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Bartolucci, L. A.

Publications and source records attributed to Bartolucci, L. A..

Evaluation of the Radiometric Quality of the TM Data Using Clustering, Linear Transformations and Multispectral Distance Measures

The radiometric quality of LANDSAT 4 TM data for the classification and identification of Earth surface features was evaluated. Techniques employed in the evaluation included clustering, data compression (linear transformations), multispectral distance measures, and hierarchical classification methods. TM and MSS data for the Chicago, Illinois test site were studied. In order to determine the radiometric quality of the TM thermal data for temperature mapping of surface water, a test site was selected within the area covered by the TM scene (Scene ID: 40101-16025) gathered over Illinois. This site was chosen because it includes a surface water body with a large range of temperatures, i.e., a cooling pond for the Dresden nuclear power plant and the junction of two rivers.

Bartolucci, L. A.

LANDSAT-4/5 image data quality analysis

A LANDSAT Thematic Mapper (TM) quality evaluation study was conducted to identify geometric and radiometric sensor errors in the post-launch environment. The study began with the launch of LANDSAT-4. Several error conditions were found, including band-to-band misregistration and detector-to detector radiometric calibration errors. Similar analysis was made for the LANDSAT-5 Thematic Mapper and compared with results for LANDSAT-4. Remaining band-to-band misregistration was found to be within tolerances and detector-to-detector calibration errors were not severe. More coherent noise signals were observed in TM-5 than in TM-4, although the amplitude was generally less. The scan direction differences observed in TM-4 were still evident in TM-5. The largest effect was in Band 4 where nearly a one digital count difference was observed. Resolution estimation was carried out using roads in TM-5 for the primary focal plane bands rather than field edges as in TM-4. Estimates using roads gave better resolution. Thermal IR band calibration studies were conducted and new nonlinear calibration procedures were defined for TM-5. The overall conclusion is that there are no first order errors in TM-5 and any remaining problems are second or third order.

Malaret, E.

Landsat-4 MSS and Thematic Mapper data quality and information content analysis

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Anuta, P. E.

Evaluation of Landsat-4 Thematic Mapper and multispectral scanner data quality

Landsat-4 image data quality was evaluated for test sites in Iowa and Illinois. Radiometric and geometric quality was tested and an applications evaluation was carried out using a cooling-pond thermal-mapping example. Geometric quality was found to be generally very good. Small errors were found in registration of the middle IR bands of the TM and the thermal IR band was found to be misregistered by one 120-meter pixel. Radiometric quality of the TM is excellent with only minor striping effects.

Bartolucci, L. A.

Comparison of classification schemes for MSS and TM data

The launch of the Landsat-4 satellite in July 1982 provided the first full coverage from space of the 0.4-12 micron spectrum of the earth scene. In addition to the green, red, and near IR bands of the MSS, the TM provides a band in the blue, two in the middle IR, and one thermal IR. The paper describes spectral class analysis of coincident MSS and TM data to evaluate the contribution of the additional TM bands. In addition, various classifiers are available which were applied to the TM data. In the spectral class analysis, twice the number of separable classes was found in the TM data compared to the MSS data.

Anuta, P. E.

Evaluation of the radiometric quality of the TM data using clustering and multispectral distance measures

Radiometrically and geometrically corrected TM data from three different geographic locations were examined. Histograms were inspected for each band to determine the dynamic range of the data, the shape of the distributions, and to verify whether empty bins were introduced by the radiometric correction process. The effect of geometric correction on the radiometry of the resampled pixels was determined. The information content between TM and MSS data sets were compared and the TM data were used to map the thermal effluent discharge into a river ecosystem from a nuclear thermal power plant, and application only possible previously only possible through the acquisition of thermal infrared scanner data from aircraft altitudes.

Bartolucci, L. A.

Customized remote sensing short courses

The advantages of customized courses over general purpose courses are outlined. The development of course objectives and content and the incorporation of hands-on exercises are discussed. Criteria for ensuring the quality of the course are also defined.

Davis, S. M.

Field measurements of the spectral response of natural waters

The spectral response (air-water interface reflectance and water-volume scattering) of turbid river water (99 mg/liter suspended solids) and relatively clear lake water (10 mg/liter suspended solids) was measured in situ with a field spectroradiometer. The influence of the river bottom on the spectral response of the water also was determined by using a modified Secchi disc approach. The results indicated that turbid river water had a higher spectral response than clear lake water (about 6 percent) in the red (0.6-0.7 micron) and near-infrared (0.7-0.9 micron) portions of the spectrum. Also, the reflectance characteristics of the river bottom did not influence the spectral response of the turbid river water when the water was deeper than 30 cm

Bartolucci, L. A.

Selective radiant temperature mapping using a layered classifier

A method of measuring temperatures of selected ground-cover types using remotely sensed multispectral scanner data and a layered classification approach is described. A brief review of radiation theory is presented to show that for the wavelength bands and temperature ranges involved in remote sensing applications, a linear calibration function can be satisfactorily utilized. An example of the application of the layered classifier for temperature mapping of water is shown.

Bartolucci, L. A.

Snow cover monitoring by machine processing of multitemporal LANDSAT MSS data

LANDSAT frames were geometrically corrected and data sets from six different dates were overlaid to produce a 24 channel (six dates and four wavelength bands) data tape. Changes in the extent of the snowpack could be accurately and easily determined using a change detection technique on data which had previously been classified by the LARSYS software system. A second phase of the analysis involved determination of the relationship between spatial resolution or data sampling frequency and accuracy of measuring the area of the snowpack.

Luther, S. G.

Snowcover mapping by machine processing of Skylab and LANDSAT MSS data

Skylab and LANDSAT MSS data were analyzed using computer-aided analysis techniques (CAAT). Results indicated that the middle infrared wavelength bands of the Skylab S-192 scanner would allow effective discrimination between snowcover and water-droplet clouds, whereas the limited spectral response of the LANDSAT-1 or 2 scanners do not allow such spectral discrimination. Five spectral classes of snowcover were defined and mapped. These classes were found to be related to differences in the proportion of snow and forest cover in the individual resolution elements.

Bartolucci, L. A.