An independent evaluation by the plenary peer review team
There are no author-identified significant results in this report.
Paarlberg, D.↗
Engineering topics
Goodenough, D.
Publications and source records attributed to Goodenough, D..
Findings of the data processing systems design peer group
There are no author-identified significant results in this report.
Goodenough, D.↗
Remote sensing data processing - Two years ago, today, and two years from today
Certain technical problems arising in the recent past (1975) in the field of the processing of remote sensing data are reviewed including approaches to the analysis of Landsat MSS data and technical difficulties which must be overcome to achieve operational data processing. The current status of remote sensing data processing is then examined with emphasis on such current technical issues as training selection and labeling, sampling schemes and classification and mensuration. Hardware projections are made for the near future (1979) relative to the development of remote sensing data processing.
Holmes, Q. A.↗
User oriented ERTS-1 images
Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.
Shlien, S.↗