PE&RS February 2002

Cover Image
Front Cover. Upper image: temporal Fourier-processed NOAA AVHRR 1km Land Surface Temperature (LST) imagery (1997-2000) produced by the International Research Partnership for Infectious Diseases (INTREPID) to help monitor and predict the spread of West Nile Virus (WNV) in the United States. Temporal Fourier analysis of the time-series of 14-day maximum value composited LST images captures habitat seasonality in terms of the mean value and the amplitudes and phases of the annual, bi-annual, and tri-annual cycles in these data. In this figure, the mean, annual amplitude and annual phase are in the red, blue and green channels respectively. Brighter colors mean higher values. Black dots superimposed on this image are the locations (county geo-centers) where birds infected with WNV were reported between January and October 2001.

Lower images: AVHRR GAC data collected by the NOAA AVHRR since 1982 and processed to an 8km resolution global data set of unique importance in environmental monitoring. The left image in this group is the 19-year mean LST (1982-2000) in false color; blue indicates low temperatures and red high. The three other images ARE the LSTs for 1998, 1999, and 2000, showing the extent of inter-annual variability. The significance of these variations is discussed in the Highlight Article.

Introduction

109 From Remote Sensing to Relevant Sensing in Human Health
Guest Editors, Simon I. Hay, Monica F. Myers, Nancy Maynard, and David J. Rogers

Highlight Article

112 Predicting the Distribution of West Nile Fever in North America using Satellite Sensor Data
David J. Rogers, Monica F. Myers, Compton J. Tucker, Perry F. Smith, Dennis J. White, P. Bryon Backenson, Millicent Eidson, Laura D. Kramer, Bernhard Bakker and Simon I. Hay  

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

137 Mapping Potential Risk of Rift Valley Fever Outbreaks in African Savannas Using Vegetation Index Time Series Data
Assaf Anyamba, Kenneth J. Linthicum, Robert Mahoney, Compton J. Tucker, and Patrick W. Kelley

The results indicate that outbreaks have occurred predominantly during warm El Niño/Southern Oscillation (ENSO) events in East Africa and during cold ENSO events in southern Africa.  

147 Climatic and Ecological Context of the 1994-1996 Ebola Outbreaks
Compton J. Tucker, James M. Wilson, Robert Mahoney, Assaf Anyamba, Kenneth Linthicum, and Monica F. Myers

Meteorological satellite data, spanning the 1981 to 2000 time period, showed that marked and sudden climate changes from drier to wetter conditions were associated with the Ebola outbreaks in the 1990s.

153 Application of Remote Sensing to Enhance the Control of Wildlife-Associated Mycobacterium bovis Infection
J.S. McKenzie, R.S. Morris, D.U. Pfeiffer, and J.R. Dymond

Supervised automatic classification of a SPOT3 multispectral image was used to generate a vegetation map, which was used together with slope data to model the risk of TB-infected possums being present in habitat patches.

161 Updating Historical Maps of Malaria Transmission Duration in East Africa Using Remote Sensing
J.A. Omumbo, S.I. Hay, S.J. Goetz, R.W. Snow, and D.J. Rogers

Land surface temperature was identified as the best predictor of transmission intensity, while rainfall and moisture availability as inferred by cold cloud duration and the normailzed difference vegetation index, respectively, were identified as secondary predictors of transmission intensity.

167 The Use of Remote Sensing for Predictive Modeling of Schistosomiasis in China
Edmund Seto, Bing Xu, Song Liang, Peng Gong, Weiping Wu, George Davis, Dongchuan Qiu, Xueguang Gu, and Robert Spear

A classification of Landsat TM imagery in mountainous regions of Sichuan Province indicated that the incorporation of soil maps may greatly improve classification accuracy, while the use of Landsat TM imagery and water level data in the lower Yangtze River region led to an understanding of seasonal differences in schistosomiasis habitat.

175 Using NOAA-AVHRR Data to Model Human Helminth Distributions on Planning Disease Control in Cameroon, West Africa
Simon Brooker, Simon I. Hay, Louis-Albert Tchuem Tchuenté, and Raoult Ratard

The use of NOAA-AVHRR data to develop logistic regression models that predict the probability of infection prevalence greater than 50 percent, and thus warrant mass treatment for intestinal nematodes and schistosomes, is described.

Announcements
122 Integrating Remote Sensing at the Global, Regional, and Local Scale — Call for Papers
145 Seventh International Conference — Remote Sensing for Marine and Coastal Environments
160 ASPRS-ACSM 2002 Conference

Columns & Updates
115 Direct Georeferencing
119 Grids & Datums — Japan
123 Letter to the Editor
130 Headquarters News
131 Industry News

Departments
121 Index to Advertisers
134 Who’s Who in ASPRS
135 Sustaining Members
146 Instructions to Authors
159 Forthcoming Articles
180 Classifieds
183 Bookstore
187 Calendar
188 Professional Directory
191 Membership Application

Top

Home