VOLUME 72, NUMBER 5
PHOTOGRAMMETRIC ENGINEERING & REMOTE
SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY
AND REMOTE SENSING
This month’s cover image is provided by GeoCue Corporation (formerly NIIRS10),
the Huntsville, Alabama-based company that has developed GeoCue, a family of geospatial workfl ow
management tools. The cover image depicts a production fusion view of a department of transportation
corridor mapping project in Ashtabula County, Ohio. Data included in the project are USGS DEM, lidar, LMK
frame imagery and Applanix DSS imagery. The entire project is superimposed on a USGS digitized quad
sheet for context. The frame images in the lower right
are in-process digital ortho photos being created by
the new Leica Ortho Accelerator system, an enterprise
ortho production system jointly developed by
GeoCue Corp. and Leica Geosystems. Superimposed
on the orthos is a lidar delta Z (dZ) image generated
in the Lidar 1 CuePac. The dZ images are used to assess
the relative vertical accuracy of lidar point data.
The narrow band of images appearing from under
the orthos and tracking the highway corridor toward
the right are elevation visualization images produced
in the DEM CuePac from LIDAR point cloud data.
This composite illustrates a new production fusion
paradigm for geospatial processing.
All data courtesy of the Ohio Department of
Transportation.
For more information please visit www.geocue.
com or contact Lewis Graham at 256-461-8289.
Announcements
497 PE&RS Special Issue Call for Papers — Remote Sensing Data Fusion
498 PE&RS Special Issue Call for Papers — Web and Wireless GIS
563 ASPRS/MAPPS Specialty Conference— Measuring the Earth
- Latest Developments with Digital
Surface Modeling and Automated
Feature Extraction
A method for feature analysis, segmentation, and indexing
for region-based management, retrieval, and data-mining of
large, high-resolution geospatial libraries.
As an extension to stereo mapping, a 3D mapping approach
which can utilize multiple images was implemented, and its
benefit was assessed in representative case studies and in
comparison to common 3D stereo mapping.
Quality analysis and theoretical limits of selected image fusion
methods with special attention to the spectral sensitivity
analysis and preservation of spectral (color) and spatial information
from Ikonos, QuickBird, and Landsat images.
Hyperspatial Ikonos imagery analyzed with a fusion of pixelbased
species classifi cation, automated image segmentation
techniques to define vegetation patch boundaries, and vegetation
community classification using querying of the species
classification raster based on existing and novel rulesets.
A comparison of 3D physical and empirical models for stereo-processing and the generation of digital surface models
from different stereo, high-resolution sensors: Ikonos and
QuickBird.