generally not valid and problematic at the international date line.

Details

Two versions of weights are available:

'normalize = FALSE', if a polygon from x (source) is entirely within a polygon in y (target), w will be 1. If a polygon from x (source) is 50 and 50 in each. Weights will sum to 1 per **SOURCE** polygon if the target polygons fully cover that feature.

For 'normalize = FALSE' the area weighted mean calculation must include the area of each x (source) polygon as in:

> *in this case, 'area' is the area of source polygons and you would do this operation grouped by target polygon id.*

> 'sum( (val * w * area), na.rm = TRUE ) / sum(w * area)'

If 'normalize = TRUE', weights are divided by the target polygon area such that weights sum to 1 per TARGET polygon if the target polygon is fully covered by source polygons.

For 'normalize = FALSE' the area weighted mean calculation no area is required as in:

> 'sum( (val * w), na.rm = TRUE ) / sum(w)'

See examples for illustration of these two modes.

Value

data.frame containing fraction of each feature in x that is covered by each feature in y.

Examples

library(sf)

source <- st_sf(source_id = c(1, 2), 
                val = c(10, 20), 
                geom = st_as_sfc(c(
  "POLYGON ((0.2 1.2, 1.8 1.2, 1.8 2.8, 0.2 2.8, 0.2 1.2))", 
  "POLYGON ((-1.96 1.04, -0.04 1.04, -0.04 2.96, -1.96 2.96, -1.96 1.04))")))

source$area <- as.numeric(st_area(source))

target <- st_sf(target_id = "a", 
                geom = st_as_sfc("POLYGON ((-1.2 1, 0.8 1, 0.8 3, -1.2 3, -1.2 1))"))

plot(source['val'], reset = FALSE)
plot(st_geometry(target), add = TRUE)

(w <- 
calculate_area_intersection_weights(source[c("source_id", "geom")], 
                                    target[c("target_id", "geom")], 
                                    normalize = FALSE, allow_lonlat = TRUE))

(res <-
merge(st_drop_geometry(source), w, by = "source_id"))

(intesive <- sum(res$val * res$w * res$area) / sum(res$w * res$area))
(extensive <- sum(res$val * res$w))

(w <-
calculate_area_intersection_weights(source[c("source_id", "geom")], 
                                    target[c("target_id", "geom")], 
                                    normalize = TRUE, allow_lonlat = TRUE))
(res <-
merge(st_drop_geometry(source), w, by = "source_id"))

(intensive <- sum(res$val * res$w) / sum(res$w))

USGS-R/ncdfgeom documentation built on June 8, 2025, 4:16 a.m.