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1. Get DSM raster data

data <- dsmSearch::get_dsm_30(bbox = c(-83.783557,42.241833,-83.696525,42.310420), key = "Your KEY")

2. Get LiDAR data

2.1 Get LiDAR data information via API

# search for lidar data information using bbox
search_result <- dsmSearch::lidar_search(bbox = c(-83.742282,
                                                  42.273389,
                                                  -83.733442,
                                                  42.278724), 
                                         preview = FALSE)
search_result

2.2 Download LiDAR data with a given point and searching distance

# try coordinates -83.741289,42.270146 (in south Michigan, USA)
# radius is 1000ft
las <- dsmSearch::get_lidar(x = -83.741289,
                            y = 42.270146,
                            r = 1000,
                            epsg = 2253)
# download with bbox
las <- dsmSearch::get_lidar(bbox = c(-83.742282,42.273389,-83.733442,42.278724),
                            epsg = 2253)
# Create DTM
dtm_ <- lidR::rasterize_terrain(las, res = 5, lidR::tin())
terra::plot(dtm_)
# Create DSM
dsm_ <- lidR::rasterize_canopy(las, res = 5, lidR::dsmtin())
raster::plot(dsm_)

For more usages of lidR please refer: https://github.com/r-lidar/lidR/tree/master and https://rpubs.com/jesseast/lidR4smarties

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.