Multidimensional Data Modeling for Feature Extraction and Mapping ACSM April 19, 2004 Multidimensional Data Modeling for Feature Extraction and Mapping E. Lynn Usery usery@usgs.gov http://mcmcweb.er.usgs.gov/carto_research

Outline Motivation Objectives Approach Theoretical Model Implementation Scale Dependent Feature Rendering Conclusions

Motivation Conventional GIS model the world in two-dimensions with a map model and geographic features dependent on geometry for definition This map model limits three-dimensional and temporal analysis, and multidimensional, multi-scale representations Cognition studies indicate that humans perceive the geographic world as a set of definable entities with spatial, thematic, and temporal attributes associated

Objectives Provide a theoretical model based on feature orientation Develop the model to support unique entities with spatial, thematic, and temporal attributes and relations for each feature instance Implement the model in a feature library and use the library for feature extraction to support The National Map

Approach Implement the theoretical feature model in an object-oriented library Develop feature instances for 20 specific features that are relevant to The National Map Develop attributes and relationships including multiple representations (raster and vector) of attributes for each feature instance Determine the extraction capability of each feature from various image sources

Feature Model Feature is geographic entity and object representation One feature, many objects Multiple resolutions Multiple geometries Access from single identity

Definitions Feature - A set of phenomena with common attributes and relationships. The concept of feature encompasses both entity and object. Entity - A real-world phenomenon that cannot be subdivided into phenomena of the same kind. Object - A digital representation of all or a part of an entity. Attribute - Characteristic of a feature or of an attribute value. Relationship - Linkage between features or objects. Feature instance - An occurrence of a feature defined by a unique set of attributes and relationships.

Databases Supporting Feature Extraction and Map Generation Feature Attributes and Relationships Image Image Chips Spectral Responses Digital Number Ranges for Multimodal Images Map Symbol Specifications Symbol Chips Inclusion Criteria

Feature Library Implementation

Multiple Feature Instance Example with Actual Data

Feature Instance Implementation with Actual Water Quality Data

Relationship Implementation from NHD

Time Attribute Implementation

National Map Feature Extraction Camp Lejeune study site 20 features selected All attributes and relationships built based on DLG-E specifications Image chips extracted for storage as attributes Spectral responses determined (laboratory and from images)

Table of the 20 Features Type Features Point (5) Helipad, Rock, Tank, Tower, Wreck Line (6) Bridge, Road, Shoreline, Stream/River, Trail, Transmission Line Polygon (9) Aircraft Facility, Apron/Taxiway, Building, Lake/Pond, Parking Site, Pier/Breakwater/Jetty, Shrub Land, Swamp/Marsh, Trees

Airport -- DOQ

Airport – Ikonos Pan

Airport – Ikonos Pan-sharpened

Airport – Ikonos MX

Airport – SPOT Pan

Airport – CIR Photo

Trail – DOQ

Trail – Ikonos Pan

Trail – Ikonos Pan-sharpened

Trail – Ikonos MX

Trail – SPOT

Trail – CIR Photo

Trail – Color Photo

Airport Map Symbol

Trail Map Symbol

Geodatabase for the Study Area in ArcCatalog

Airport Feature

The Study Area – Camp Lejeune, NC

Scale Dependent Renderer

Trees on 1:30,000-Scale Map Trees on small scale map.

Trees on 1:9,000-Scale Map Trees on large scale map.

Buildings Rendered as Polygons 1:5,000-Scale Map Building rendered as polygon at scale larger than 1:10,000

Buildings Rendered as Polygons/Points Based on the Longest Axis -- 1:12,000-Scale Map Building rendered as polygon or point based on the length at scale range 1:10,000-1:25,000

Buildings Rendered as Points on 1:28,000-Scale Map Building rendered as points at scale range 1:25,000-1:50,000

Buildings Not Displayed on 1:55,000- Scale Map Building is not displayed at scale smaller than 1:50,000

Conclusions A theoretical model of features existing in the real world as single geographical entities has been developed This model shows promise for implementing feature extraction methods and scale-dependent rendering for The National Map Probabilities for extracting specific features from multimodal sources can be developed based on feature attributes and relationships and appearance in various image sources

Multidimensional Data Modeling for Feature Extraction and Mapping ACSM April 19, 2004 Multidimensional Data Modeling for Feature Extraction and Mapping E. Lynn Usery usery@usgs.gov http://mcmcweb.er.usgs.gov/carto_research