Cover Image
The multispectral camera images featured on the cover represent a
derived chlorophyll detection model (bottom) and standard color infrared
imagery (top) product for irrigated and non-irrigated cotton fields
in Tifton, Georgia. These data were acquired at 1 meter/pixel ground
resolution using the U.S. Army Topographic Engineering Center’s Digital
Multispectral Camera System mounted on a HELIO C/STOL fixed wing aircraft
operated by EarthData Aviation. Fields are courtesy of Southern States
Cooperative Incorporated. Image data were acquired and processed
by Virginia Commonwealth University, Department of Biology and Center
for Environmental Studies. See Highlight Article on page 1118.
Highlight Articles
1118 Remote Sensing and Precision Agriculture: Ready for Harvest
or Still Maturing?
John E. Anderson, Robert L. Rischer, and Stephen R. Deloach
Peer-Reviewed Articles
1143 Landsat and Apollo: The Forgotten Legacy
Paul D. Lowman, Jr.
Landsat was the unexpected by-product of the Apollo Program, through the Gemini terrain photography, NASA-sponsored remote sensing research, and remote sensing experiments by the Manned Spacecraft Center.
1149 Improvement in Predicting Stand
Growth of Pinus radiata (D. Don) across Landscapes Using NOAA
AVHRR and Landsat MSS Imagery Combined with a Forest Growth Process
Model (3-PGS)
Nicholas Coops
Accumulated above-ground biomass predicted by the model was compared with biomass data from discrete stands in a plantation in southern New South Wales, Australia.
1157 Development of Landscape Metrics for Characterizing Riparian-Stream
Networks
Michael J. Schuft, Thomas J. Moser, P.J. Wigington, Jr., Don L. Stevens,
Jr., Lynne S. McAllister, Shannen S. Chapman, and Ted L. Ernst
The methods developed provide a flexible framework for deriving landscape metrics of functionally important structural attributes of riparian-stream networks for exploring relationships at varying spatial scales with indicators of stream ecological condition.
1169 Spatial Interrelationships between
Lake Elevations, Water Tables, and Sinkhole Occurrence in Central
Florida: A GIS Approach
Dean Whitman, Timothy Gubbels, and Linda Powell
Landsat TM imagery, digital topography, and well data are used to construct a model of the head difference between a discontinuous set of surficial aquifers and the Floridan aquifer, a regionally extensive confined aquifer.
1179 An Image Processing Chain for Land-Cover Classification
Using Multitemporal ERS-1 Data
Jan Verhoeye and Robert De Wulf
The procedure was applied to a series of four SAR images, taken over northeast Costa Rica, which yielded a map with an overall accuracy of 76 percent.
1187 Remotely Sensed Change Detection Based on Artificial
Neural Networks
Xiaolong Dai and Siamak Khorram
Findings of this study demonstrated the potential and advantages of using neural networks with multitemporal Landsat TM imagery for land-cover change analysis.
1195 A Technique for Spatial Sampling and Error
Reporting for Image Map Bases
Albert K. Chong
The technique is based on the coverage of an image map base, the initial estimated accuracy, and the principle of error propagation to determine a number of check points.
1199 Detection and Location of Objects from Mobile Mapping
Image Sequences by Hopfield Neural Networks
Rongxing Li, Weian Wang, and Hong-Zeng Tseng
Street light poles were modeled in the 3D scene domain and detected by the network with neurons formed by vector edge features from the model and the mobile mapping images.
Announcements
1134 Pecora 14/Land Satellite Information III
1205 PE&RS Special Issue—Call for Papers
1210 ASPRS DC2000—Annual Conference
Columns & Updates
1115 In Memoriam — Carl M. Berry, and William L. Johnson
1125 National Spatial Data Infrastructure — Make No Small Plans
1129 Grids & Datums — The
Kingdom of Norway
1133 Industry News
Departments
1139 Who’s Who in ASPRS
1140 Sustaining Members
1142 New Members
1142 Index to Advertisers
1148 Instructions to Authors
1168 Forthcoming Articles
1206 Calendar
1207 Classifieds
1213 Bookstore
1217 Professional Directory
1221 Membership
Application
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