VOLUME 75, NUMBER 3
PHOTOGRAMMETRIC ENGINEERING & REMOTE
SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY
AND REMOTE SENSING
This month’s cover image highlights the variety of datasets produced by,
the PAMAP Program. The PAMAP team uses GeoCue
Corporation’s Distributed Project Management System
(DPMS) to coordinate production, acceptance testing,
and delivery of the nearly 54,000 lidar deliverables. From
top left, downtown Pittsburgh is depicted with: (a) 1-foot
pixel digital orthophotography; (b) 3.2-foot pixel bareearth
Digital Elevation Model; (c) 2-foot contour lines;
(d) contour enhancement/lidar processing breaklines;
and (e) 3-D rendering of the lidar point cloud. The lower
right image illustrates the tracking of workfl ow steps in
DPMS for PAMAP tiles in the southwest region of the
state. PAMAP is a seamless, consistent, high-resolution
suite of digital orthophotography, lidar-derived elevation
products, and other geospatial datasets covering
Pennsylvania. PAMAP is a program of the Bureau of
Topographic and Geologic Survey (BTGS) at the Pennsylvania
Department of Conservation and Natural Resources,
and managed by the Center for Environmental Informatics
at The Pennsylvania State University. For additional
information, please contact: (PAMAP) Jay Parrish, Ph.D.
(jayparrish@state.pa.us), Director/State Geologist , BTGS;
(GeoCue/DPMS) Martin Flood (mflood@geocue.com),
GeoCue Corporation; or (cover/PAMAP/DPMS) Brian Bills (bbills@eesi.psu.edu), Assistant Director,
Center for Environmental Informatics, Penn State University.
An approach to topographic feature extraction from DTM using
adaptive marching square algorithm based on the maximum
curvature and maximum connectivity
The scaling effect was examined on the relationship between
landscape patterns and land surface temperatures based on a
case study of Indianapolis, United States.
An investigation of the influence of the number and distribution
of tie points on the integrated orientation of aerial frame
cameras for photogrammetric map compilation.
An analysis of measurement error introduced by mismatches
of scale and location between ground-based response variables
and image-based predictor variables and its effect on
the optimal analytical model and accuracy of forest structure
maps.
A new method that uses existing digital elevation data to
identify errors in elevation models and optimize the stereomatching
algorithms that generate them.