A. Starling's GIS Blog

     Module 4 in Applications in GIS  focused on coastal flooding. For this week’s lab, we became familiar with procedures to assess coastal flooding and perform analysis on the differences between LiDAR and USGS data in application. First, we focused on the area of Mantoloking, New Jersey and how Hurricane Sandy (2012) impacted the area before and after the Category 1 storm event. We used data from NOAA for this. We used a Spatial ETL Tool to translate the .laz files that were downloaded from NOAA for the pre- and post- Sandy event into .las files. This helped us to start creating Digital Elevation Models (DEMs) of the before and after event data. Once we converted the .las files into TINs, we then used the TIN to Raster tool and used the Raster Calculator to determine the difference in erosion/accretion before and after Hurricane Sandy. Mantoloking, New Jersey coastal impact from Hurricane Sandy (2012) The red indicates erosion, while the blue indicates acc...

     This week in Applications in GIS focused on LiDAR (Light Detection and Ranging) and how to handle LiDAR data in ArcGIS Pro to calculate forest height and forest biomass. Using the decompressed version of the provided LiDAR data of the study area in Shenandoah, Virginia (Fig. 1), we created a Digital Elevation Model (DEM) and Digital Surface Model (DSM) to determine the tree canopy height of the study area. Fig. 1: LiDAR image of Shenandoah, Virginia study area Creating DEM Using the LiDAR .las file, right click in Contents -> Filters -> LAS Points = Ground The LAS Dataset to Raster geoprocessing tool was used to convert the LiDAR data into a raster format. This made a Digital Elevation Model (DEM). See Fig. 2 for this map output. Creating a DSM Using the LiDAR .las file, right click in Contents -> Filters -> LAS Points = Non-Ground The LAS Dataset to Raster geoprocessing tool was used to convert the LiDAR data into a raster format. This made ...