Engineering topics

Thomas, G. S.

Publications and source records attributed to Thomas, G. S..

8 records

NASA NTRS1979

Feature extraction applied to agricultural crops as seen by LANDSAT

The physical interpretation of the spectral-temporal structure of LANDSAT data can be conveniently described in terms of a graphic descriptive model called the Tassled Cap. This model has been a source of development not only in crop-related feature extraction, but also for data screening and for haze effects correction. Following its qualitative description and an indication of its applications, the model is used to analyze several feature extraction algorithms.

Kauth, R. J.↗

NASA NTRS1978

Data screening and preprocessing for Landsat MSS data

Two computer algorithms are presented. The first, called SCREEN, is used to automatically identify pixels representing clouds, cloud shadows, snow, water, or anomalous signals in Landsat-2 data. The second, called XSTAR, compensates Landsat-2 data for the effects of atmospheric haze, without requiring ground measurements or ground references. The presentation of these algorithms includes their theoretical background, algebraic details, and performance characteristics. Verification of the algorithms has for the present been limited to Landsat agricultural data. Plans for further development of the XSTAR technique are also presented.

Lambeck, P. F.↗

NASA NTRS1977

BLOB: An unsupervised clustering approach to spatial preprocessing of MSS imagery

A basic concept of Multispectral Scanner data processing was developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called blobs). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.

Kauth, R. J.↗

NASA NTRS1977

Blob - An unsupervised clustering approach to spatial preprocessing of MSS imagery

A basic concept of MSS data processing has been developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called 'blobs'). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.

Kauth, R. J.↗

NASA NTRS1976

System for analysis of LANDSAT agricultural data: Automatic computer-assisted proportion estimation of local areas

The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.

Nalepka, R. F.↗

NASA NTRS1976

The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat

The time trajectories of agricultural data points as seen in Landsat signal space form a pattern suggestive of a tasselled woolly cap. Most of the important crop phenomena can be described using this three dimensional construct: the distribution of signals from bare soil, the processes of green development, yellow development, and shadowing and harvesting. A linear preprocessing transformation which isolates green development, yellow development and soil brightness is used to reduce the dimension of the signal space. Specific measurable pattern elements of the tasselled cap are used to estimate and correct atmospheric haze and moisture effects.

Kauth, R. J.↗

NASA NTRS1975

Methods of extending signatures and training without ground information

Methods of performing signature extension, using LANDSAT-1 data, are explored. The emphasis is on improving the performance and cost-effectiveness of large area wheat surveys. Two methods were developed: ASC, and MASC. Two methods, Ratio, and RADIFF, previously used with aircraft data were adapted to and tested on LANDSAT-1 data. An investigation into the sources and nature of between scene data variations was included. Initial investigations into the selection of training fields without in situ ground truth were undertaken.

Henderson, R. G.↗

NASA NTRS1974

Signature extension studies

The importance of specific spectral regions to signature extension is explored. In the recent past, the signature extension task was focused on the development of new techniques. Tested techniques are now used to investigate this spectral aspect of the large area survey. Sets of channels were sought which, for a given technique, were the least affected by several sources of variation over four data sets and yet provided good object class separation on each individual data set. Using sets of channels determined as part of this study, signature extension was accomplished between data sets collected over a six-day period and over a range of about 400 kilometers.

Vincent, R. K.↗