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Cate, R. B.

Publications and source records attributed to Cate, R. B..

Automated vegetation classification using Thematic Mapper Simulation data

The present investigation is concerned with the results of a study of Thematic Mapper Simulation (TMS) data. One of the objectives of the study was related to an evaluation of the usefulness of the Thematic Mapper's (TM) improved spatial resolution and spectral coverage. The study was undertaken as part of a preparation for the efficient incorporation of Landsat 4 data into ongoing technology development in remote sensing. The study included an application of automated Landsat vegetation classification technology to TMS data. Results of comparing TMS data to Multispectral Scanner (MSS) data were found to indicate that all field definition, crop type discrimination, and subsequent proportion estimation may be greatly increased with the availability of TM data.

Nedelman, K. S.

SSG-4 - An automated spring small grains proportion estimator

In connection with an implementation of the classification procedures employed in the Large Area Crop Inventory Experiment (LACIE), a human analyst had to provide labeled samples. The present investigation is concerned with an automated proportion estimation procedure which has been derived from the early field-labeling procedures used in LACIE. This procedure was developed for the U.S./Canada Spring Small Grains Pilot Experiment. It is demonstrated that the considered spatial/color-based proportion estimation procedure provides the agricultural remote-sensing community with the basic tools to develop unbiased and highly efficient procedures for obtaining crop area estimates at the end of the season.

Dennis, T. B.

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Cate, R. B.