cgt_profile | R Documentation |
An implementation of the criminal geographic targeting model for serial crime analysis developed by DK Rossmo. This function applies Rossmo's distance decay formula to a series of suspected crime incidents for geographic profiling and prediction of perpetrator home base.
cgt_profile(lat, lon, buffer = NULL, f = NULL, g = NULL, n = NULL)
lat |
a vector of latitudes for the crime incident series |
lon |
a vector of latitudes for the crime incident series |
buffer |
the radius for the buffer zone assumed by the distance decay model. |
f |
decay formula coefficient which changes the steepness of the decay
curve after the buffer radius. If |
g |
decay formula coefficient which changes the steepness of the decay
curve before the buffer radius. If |
n |
total number of cells within the spatial grid for the jeopardy surface.
If |
A data frame of points depicting a spatial grid of the hunting area for the given incident locations. Also given are the resultant summed values (score) for each map point. A higher resultant score indicates a greater the probability that point contains the offender's anchor point.
Jamie Spaulding, Keith Morris
DK Rossmo (2000). Geographic profiling. Boca Raton, FL: CRC Press.
DK Rossmo (1995). Geographic profiling: Target patterns of serial murderers. Diss. Theses (School of Criminology)/Simon Fraser University.
#Using provided dataset for the Boston Strangler Incidents: data(desalvo) test <- cgt_profile(desalvo$lat, desalvo$lon) g_map = sp::SpatialPixelsDataFrame(points = test[c("lons", "lats")], data = test) g_map <- raster::raster(g_map) # Assign a Coordinate Reference System for the Raster raster::crs(g_map) <- sp::CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") # Define a Parula Color Pallete for Resultant Jeopardy Surface library(leaflet) #for mapping the geographic profile pal <- colorNumeric(pals::parula(200), raster::values(g_map), na.color = "transparent") leaflet() %>% addTiles() %>% addProviderTiles('Esri.WorldTopoMap', group = 'Topo') %>% addAwesomeMarkers(lng = -71.07357, lat = 42.41322, icon = awesomeIcons(icon = 'home', markerColor = 'green'), popup = 'Residence') %>% addRasterImage(g_map, colors = pal, opacity = 0.6) %>% addLegend(pal = pal, values = raster::values(g_map), title = 'Score') %>% addCircleMarkers(lng = desalvo$lon, lat = desalvo$lat, radius = 4, opacity = 1, fill = 'black', stroke = TRUE, fillOpacity = 0.75, weight = 2, fillColor = "red")
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