Current PE&RS Cover
PE&RS March 2005
VOLUME 71, NUMBER 3PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING
Cover Image
The satellite images on the cover show the western coast of Sumatra, Indonesia before and after an earthquake triggered a massive tsunami that devastated the region on Dec. 26, 2004.
The larger post-tsunami image, taken by Space Imaging’s IKONOS® satellite, was acquired and processed by CRISP at the National University of Singapore on Dec. 29, 2004. It shows the village of Lhoknga near the capital city of Banda Aceh. The village was completely destroyed by the tsunami, with the exception of the white mosque in the center of town. Almost all trees, vegetation, and buildings in the area were washed away. Behind the town, low-lying agricultural areas remained covered with water three days after the disaster. In addition, the white sand of nearby beaches was completely removed. The inset image, also from IKONOS, shows how the lush green coast and inland looked on Jan. 10, 2003.
In the days following the disaster, remote sensing satellites were tasked to gather and disseminate imagery of the disaster. Imagery was sent to U.S. government agencies, federal civilian agencies, and international aid agencies to help facilitate and coordinate relief efforts. Significant amounts of satellite collection capacities were dedicated to acquiring imagery associated with the disaster.
IKONOS® images acquired and processed by the Centre for Remote Imaging, Sensing, and Processing (CRISP), National University of Singapore. Copyright© 2005, Space Imaging/CRISP-Singapore. All rights reserved.
For more images of the tsunami damage, go to the Gallery section on www.spaceimaging.com.
Highlight Article
240 Enterprise Geospatial Production
Lewis Graham
Columns & Updates
249 Grids & Datums — Independent State of
Papau New Guinea
252 Region Activities — Region Doubles
Scholarship Awards
253 Headquarters News — 2005 ASPRS Fellow
Award Winner
257 Industry News
Peer-Reviewed Articles (Click the linked titles to see the full abstract)
269 Evaluating Object-Based Data Quality
Attributes in the Land Cover Map 2000
of the United Kingdom
Paul Robinson, Peter Fisher, and Geoff Smith
Object-based data quality information in the Land Cover Map 2000 of the United Kingdom is analyzed, and its usefulness demonstrated.
277 Automatic Determination of the Optimum
Generic Sensor Model Based on Genetic
Algorithm Concepts
Farhad Samadzadegan, Ali Azizi, and Ahmad
Abootalebi
A genetic algorithm was used to automatically determine the optimum term and order of Generic Sensor Models for geometric correction of satellite imagery.
289 Textural Discrimination of an Invasive Plant,
Schinus terebinthifolius, from Low Altitude
Aerial Digital Imagery
Leonard Pearlstine, Kenneth M. Portier, and Scot E.
Smith
Texture features derived from first and second order statistics and edge components in high-resolution digital color infrared images were tested for their ability to discriminate Schinus terebinthifolius in multiple linear logistic regressions.
299 Leaf Optical Property Changes Associated
with the Occurrence of Spartina alterniflora
Dieback in Coastal Louisiana Related to Remote
Sensing Mapping
Elijah Ramsey III and Amina Rangoonwala
Determining optimal reflectance bands for detecting march impact with hyperspectral leaf optical analysis.
313 Comparison of Three Algorithms for Filtering
Airborne Lidar Data
Keqi Zhang and Dean Whitman
Three terrain filtering methods for airborne lidar measurements based on changes of local elevation and slopes are presented and compared by applying them to various data sets from urban, coastal, and mountainous areas.
325 Semi-Automatic Registration of Multi-Source
Satellite Imagery with Varying Geometric
Resolutions
Ayman Habib and Rami Al-Ruzouq
A semi-automatic image registration paradigm that can handle multi-source satellite imagery with varying geometric resolutions.
333 Nested Hyper-Rectangle Learning Model for
Remote Sensing: Land Cover Classification
Li Chen
The NHLM learning model is presented and tested with SPOT data to illustrate an efficient and accurate supervised classification method.
Announcements
262 Photogrammetric Engineering & Remote
Sensing Special Issue Call for Papers — “Mapping
from High Resolution Satellite Imagery”
268 Photogrammetric Engineering & Remote
Sensing – Special Issue Call for Papers —“The Shuttle Radar
Topography Mission– Data Validation and Applications”
324 Call for Papers — The 20th Biennial
Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery
for Resource Assessment
Departments
253 Region of the Month
254 New Member List
264 Who’s Who in ASPRS
265 Sustaining Members
267 New Sustaining Member
268 Advertiser Index
312 Instructions
to Authors
341 Forthcoming Articles
342 Calendar
343 Classifieds
344 Bookstore
349 Professional Directory
352 Membership Application
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