PE&RS March 2009

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.

Highlight Articles
222 Implementing Distributed Production Management on PAMAP (Adobe PDF 820Kb)
Martin Flood, Brian Bills and Bob Ryan

Columns & Updates
228 Grids and Datums — Belize (Adobe PDF 587Kb)
231 Mapping Matters
232 Mapping Matters— Correction
235 Book Review — Advances in Spatio-Temporal Analysis (Adobe PDF 738Kb)
238 In Memoriam — Morris M. Thompson
239 Reflection of the Past (Adobe PDF 550Kb)
249 Industry News

Announcements
221 ASPRS Celebrates its 75th Anniversary (Adobe PDF626Kb)
240 New Sustaining Member— TerraGo Technologies
242 ASPRS Foundation Donors— 2004 – 2008
334 ASPRS/MAPPS Fall Conference— Digital Mapping from Elevation to Information

Departments
236 New Members
240 Region of the Month
240 Certification List
248 ASPRS Member Champions (Adobe PDF 572Kb)
252 Who’s Who in ASPRS
253 Sustaining Members
255 Instructions for Authors
270 Forthcoming Articles
312 CalendarCalendar
336 Classifieds
337 Professional Directory
338 Advertiser Index
340 Membership Application

Peer-Reviewed Articles (Click the linked titles to see the full abstract)

257 Assessing Spatial Uncertainty of Lidar-derived Building Model: A Case Study in Downtown Oklahoma City
Mang Lung Cheuk and May Yuan

Research assessing the spatial uncertainty of lidar-derived building model using downtown Oklahoma City as an example.

271 Reconstruction of Complex Shape Buildings from Lidar Data Using Free Form Surfaces
Nizar Abo Akel, Sagi Filin, and Yerach Doytsher

A lidar-based building-extraction model that supports the reconstruction of buildings with general, free-form shapes.

281 An Adaptive Approach to Topographic Feature Extraction from Digital Terrain Models
Yonghak Song and Jie Shan

An approach to topographic feature extraction from DTM using adaptive marching square algorithm based on the maximum curvature and maximum connectivity

291 Scaling Effect on the Relationship between Landscape Pattern and Land Surface Temperature: A Case Study of Indianapolis, United States
Hua Liu and Qihao Weng

The scaling effect was examined on the relationship between landscape patterns and land surface temperatures based on a case study of Indianapolis, United States.

305 Role of Tie Points in Integrated Sensor Orientation for Photogrammetric Map Compilation
Kourosh Khoshelham

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.

313 Effects of Mismatches of Scale and Location between Predictor and Response Variables on Forest Structure Mapping
Yaguang Xu, Brett G. Dickson, Haydee M. Hampton, Thomas D. Sisk, Jean A. Palumbo, and John W. Prather

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.

323 Optimization of Stereo-matching Algorithms Using Existing DEM Data
D.G. Milledge, S.N. Lane, and J. Warburton

A new method that uses existing digital elevation data to identify errors in elevation models and optimize the stereomatching algorithms that generate them.