Cover Image
The National Elevation Dataset (NED) is a seamless raster product produced
by the U.S. Geological Survey (USGS). The NED provides elevation data coverage
of the continental United States, Alaska, Hawaii, and the island territories
in a seamless format with consistent projection, resolution, elevation units,
and horizontal and vertical datums. “Application-ready” NED products are
available in several formats through a Web-based seamless data distribution
system. The NED is the result of the maturation of the USGS elevation production
program, in which national coverage of quadrangle-based digital elevation
models has been completed. Because it is regularly maintained and updated
and is easily accessible, the NED provides basic elevation data for many
GIS applications, thus fulfilling many of the concepts of the “best available” framework
geospatial data as envisioned for the National Spatial Data Infrastructure.
The use of the NED facilitates applications by allowing users to focus on
analysis rather than data preparation. This month’s Highlight
Article (pg. 5) gives details on the technical specifications of the
NED, its production methodology, and ongoing related development. Further
information is available on the NED Web site at http://gisdata.usgs.gov/ned/.
Highlight Article
5 The National Elevation Dataset
Dean Gesch, Michael Oimoen, Susan Greenlee, Charles Nelson, Michael
Steuck, and Dean Tyler
Peer-Reviewed Articles (Click the linked titles to see the full abstract)
33 A Synergistic Automatic Clustering
Technique (SYNERACT) for Multispectral Image Analysis
Kai-Yi Huang
A new effective synergistic automatic clustering technique (SNYERACT)
was developed to serve as a substitute for ISODATA when applied to
remote sensing image analysis with a large data set.
41 Fuzzy Objects: Their Changes and Uncertainties
Tao Cheng
Uncertainty issues in GIS and remote sensing are addressed.
51 Scale and Texture in Digital Image
Classification
Christopher J.S. Ferro and Timothy Warner
Simulated and actual data experiments were used to determine the effects
various texture scales had upon a maximum-likelihood classifier and
to suggest an approach that might aid in the selection of appropriate
window sizes for texture feature extraction.
65 Impacts of Patch Size and Land-Cover
Heterogeneity on Thematic Image Classification Accuracy
Jonathan H. Smith, James D. Wickham, Steven V. Stehman, and Limin Yang
The effects of landscape characteristics on image classification accuracy
are assessed and compared with those due to land-cover class confusion.
71 Drought Monitoring with NDVI-Based
Standardized Vegetation Index
Albert J. Peters, Elizabeth A. Walter-Shea, Lei Ji, Andrés Viña,
Michael Hayes, and Mark D. Svoboda
The Standardized Vegetation Index, derived from AVHRR satellite data,
describes the relative condition of vegetation status and can assess
the extent and severity of drought at a 1-kilometer spatial resolution.
77 Subpixel Classification of Alder Trees
Using Multitemporal Landsat Thematic Mapper Imagery
Kazuo Oki, Hiroyuki Oguma, and Mikio Sugita
Estimation of alders from multitemporal TM imagery of the Kushiro
mire wetlands was achieved by an unmixing method using ground-truth
data.
83 Use of Contour-Based DEMs for Deriving
and Mapping Topographic Attributes
Hiroko Mizukoshi and Masamu Aniya
The methods to calculate slope gradient and aspect and to classify
slope form using contour-based DEMs are presented.
Announcements
22 Integrating Remote Sensing at the Global, Regional, and Local Scale — Call
for Papers
49 Call for Papers — Challenges in Geospatial
Analysis and Visualization
64 ASPRS-ACSM 2002 Conference
Columns & Updates
13 Direct Georeferencing (Adobe Acrobat format 405kb)
19 Grids & Datums — Bulgaria
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