LiDAR Terrain Analysis and Change Detection from Above
Terrain change detection, cut and fill volume estimation, terrain profiling, reclamation monitoring, and erosion analysis from LiDAR point clouds and DEMs. Built on ‘lidR’ for point cloud I/O and ‘terra’ for raster operations. Includes utilities for ‘KyFromAbove’ LiDAR data access.
# Install from CRAN (when available)
install.packages("aboveR")
# Or install the development version from GitHub
# install.packages("pak")
pak::pak("chrislyonsKY/aboveR")library(aboveR)
# Load bundled sample DEMs
before <- sample_data("dem_before")
after <- sample_data("dem_after")
# Detect terrain changes between two epochs
change <- terrain_change(before, after)
terra::plot(change[["change"]], main = "Elevation Change (m)")reference <- sample_data("dem_reference")
boundary <- sample_data("boundary")
vol <- estimate_volume(after, reference, boundary)
cat(sprintf("Cut: %.0f m³ | Fill: %.0f m³ | Net: %.0f m³\n",
vol$cut_volume, vol$fill_volume, vol$net_volume))zones <- sample_data("zones")
summary <- change_by_zone(change, zones, id_field = "zone_id")
print(summary[, c("zone_id", "mean_change", "cut_volume", "fill_volume")])line <- sample_data("profile_line")
prof <- terrain_profile(before, line)
plot(prof$distance, prof$elevation, type = "l",
xlab = "Distance (m)", ylab = "Elevation (m)",
main = "Terrain Profile")roughness <- surface_roughness(after, window = 5)
terra::plot(roughness, main = "Surface Roughness (Std Dev)")# Access Kentucky statewide LiDAR (requires network)
library(sf)
aoi <- st_point(c(-84.5, 38.0)) |>
st_sfc(crs = 4326) |>
st_buffer(1000)
tiles <- kfa_find_tiles(aoi, phase = 2)
dem <- kfa_read_dem(tiles$tile_id[1], phase = 2)MIT