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The Long Term Resource Monitoring Program An element of the Upper Mississippi River Restoration - Environmental Management Program Light Detection And Ranging (LiDAR) Elevation Data

Resource Mapping and Spatial Analysis

LiDAR is acquired using laser and light sensors mounted in aircraft. The units perform vertical sweeps of the ground below, painting the surface with thousands of laser pulses per second. The pulse’s reflection is calculated by time sent/received and by return intensity. LiDAR can accurately generate cells of a meter or less and support creation of two-foot contours. Horizontal accuracy of spot elevations are sub-meter and vertical accuracy of spot elevations are typically six-inches or better. Sensors can receive multiple returns and be processed to describe heights of overstory and understory vegetation and bare earth. By using all returns, forest stand height and density can be calculated. The most common use is expected to be detailed digital elevation models (DEMs) of the floodplain using the bare earth returns.

LiDAR postings showing bare earth heights.

DEMs are constructed from text-based XY (horizontal) and Z (vertical) coordinates. From these values, contours and triangular irregular networks (TINs) can be generated for use in models and habitat analyses. The Upper Midwest Environmental Sciences Center (UMESC) has been working with LiDAR data for nearly a decade and has established itself as a leader in LiDAR processing. From LiDAR data, UMESC plans to serve pool-based UMRS elevation products (DEMs, TINs, contours, hillshades, etc.) via its website for the Upper Mississippi River Restoration–Environmental Management Program and its Long Term Resource Monitoring Program (LTRMP). LiDAR data is currently being served at two levels of processing, known as “Tier 1” and “Tier 2”. Tier 1 is processed directly from vendor-provided LAS files and is not cleaned or edited in order to serve the data as quickly as possible. Tier 1 data has been quality checked by the vendor and obvious blunders are removed but some isolated errors remain, typically points that have been misclassified. Tier 1 data has not had water masked or flattened, nor have contours been smoothed. Tier 2 data performs water-masking, contour-smoothing, point-reclassification where necessary and performs an additional quality control phase, as defined below. Once all LiDAR products have undergone Tier 2 processing, Tier 1 products will be removed.

Tier 2 processing includes:

1. masking of water - also referred to as flattening, is assigning a single elevation value to a body (or section) of water to produce a more esthetically pleasing DEM. Since water absorbs most of the LIDAR signal, there are very few elevation points on water surfaces, generating large, but essentially flat, triangles as those surface and shoreline points are tied together. Masking eliminates these small differences by creating a completely flat surface.
    
2. smoothing of contours - this is another step that improves the visual appearance of elevation data. Since contour lines are straight lines interpolated from, in our case, 1-m DEM horizontal cells at a predefined vertical increment (0.5m for LTRMP), they can appear very jerky at resolutions this detailed. Smoothing sacrifices a small amount of precision to improve the overall visual quality of the contour lines data set. Additional benefits of smoothing include a size reduction of contour data sets since the number of vertices are greatly reduced, making the data easier to display and analyze on a computer.
    
3. reclassifying of data errors - this error shows up primarily along edge ties and in missing features such as small islands. Occasionally data in transition zones may be classified as vegetation or land on one tile and water on the adjacent tile so that there appears to be an unnatural straight line between tiles when displaying these data by class. Also, small islands maybe lost when areas are broadly classified as water. Using background imagery to reclassify these types of errors will improve the accuracy of the final product. 
   
   
4. additional quality assurance/quality control assessment - the best way to catch classification errors is by a focused review at the tile level using both hillshades and the highest resolution background imagery available. Anomalies can be either noted and repaired in the reclassification process or, if systemic, brought to the attention of the vendor.

While some information needs can be met by using the individual LiDAR derivatives, an integrated database for LiDAR and bathymetry is required in some cases. For example, hydrodynamic models used to predict flow and inundation have until now been limited to predictions in low water conditions. Other examples are information on near-shore habitat use by water birds, fish spawning and marshland vegetation. Using specialized Geographical Information System (GIS)-software and high-speed computer processors, it is now possible to merge LiDAR and bathymetric data into a seamless GIS layer. These seamless elevation layers, limited initially to Pools 4-5, 7-10, 13, and 21, will be classified as Tier 3 products.

All LiDAR products generated by UMESC are available for download on the data download pages.

Examples of LiDAR products are shown below.

 LiDAR (Light Detection And Ranging) data are remotely sensed, high-resolution elevation data collected by airplane. The Upper Midwest Environmental Sciences Center processed these data to create Digital Elevation Models (DEMs), 0.5 meter contour lines, and pool-wide hillshade images. Tier 2 processing has been completed for this pool. This process include water-masking, contour-smoothing, point reclassification, where needed, and additional quality control steps. The collection and processing of these data were funded by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration–Environmental Management Program and its Long Term Resource Monitoring Program (LTRMP).

Impact of UMESC Science

High-resolution elevation derivatives, such as those generated from LIDAR data, are useful for many reasons – flow, inundation, and run-off model building, habitat project design and evaluations, floodplain forest height and density information, connectivity analyses, and seamless 3-D model generations by pool or reach to name a few. LiDAR data will also assist in the development of LCU products by informing botanists and GIS specialists about floodplain vegetation's slope, aspect, and elevation above the water table.

Point of Contact: Jennifer Dieck

Disclaimer: Tier 1 LiDAR data available on this site are currently undergoing quality assurance testing by the U.S. Geological Survey (USGS). While this testing is underway, these data are being provided as-is, with no guarantee of accuracy. Tier 2 LiDAR data have gone through quality assurance testing and have been approved for release by the USGS. Although Tier 2 data have been subjected to rigorous review and are substantially complete, the USGS reserves the right to revise these data pursuant to further analysis and review. Furthermore, Tier 1 and Tier 2 data are released on condition that neither the USGS nor the United States Government may be held liable for any damages resulting from their authorized or unauthorized use.