Digital Commons Network^™

A Landsat Digital Image Rectification System, Peter Van Wie, Maurice Stein

LARS Symposia

DIRS is a Digital Image Rectification System for the geometric correction of Landsat Multispectral Scanner digital image data. DIRS removes spatial distortions from the data and brings it into conformance with the Universal Transverse Mercator (UTM) map projection. Scene data in the form of landmarks or Ground Control Points (GCPs) are used to drive the geometric correction algorithms. The system offers extensive capabilities for "shade printing" to aid in the determination of GCPs. Affine, two dimensional least squares polynominal and spacecraft attitude modeling techniques for geometric mapping are provided. Entire scenes or selected quadrilaterals may be rectified. Resampling through nearest …

So You Think You Are Ready For Remote Sensing -- Implementation Considerations Of Remote Sensing Technology In A Private Industrial Environment, G. R. Barker

LARS Symposia

One of the most perplexing and continuing problems of research at all levels, is applying and implementing the results in an operational situation. Although no statistics are offered here, it is suspected that the amount of monies allocated each year for research destined for obscurity or strictly academic residency, must be enormous. It is probably no exaggeration to say the most frequent criticism of any industrial management toward research is how pitifully little seems to filter down to the "grass roots" level.

This paper explores the "how come" of this criticism within the private industrial sector, and suggests the problem …

Stratification Of Landsat Data By Clustering, Marvin E. Bauer, Barbara J. Davis

LARS Symposia

Full realization of the potential advantages of the synoptic coverage provided by Landsat will require the development and use of data analysis techniques which take into account the large variation and diversity of patterns found over many Landsat scenes. Stratification of the scene into units which, are internally homogeneous is recommended as a first step in the analysis of data for whole or multiple frames of Landsat data. The use of clustering as an objective and efficient method of dividing scenes into areas which are spectrally similar (strata) is discussed and initial results, including classification performances and comparison of spectral …

Evaluation Of Image Registration Accuracy In The Large Area Crop Inventory Experiment, Toyohisa Kaneko, John Engvall

LARS Symposia

The Large Area Crop Inventory Experiment (LACIE) was created to demonstrate the capability of forecasting the wide area annual production of major crops, such as wheat and corn, from multispectral LANDSAT imagery and meteorological data. The current classification algorithm utilizes multi-temporal imagery from different biological phases which are spatially aligned or registered. It is of paramount importance to investigate and evaluate the accuracy of the registration process, because the number of pixels and the area classified are directly affected. A new technique has been developed at the NASA Johnson Space Center to evaluate image registration accuracy.

University Education In Remote Sensing: Ill-Defined And Ill-Equipped, Stanley A. Morain

LARS Symposia

Training in remote sensing, like that for chemistry and physics from which it draws, demands a "hands-on" experience by students. Explosive growth in the field over the past decade has left instructors and professors in the untenable position of having inadequate instructional aids. Moreover, the extraordinary breadth of sensor applications, both proven and feasible, has led to almost ad hoc decisions as to what should be included in current course work. This ill-defined and ill-equipped status, in the absence of common denominators, results in students whose training is difficult to assess.

Two recent compilations (Morain, Nealey) summarize the current expanse …

Remote Sensing Technology - A Look To The Future, David Landgrebe

LARS Symposia

If one is bothered by the possibility of being wrong perhaps one of the most risky things to do is to attempt to predict future directions of technology. However, in these days of extremely limited resources, good planning for development is essential to get the greatest bang for the buck spent on technology development. Such a plan must be based upon some anticipation of the direction that development will go. Thus, one must attempt to project both the potential for and direction of the future development of a technology. It is important to know at any given time what one's …

Gutter Flushing Systems For Swine Buildings, Don D. Jones, John C. Nye, Brian C. Horsfield, Robert George

Historical Documents of the Purdue Cooperative Extension Service Archive

No abstract provided.

Juniper Twig Blight, Paul C. Pecknold, Walter R. Stevenson, Donald H. Scott

Historical Documents of the Purdue Cooperative Extension Service Archive

No abstract provided.

Algorithmic Progress In Solving Partial Differential Equations, John R. Rice

Department of Computer Science Technical Reports

No abstract provided.

Blending To Control Fat In Processed Meats, H. R. Johnson

Historical Documents of the Purdue Cooperative Extension Service Archive

No abstract provided.

Traffic Speed Report No. 96 : Progress Report, Ahmed Atef Gadallah, George K. Stafford

JTRP Technical Reports

No abstract provided.

Development Of Techniques For Plant Establishment On The Roadside, Philip L. Carpenter, David L. Hensley

JTRP Technical Reports

No abstract provided.

Land Use Studies With Skylab S-192 Data, D. S. Simonett, R. L. Shotwell, N. Belknap

LARS Symposia

The work discussed in this paper uses SKYLAB S-192 digital tapes for the SL/3 Mission over the Washington, D.C.-Baltimore, Maryland urban areas and nearby rural areas in Virginia and Maryland.

The questions addressed were as follows:

* To what degree does the increased spectral coverage of the SKYLAB S-192 Multispectral Scanner (0.41 microns - 12.5 microns) provide new and important information not currently available with the LANDSAT I and II MSS?

* What are the optimal spectral bands to be used in discriminating various land use categories? How do the optimal spectral bands vary from category to category?

* What …

Machine Estimation Of Timber Volumes For Use In Sampling Surveys, Jan W. Van Roessel

LARS Symposia

The digital timber volume estimation method was developed primarily for use with Landsat MSS scanner data. The technique makes use of a vector field clustering algorithm, nearest neighbor classification, and regression analysis. When such a technique is to be applied to reduce the cost for a given level of precision in a forest inventory, the interface between sampling methods and the digital estimation model must be considered. The candidate models and sampling methods must be evaluated using test data as closely related to actual circumstances as possible.

The Use Of Spatial Characteristics For The Improvement Of Multispectral Classification Of Remotely Sensed Data, D. J. Wiersma, D. Landgrebe

LARS Symposia

Two parallel and overlapping approaches to classification of remotely sensed data with the aid of spatial information are underway at the present time. The image processing approach attempts to model after the human visual system, while the second approach is primarily numerical. The technique of texture features, representing the image processing approach, and the sample classifier ECHO, representing the numerical approach are compared. The numerical approach is demonstrated to be superior in classification accuracy as well as being more efficient computationally.

Comparison Of Vegetation Classes In The Great Dismal Swamp Using Two Individual Landsat Images And A Temporal Composite, Patricia T. Gammon, Virginia P. Carter

LARS Symposia

The Great Dismal Swamp on the Virginia/ North Carolina border has highly diverse vegetation, largely due to past alteration by lumbering, fire and drainage. Vegetation maps are presently being completed using National Aeronautics and Space Administration high and low altitude color infrared photographs and 1:100,000 and 1:24,000 scale black and white orthophoto bases. Having mapped the vegetation to the required precision for management needs, we are now evaluating the application potential of Landsat data to provide a cost-effective, repetitive information source for future monitoring and map revision.

Three data sets were prepared for analysis using two Landsat scenes (Image #1583-15100, …

Bayes Estimation On Parameters Of The Single-Class Classifier, G. C. Lin, T. C. Minter

LARS Symposia

Normal procedures used for designing a Bayes classifier to classify wheat as the major crop of interest require not only training samples of wheat but also those of nonwheat. Therefore, ground truth must be available for the class of interest plus all confusion classes. The single-class Bayes classifier classifies data into the class of interest or the class "other" but requires training samples only from the class of interest. This paper will present a procedure for Bayes estimation on the µi, Σi, qi (i.e., mean vector, covariance matrix, and a priori probability) of the single-class classifier using labeled samples from …

Sar Enhancement Of Landsat Imagery, Harold E. Maurer, Paul K. Clemens

LARS Symposia

The objective of this study is to demonstrate that Synthetic Aperture Radar (SAR) imagery adds information for Earth Survey applications which is not available from LANDSAT imagery alone, and that this information can be extracted by application of machine processing techniques. If optimum use is to be made of SAR imagery then its areas of impact need to be identified. SAR imagery was acquired of portions of the Delmarva Peninsula on August 8, 1973, by a United States Air Force RF-4 aircraft based at Shaw Air Force Base, in South Carolina. LANDSAT imagery (0% of cloud cover) was acquired on …

Hindu: Histogram Inspired Neighborhood Discerning Unsupervised Pattern Recognition System, Belur V. Dasarathy

LARS Symposia

A newly developed system for pattern recognition in unsupervised environments, capable of processing large volume data sets with minimal computational resources and human intervention, which is currently operational at the Marshall Space Flight Center, is presented in this study. Here, in this system, the problem of unsupervised learning is viewed as one of clustering the large volume multidimensional data sets and is approached through the novel gambit of terrain development in the multidimensional histogram space. The terrain is developed by connecting each histogram cell to all of its higher density neighbors. This process leads to amalgamation of all the cells …

Generating Character Maps On A Remote Terminal By Use Of Simplified Software, Premsukh Poonai, W. J. Floyd, Royce Hall, Carl J. Upp

LARS Symposia

By use of a simple function to be known as a Natural Classification Function, multispectral signatures of 13910 LANDSAT pixels were classified into categories each of which when plotted on a character map, was found to correspond with a definable ground feature. Classification of the multispectral signatures was done in two stages. In the first stage, 65 categories were generated on the basis of the Natural Classification Function in which the independent variables are the reflectance values of multispectral signatures of pixels. In the second stage the 65 categories were merged into seven realistic categories on the basis of the …

Filtering To Remove Cloud Cover In Satellite Imagery, O. R. Mitchell, P. L. Chen

LARS Symposia

The possibility of filtering light cloud cover in satellite imagery to expose objects beneath the clouds is discussed. A model of the cloud distortion process is developed and a transformation is introduced which makes the signal and noise additive so that optimum linear filtering techniques can be applied. This homomorphic filtering can be done in the two dimensional image plane, or it can be extended to include the spectral dimension on multispectral data. This three dimensional filter is especially promising because clouds tend to follow a common spectral response. The noise statistics can either be estimated from a general cloud …

Experiments In Iterative Enhancement Of Linear Features, Gordon J. Vanderbrug

LARS Symposia

Lines and curves in an image are detected locally by a template-matching process which determines the "line-ness" value of the image at each point, in a set of orientations. The output of the detection process is the strongest of these values at each point, and the orientation that gave rise to this value. The results of this approach tend to be noisy, but their noisiness can be reduced by examining, for each point, the values at nearby points, in the direction defined by the preferred orientation, and increasing the point's value if the nearby points have high values and similar …

Landsat Signature Development Program, Royce N. Hall, Ken G. Mcguire, Roy A. Bland

LARS Symposia

The LANDSAT Signature Development Program, LSDP, is designed to produce an unsupervised classification of a scene from a LANDSAT tape. This classification is based on the clustering tendencies of the multispectral scanner data processed from the scene. The program will generate a character map that, by identifying each of the general classes of surface features extracted from the scene data with a specific line printer symbols, indicates the approximate locations and distributions of these general classes within the scene.

Also provided with the character map are a number of tables each of which describes either some aspect of the spectral …

Remote Sensing Applications For Identifying Potential Recreation Resources, William C. Beattie, Kenneth A. Wenner

LARS Symposia

The applicability of utilizing machine processing (LARSYS) of LANDSAT-1 data for identification of potential recreation resources was investigated. A 6,560 acre tract of land in Geauga County, Ohio, which contained areas identified in the 1971- 1977 Statewide Plan for Outdoor Recreation in Ohio as having potential for outdoor recreation, was selected as the study area. Aerial photographs, field inspection data and land use maps prepared by computer analysis of LANDSAT data were used in this study.

The research was divided into four phases:

1. Identification and evaluation of potential outdoor recreation areas by using either aerial and field data or …

Use Of Landsat Technology By Statistical Reporting Service, William H. Wigton

LARS Symposia

This paper describes an area sampling frame and defines the sampling error and bias of an estimate. LANDSAT data is explained in the Statistical Reporting Service framework and the essential components of computer classification are delineated. A procedure is presented that utilizes satellite data to improve an estimator with 3 percent sampling error.

Application Of A Class Of Sequential Classifiers To Multitemporal Remote Sensing Data, Hans Hauska, Philip H. Swain

LARS Symposia

Developments in the technology of registering images collected by a multispectral scanner over the same area at different times have led to new possibilities for the extraction of temporal information from the scene. This may be of particular value for agricultural scenes, for example, where images from two or more temporally displaced passes can be combined to enhance the discriminability of the classes and thus increase the accuracy with which ground cover types can be determined. Temporal data also are of significant value where changes in the scene from season to season or even over a span of years are …

Experimental Examination Of Similarity Measures And Preprocessing Methods Used For Image Registration, M. Svedlow, C. D. Mcgillem, P. E. Anuta

LARS Symposia

An experimental analysis of a number of image registration techniques is described. The objective is to provide a better understanding on a comparative basis of some of the methods of registering imagery that have been proposed. In particular, this study encompasses the choice of a similarity measure and the effects of preprocessing the imagery prior to the registration.

Correcting Landsat Data For Changes In Sun Angle, Haze Level, And Background Reflectance, J. F. Potter

LARS Symposia

This paper describes a computer program, called ATCOR, which is used to correct signatures obtained from LANDSAT data for differences in sun angle, haze level, and background reflectance.

A set of pre-computed tables is used in the calculations. These tables give the response of the LANDSAT multispectral scanner in each channel as a function of the solar zenith angle, 9, the atmospheric haze level, T, the target reflectance, R, and the average background reflectance RB. The tables also provide coefficients a and b such that for fixed, 9, r, and R the sensor response in a particular channel is given …

Current Methods And Policies Of The Statistical Reporting Service, Charles E. Caudill

LARS Symposia

The Statistical Reporting Service as the, primary fact-collecting and reporting organization of the U.S. Department of Agriculture is responsible for the national program of crop and livestock estimates. Over time, methodology underlying this program has evolved to the point where its foundation is firmly based on probability sampling, employing both area and list sampling frames. Basic data collected for this program is based on voluntary reporting under a pledge of confidentiality. This places strict limits and restraints on SRS in terms of sharing with other agencies or groups the basic data or even unpublished estimates used or generated in the …

Automatic Detection And Classification Of Infestations Of Crop Insect Pests And Diseases From Infrared Aerial Color Photographs, M. Ali, J. K. Aggarwal

LARS Symposia

This paper describes a system designed to analyze aerial color infrared photographs of citrus orchards. The input to the system is a 35 mm transparency of the infrared aerial photograph mounted in a 3-color film digitizer which is controlled by an XDS 930 computer.

An algorithm locates the outline of each individual tree in the photograph and then cluster analysis is applied. For the trees of a transparency, centre of gravity (C.G.) of the set of these trees is determined and then the distance of each individual tree from C.G. is computed by using an empirical distance function which we …