ABSTRACT
This project was centered on the development of a 3D Urban GIS Database for the U.S. Army Research Development Engineering Command that would be used for the purposes of mapping and simulation-visualization. Spectrum's role was to physically collect (using its in-house LIDAR, Digital Camera and hyperspectral sensors), and develop the necessary source data required to construct a 3D urban database using real-time urban data. This data was developed using a data fusion approach in which LIDAR, Color-CIR Digital Camera and 63-band Hyperspectral data were integrated in order to acquire 3D urban feature data. This base terrain data and its associated feature objects were used as the input into the GIS and visualization models.
LIDAR data served as the terrain and (X,Y,Z) feature source information for most of the 3D Objects contained in the terrain database. This included bare-earth surface, building footprints, height and structure of vegetation and tree cover, roads, and localized sign and street light infrastructure. All features were extracted as LIDAR point data and then transformed into their appropriate terrain formats (GeoTIFF, polygon, point, line shape files). The 0.5-ft to 1.0-ft resolution Color / CIR Digital Orthophotography served as the geo-coordinate base for the terrain database, due to its highly accurate geopositional characteristics, and was used as the base (RGB) drape-overlay layer for the visualization model. The hyperspectral imagery served as the source platform for feature attribution that will be derived using automated spectral analysis techniques (spectral curves-matching and feature space mapping techniques). All hyperspectral pixels were geolocated to their corresponding LIDAR point data, giving each point an identifiable material class to be used in the visualization construction process. The hyperspectral data was also used to generate an overall land cover map, which will provide feature class names and material class attribute for all surface features contained within the project area. Extracted features included: spectral characteristics of buildings, roads; water bodies; water networks; wetlands; agricultural classes, and tree types.
Two primary study areas were used in the project: Los Lunas, New Mexico and Commerce City, Denver Colorado. All resultant data, images and terrain models were input into the ArcGIS version 9.0 environment for display, query and product output.
As part of the work with RDECOM (U.S. Army Research and Development Command), Spectrum generated two project study areas from which earth surface features were to be extracted for use in a prototype urban visualization database. The study areas sued were as follows:
- Los Lunas, New Mexico Urban-Rural test site
- Commerce City-Denver, Colorado test site
Each test site was selected for its unique urban characteristics, where urban features were to be extracted using a fusion sensor and dataset approach. The sensors used in this study included:
- Spectrum RAMS LIDAR
- RAMS Color Digital Camera
- SPECTIR Hyperspectral Imager
From the above sensor Spectrum provided a prototype urban database that could be imported into the Terrex visualization software with its associated descriptive database attributes. Each test site was run through the same process for data preprocess, feature extraction and analysis and creation of product deliverables. Several lessons learned were also established that primarily had to do with the feature extraction of residential homes and the characterization in hyperspectral feature space of urban rooftops