The Laboratory for Applications of Remote Sensing (LARS)is a multidisciplinary research laboratory, internationally known for its research efforts relating to remote sensing and more recently Geographic Information Systems. The focus of LARS is to further develop the fundamental knowledge of the earth and its biophysical processes and to improve techniques for analyzing and interpreting remotely sensed data from earth observation sensors. LARS is a laboratory within Information Technology at Purdue (ITaP) Discovery Resources.
This series contains technical reports written by Laboratory for Applications of Remote Sensing at Purdue University.
Technical Reports from 1973
The Role of Computer Networks in Remote Sensing Data Analysis, P. H. Swain, T. L. Philips, and J. C. Lindenlaub
Land Use Classification of Marion County, Indiana by Spectral Analysis of Digitized Satellite Data, William J. Todd and Marion F. Baumgardner
Urban Land Use Monitoring from Computer-Implemented Processing of Airborne Multispectral Sensor Data, William J. Todd, Paul W. Mausel, and Marion F. Baumgardner
An Analysis of Milwaukee County Land Use by Machine-Processing of ERTS Data, W. Todd, P. Mausel, and M. F. Baumgardner
Technical Reports from 1972
Spectra of Normal and Nutrient-Deficient Maize Leaves, A. H. Al-Abbas, R. Barr, J. D. Hall, F. L. Crane, and M. F. Baumgardner
A Cluster-Oriented Analysis of Multispectral Scanner Data, Paul E. Anuta
Calibration of Aircraft Scanner Data Using Ground Reflectance Panels, Paul E. Anuta and William R. Simmons
Data Handling and Analysis for the 1971 Corn Blight Watch Experiment, P. E. Anuta, T. L. Philips, and D. A. Landgrebe
Final Report for the LARS/Purdue - IBM Houston Scientific Center Joint Study Program, P. E. Anuta, E. M. Rodd, R. E. Jensen, and P. R. Tobias
The Corn Blight Problem--1970 and 1971, Marvin E. Bauer
Differentiating Elements of the Soil-Vegetation Complex, M. F. Baumgardner
Mapping of Soils and Geologic Features with Data from Satellite-Borne Multispectral Scanners, M. F. Baumgardner, S. J. Kristof, and W. N. Melhorn
Definition of Spectrally Separable Classes for Soil Survey Research, J. E. Cipra, P. H. Swain, J. H. Gill, M. F. Baumgardner, and S. J. Kristof
A Three-Stage Sample Model for Remote Sensing Applications, Ludwig M. Eisgruber
Potential Benefits of Remote Sensing: Theoretical Framework and Empirical Estimate, Ludwig M. Eisgruber
Conjugate Point Determination in Multitemporal Data Overlay, Richard A. Emmert and Claire D. McGillem
Agricultural and Forest Resource Surveys from Space, Roger M. Hoffer
Land Utilization and Water Resource Inventories over Extended Test Sites, Roger M. Hoffer
Corn Blight Watch Experiment Results, C. J. Johannsen and M. E. Bauer
Influence of Haze Layers upon Remotely-Sensed Surface Properties, G. M. Jurica and W. L. Murray
Light Ray Tracing through a Leaf Cross Section, R. Kumar and L. Silva
An Early Analysis of ERTS-1 Data, D. A. Landgrebe, R. M. Hoffer, and F. E. Goodrick
Automatic Classifications of Soils and Vegetation with ERTS-1 Data, David Landgrebe
Data Processing II: Advancements in Large-Scale Data Processing Systems for Remote Sensing, David Landgrebe
Utilizing Remote Multispectral Scanner Data and Computer Analysis Techniques, Philip N. LeBlanc, Christian J. Johannsen, and Joseph E. Yanner
Results of the 1971 Corn Blight Watch Experiment, Robert B. MacDonald, Marvin E. Bauer, Richard D. Allen, Joseph W. Clifton, Jon D. Erickson, and David A. Landgrebe
Moire Patterns and Two-Dimensional Aliasing in Line Scanner Data Acquisition Systems, C. D. McGillem and T. E. Riemer
1971 Corn Blight Watch Experiment Data Processing, Analysis, and Interpretation, Terry L. Phillips
Multispectral Data Compression through Transform Coding and Block Quantization, P. J. Ready and P. A. Wintz
Measurement of Available Soil Moisture, F. V. Schultz
Measurements Program in Remote Sensing, Leroy F. Silva
Multispectral Determination of Vegetative Cover in Corn Crop Canopies, E. R. Stoner and M. F. Baumgardner
Determining Density of Maize Canopy: III. Temporal Considerations, E. R. Stoner, M. F. Baumgardner, P. E. Anuta, and J. E. Cipra
Determining Density of Maize Canopy: II. Airborne Multispectral Scanner Data, E. R. Stoner, M. F. Baumgardner, and J. E. Cipra
Determining Density of Maize Canopy: I. Digitized Photography, E. R. Stoner, M. F. Baumgardner, and P. H. Swain
Pattern Recognition: A Basis for Remote Sensing Data Analysis, Philip H. Swain
Minimum Distance Classification in Remote Sensing, A. G. Wacker and D. A. Landgrebe
Engineering Soils Mapping from Multispectral Imagery Using Automatic Classification Techniques, Terry R. West
Notes of Image Correlation and Registration System Improvements, Stanton Yao
Application of Multispectral Remote Sensing to Soil Survey Research in Indiana, A. L. Zachary, J. E. Cipra, R. I. Diderickson, S. J. Kristof, and M. F. Baumgardner
Technical Reports from 1971
Remote Sensing as a Means of Detecting Crop Disease, Marvin E. Bauer