Atmospheric effects in ERTS-1 data, and advanced information extraction techniques
Atmospheric effects in ERTS-1 multispectral scanner data, and techniques for estimating portions of materials within individual elements
Malila, W. A.↗
Engineering topics
Nalepka, R. F.
Publications and source records attributed to Nalepka, R. F..
Signature extension: An approach to operational multispectral surveys
Two data processing techniques were suggested as applicable to the large area survey problem. One approach was to use unsupervised classification (clustering) techniques. Investigation of this method showed that since the method did nothing to reduce the signal variability, the use of this method would be very time consuming and possibly inaccurate as well. The conclusion is that unsupervised classification techniques of themselves are not a solution to the large area survey problem. The other method investigated was the use of signature extension techniques. Such techniques function by normalizing the data to some reference condition. Thus signatures from an isolated area could be used to process large quantities of data. In this manner, ground information requirements and computer training are minimized. Several signature extension techniques were tested. The best of these allowed signatures to be extended between data sets collected four days and 80 miles apart with an average accuracy of better than 90%.
Nalepka, R. F.↗
Summary report of work on ten tasks
There are no author-identified significant results in this report.
Thomson, F. J.↗
Signature extension techniques applied to multispectral scanner data.
Review of a number of spectral radiance signature extension techniques based on the concept of preprocessing the data to reduce the effects due to atmospheric effects, scanner look angle, etc. One of the promising methods studied to date involves using a ratio preprocessing transformation wherein the signals generated in adjacent spectral bands are ratioed on a point-by-point basis prior to classification. This method is easily and efficiently implemented and tests to date have yielded excellent results. Signatures have been successfully extended over 100+ miles, four days, different times of day, and very different atmospheric conditions.
Nalepka, R. F.↗
Classifying unresolved objects from simulated space data.
A multispectral scanner data set gathered at a flight altitude of 10,000 ft. over an agricultural area was modified to simulate the spatial resolution of the spacecraft scanners. Signatures were obtained for several major crops and their proportions were estimated over a large area. For each crop, a map was generated to show its approximate proportion in each resolution element, and hence its distribution over the area of interest. A statistical criterion was developed to identify data points that may not represent a mixture of the specified crops. This allows for great reduction in the effect of unknown or alien objects on the estimated proportions. This criterion can be used to locate special features, such as roads or farm houses. Preliminary analysis indicates a high level of consistency between estimated proportions and available ground truth. Large concentrations of major crops show up especially well on the maps.
Nalepka, R. F.↗
Classification of spatially unresolved objects
A proportion estimation technique for classification of multispectral scanner images is reported that uses data point averaging to extract and compute estimated proportions for a single average data point to classify spatial unresolved areas. Example extraction calculations of spectral signatures for bare soil, weeds, alfalfa, and barley prove quite accurate.
Nalepka, R. F.↗
Detailed interpretation and analysis of selected corn blight watch data sets
A detailed interpretation and analysis of selected corn blight data set was undertaken in order to better define the present capabilities and limitations of agricultural remote multispectral sensing and automatic processing techniques and to establish the areas of investigation needing futher attention in the development of operational survey systems. While the emphasis of this effort was directed toward the detection of various corn blight levels, problems related to the more general task of crop identification were also investigated. Since the analog recognition computer (SPARC) was fully committed to the more routine aspects of processing and since the detailed interpretation and analysis required more in the way of quantitative information, the CDC 1604 digital computer was employed.
Nalepka, R. F.↗
Estimating the proportions of objects within a single resolution element of a multispectral scanner.
Description of a procedu*e designed to estimate the proportions of objects and materials contained in the instantaneous field of view (IFOV) of an airborne multispectral device. A mathematical model is derived to relate the signature of a combination of materials in a resolution cell to the signatures of the individual materials considered. Estimation algorithms are generated and digital computer programs are prepared to apply the algorithms in the description of the effects which are observed when several objects are viewed simultaneously. The maximum likelihood estimate of the proportions of various individual materials in an IFOV is discussed. A simulation program is proposed for such estimates. A procedure for analyzing the geometric relations of signatures which affect the accuracy of estimates is set forth.
Horwitz, H. M.↗
Importance of atmospheric scattering in remote sensing, or everything you've always wanted to know about atmospheric scattering but were afraid to ask.
Discussion of the effects of atmospheric scattering and/or absorption on discrimination between target and background materials in environmental or natural science remote sensing applications. The spectral region considered lies between 0.4 and 3 microns. The results are presented parametrically and include an interesting effect that neighboring materials have on the spectral character of a target as a result of aerosol scattering by atmospheric haze.
Turner, R. E.↗