Quality Control & Standards in Photogrammetry Flashcards

What does the ASPRS 2014 standard use instead of the traditional NMAS 90% circular error to define accuracy?

Answer: RMSE-based accuracy with separate thresholds for horizontal (RMSEx, RMSEy) and vertical (RMSEz) components

ASPRS 2014 replaced the circular error approach with RMSE-based accuracy metrics, separately specifying RMSEx, RMSEy, and RMSEz thresholds that are tied to the product's GSD or contour interval.

What is the minimum number of independent check points recommended by ASPRS 2014 for a small project area (< 500 km²)?

Answer: At least 20 well-distributed independent check points

ASPRS 2014 recommends a minimum of 20 well-distributed independent check points for assessing accuracy on smaller project areas, ensuring statistical validity of the reported accuracy.

What is 'QA/QC' in the context of a photogrammetric mapping project?

Answer: Quality Assurance (process controls) and Quality Control (product inspection and testing) to ensure deliverables meet specifications

QA/QC encompasses Quality Assurance (systematic processes that prevent defects) and Quality Control (inspection and testing activities that detect and correct defects) in the production of photogrammetric deliverables.

What is a 'metadata report' required to accompany photogrammetric deliverables?

Answer: Documentation describing data acquisition parameters, processing methods, datum/projection, accuracy, and data quality information

Metadata reports document all relevant information about data acquisition and processing—including flight parameters, camera calibration, datum, projection, accuracy statistics, and lineage—enabling proper use and archiving of deliverables.

What is 'vertical datum' and why is it critical in photogrammetric elevation products?

Answer: The reference surface (e.g., NAVD 88, NGVD 29, ellipsoid) to which all elevations are referenced, determining how heights interoperate with other datasets

The vertical datum defines the reference surface (e.g., NAVD 88 in the US) to which all elevations are referenced; using an incorrect or undocumented datum causes systematic elevation offsets when data is integrated with other height information.

What is 'data completeness' as a dimension of geospatial data quality?

Answer: The degree to which all required features and attributes are present and correctly represented in the dataset

Data completeness measures whether all required features, objects, and attributes are present in the dataset without omissions or commissions, as specified by the product standard or project specification.