DTM Quality assessment

Goals• 1- To explain procedures for quantitative assessment of bare-earth DTMs. (to ensure about accuracy)• 2- To explain procedures for qualitative assessment of bare-earth DTMs. (to ensure about usability)

Definitions•Quality Assurance (QA):• Step token to ensure the end client receives the quality

products it pays for, consistent with the scope of work or to ensure an organization’s Quality Program works effectively.

•Quality Control (QC):• Steps token by data producers to ensure delivery of

products that satisfy standards, guidelines and specifications identified in the Scope of work.

Standards and Guidelines

ASPRS

NSSDA

FEMA

NDEP

NSSDA (National Standard for Spatial Data Accuracy)• The NSSDA tests and reports the vertical accuracy of digital elevation data at 95 percent confidence level, but accuracy thresholds are defined by user requirements.•NSSDA often used independent source data with higher accuracy for testing data accuracy at 95 percent confidence level (called Tested), But when such data is not available used an alternative method (called Complied to Meet) for evaluating the accuracy.

FEMA (Federal Emergency Management Agency)• (FEMA 2003) establishes accuracy thresholds by requiring DEM data to have accuracies equivalent to 2-foot contours for flat area and 4-foot contours for hilly to mountainous.•Need at least 20 checkpoints for each major land cover.•We have 5 major land cover: (open terrain- weeds and crops- scrub and bushes- forested- built up areas)

NDEP (National Digital Elevation Program)• The NDEP mandates the use of “Fundamental Vertical Accuracy” (FVA) in open terrain, and provides for the optional use of “Supplemental Vertical Accuracy” (SVA) in other individual land covers and “Consolidated Vertical Accuracy” (CVA) in all combined land covers.

NDEP (National Digital Elevation Program)• FVA is calculated at 95% confidence level as a function of RMSE(Z) , SVA and CVA are calculated at 95% confidence level (for each check data, DEM checked ) if 95% of elevation errors equal or less than the RMSE in 95% confidence level.

NDEP (National Digital Elevation Program)• FVA:• Using check points in open terrain only:• 1- Compute vertical RMSE = • 2- Compute Accuracy = 1.96*RMSE• 3- Report FVA…

NDEP (National Digital Elevation Program)• SVA / CVA:• When testing individual or combined ground cover

excluding open terrain:• 1- Compute FVA (accuracy at 95% CL)• 2- Checking accuracy for each Check points.• 3- in Metadata, Document the errors lager than the 95%

CL. Report x, y and z error for small number of errors. For large number of errors above 95% CA report only the quantity and range of values.

ASPRS (American Society For Photogrammetry and Remote

Sensing)• FVA is assumed to be relevant standard if only a single accuracy is stated.• Check points should be selected on flat terrain, or on uniformly sloping terrain for x meters in all directions from each check point, where x is the nominal spacing of DEM or mass points evaluated.• Terrain slope should not be steeper than 20% because horizontal errors will unduly influence the vertical RMSE calculation.

Interpolation and Quality• Elevation of check points must be derived from data set and checked for blunders (Usually 3-sigma test). Exact procedures for obtaining these elevations will vary depending on the elevation data model.•We can use contours for Quality Control to ensure about accuracy after procedures like Interpolation, Generalization, or Smoothing.

Qualitative Assessment

Qualitative Assessment

Macro Level Micro Level

Macro Level Assessment•DEM are based on one of two data type (raster model or vector model), with both data types, visualization is a key component to reviewing data for qualitative purposes.•We can use tools to calculate descriptive statistics to provide benefits with minimal human intervention.

Micro Level Assessment• There are many ways and processed to review the data on a micro level to assess whether the data fulfills the client’s requirements.• In This level we find certain problems like :• Spikes (High points)• Anomalies (even we use hill shades of DEM to detect

anomalies)• Gap of Data• ….

Spikes (High points):

Thanks