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Susan Smith
Susan Smith
Susan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’ … More »

Flood modeling data with Intermap Digital Elevation Models and Hydrology

July 3rd, 2012 by Susan Smith

In a webcast presented by Carahsoft, Intermap representatives talked about the fact that they have “the world’s largest 3D terrain database with the one meter LE 90 accuracy and consistency.” LE 90 is a linear air of 90 percent, and is commonly used for quoting and validating DEMs. LE 90 value represents the linear vertical distance of  90 percent of control points, and the respective twin matching counterparts acquired in an independent geodetic survey should be found from each other. For the U.S., which most on this call is interested in, Intermap has mapped the entire lower 48 plus some of Alaska.

Along with Intermap’s NEXTMap 5 meter data they’re also releasing NEXTMap 30 meter DSM which covers the entire globe. NEXTMap 30 DSM is characterized by a 30 meter ground sampling distance (GSD) seamless best of breed and possesses a range of accuracy starting at 5 millimeter LE 90 and bearing terrain of low slope.

Intermap employs a unique system to filter the IFSAR data to remove cloud and vegetation elevation and obtain a set of survey grade reference points. An image of Intermap’s IFSAR technology is created to show the NEXTMap data set in a nutshell. The data is collected from a fixed wing aircraft equipped with IFSAR which can operate day or night in clear or cloudy conditions virtually anywhere at any time. Height information is obtained in a single pass mode by using the phased difference between two coherent IFSAR images simultaneously obtained by two antennae separated by a cross track baseline.

In order to determine what dataset you need for a project, ask yourself about your budget, and how accurate does data need to be? Is your flood model going to be in the city, rural area, or both? If you’re using Lidar do you have coverage for entire area of interest, and is the data currency something that is important to you?

Flood modeling data suitability

DTMS vs DSM :  Artifact removal is dependent on the source, and some DEMs or DTMS have vegetation or buildings in them. NEXTMap data is completely removed and a human actually went in and QC’d it to make sure all artifacts are removed. SPOT, ASTER and SRTM are some of the best data where there are no fly zones, and there are large areas available for these datasets.

However, your flood model is only as good as the data put in. This means that your flood model with these kinds of revolutions such as 30 and 90, whether its high urbanizations or future development, can greatly change the outcome if there is a major flood. IFSAR is used in cities due to the size of radar characteristics and certain terrain conditions for shortening layover and shadowing affect the data. The Lidar benefits are high vertical accuracy and fast data collection, where it should be used is for detailed study analysis for flooding, especially using or creating deforms for FEMA, urban core design projects, small projects and when funds are plentiful for larger projects. Lidar creates lot of details in cities, whereas the other datasets can be lacking in these areas.

ASTER digital elevation model compared to the NEXTMap World 30 (right).

Ths USGS undertook the massive task of mapping the entire US. It’s consistently being updated. USGS topography quads make an excellent reference source, however, topography maps were never intended for flood modeling.

Elevation data makes a big difference when making stream center lines. Use the same process on all sides of the dataset. NED or National Elevation Dataset  offers a 10 meter centerline – a lot more details on this dataset compared ASTER and others. The NEXTMap stream centerlines covers more detail than NED or Aster. Lidar flown in 2008 can see quite complex stream centerlines. However, the processing time for this was double what it was for the stream centerlines done with NEXTMap data.

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Categories: Intermap, remote sensing, satellite imagery

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