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Amis, M. L.

Publications and source records attributed to Amis, M. L..

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

When the Thematic Mapper (TM) imagery was first received and displayed in the fall of 1982, its radiometric lucidity and geometric fidelity was judged far superior to the multispectral scanner (MSS) imagery. The MSS data from the LANDSAT series of satellites have served well as the mainstay of satellite imagery for the remote sensing community up to now. Therefore, there is great anticipation as to the utility of this new IM imagery to advance the field of remote sensing. The thematic mapper (TM) band to band registration accuracy evaluation was discussed. In particular, the band to band registration accuracies of the TM data in the subpixel region were evaluated using the Johnson Space Center (JSC) registration processor which is ideally suited for this task. The JSC registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. The approach and the rationale behind the task, the description of the data set, the evaluation results, and the preliminary conclusions are discussed.

Yao, S. S.↗

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Yao, S. S.↗

Evaluation of small area crop estimation techniques using LANDSAT- and ground-derived data

Studies completed in fiscal year 1981 in support of the clustering/classification and preprocessing activities of the Domestic Crops and Land Cover project. The theme throughout the study was the improvement of subanalysis district (usually county level) crop hectarage estimates, as reflected in the following three objectives: (1) to evaluate the current U.S. Department of Agriculture Statistical Reporting Service regression approach to crop area estimation as applied to the problem of obtaining subanalysis district estimates; (2) to develop and test alternative approaches to subanalysis district estimation; and (3) to develop and test preprocessing techniques for use in improving subanalysis district estimates.

Amis, M. L.↗

Evaluation of large area crop estimation techniques using LANDSAT and ground-derived data

The results of the Domestic Crops and Land Cover Classification and Clustering study on large area crop estimation using LANDSAT and ground truth data are reported. The current crop area estimation approach of the Economics and Statistics Service of the U.S. Department of Agriculture was evaluated in terms of the factors that are likely to influence the bias and variance of the estimator. Also, alternative procedures involving replacements for the clustering algorithm, the classifier, or the regression model used in the original U.S. Department of Agriculture procedures were investigated.

Amis, M. L.↗

Evaluation of large area crop estimation techniques

The performance of the USDAs EDITOR system is evaluated. The system processes Landsat imagery and estimates crop hectarage for large areas based on a regression estimator developed on a sample with known ground truth. It is found that use of multitemporal data over unitemporal significantly improves the hectarage estimates, and a 15% reduction in the r-squared of the regression occurs when independent and jackknifed test sets are used to evaluate the performance of the estimator. When an alternative clustering algorithm, CLASSY, is substituted for the current EDITOR method, estimator performance is improved with reduced need for analyst decisions. It is recommended that the CLASSY clustering algorithm and some form of jackknifing be implemented on EDITOR.

Amis, M. L.↗