VOLUME 73, NUMBER 9
PHOTOGRAMMETRIC ENGINEERING & REMOTE
SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY
AND REMOTE SENSING
Landsat fusion image of Hong Kong on 11th November and 20th December 2006.
Although Hong Kong has a population of 7 million people and growing, and is one of the busiest trans-shipment ports in the world, only about 20% of the land area is available for urban development due to the steep and rugged terrain. The pressures placed on the developable land makes Earth Observation a significant and necessary planning tool for balanced and sustainable development. Landsat-7 fusion image processed by Geocarto International
Centre (http://www.geocarto.com).
991 LAS 2.0 Lidar Data Exchange Standard Proposed for Approval
991 ASPRS Proposed Bylaws Changes
992 State of ASPRS Membership Report
997 Two New Members Named to ASPRS Foundation Board of Trustees
997 ASPRS Foundation Receives First Transfer of Scholoarship Funds from Region
Announcements 989 New and Renewed Certified Photogrammetrists, Mapping Scientists and Technologists, December 6th 2006- June 14th 2007
1066 Call for Papers — ILMF 2008
1066 Call for Papers — Spatial Change Analysis
A comparison and evaluation of the effectiveness of hyperspectral
(CASI) image visualization techniques based on band selection and feature extraction with the goal of detecting an invasive weed, yellow starthistle, in an annual grassland in California.
Three post-classification techniques were applied to improve the accuracy and the structural coherence of an urban land-cover map derived from a soft pixel-based classification.
A study which clearly implies the strengths of the spectral matching technique in identifying and labeling land-use/land-cover and irrigrated area classes with little or no ground truth.
A method is presented to autonomously register small overlap
imagery with the added benefit that the method provides an indication of when the images have no common area.
To efficiently and reliably extract the main road network from high-resolution satellite imagery, a hierarchical grouping approach
is proposed to generate long collinear main road centerlines
from fragmented road segments.
Tropical forest and land-cover classes within a topographically complex area are mapped from a terrain corrected SPOT HRVIR
image and using linear mixture modeling in combination with a decision tree classifier.