A preliminary report on the assessment of wetland productive capacity from a remote-sensing-based model - A NASA/NMFS joint research project
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Butera, M. K.↗
Engineering topics
Butera, M. K.
Publications and source records attributed to Butera, M. K..
An analysis of the effect of biological and physical parameters of a wetlands grass biome on the spectral modeling of phytomass and primary productivity
Aircraft simulated thematic mapper data and field data were acquired in the fall and spring to analyze the relationship of spectral response and biomass for the marsh grass Spartina patens. Regression results indicate no simple relationship exists for TMS spectral response and biomass with a high R sq. However, results show a consistent relationship between spectral response and the percent live vegetation (by weight) and percent interstitial standing surface water (by area) as independent variables. It is suggested that the reflected energy of a pixel represents a mixture of surface constituents. It is recommended that alternative remote sensors be employed to account for the pixel constituents of live and dead vegetation, litter, and standing water.
Butera, M. K.↗
A correlation analysis of percent canopy closure versus TMS spectral response for selected forest sites in the San Juan National Forest, Colorado
The correlation of canopy closure with the signal response of individual thematic mapper simulator (TMS) bands for selected forest sites in the San Juan National Forest, Colorado was investigated. Ground truth consisted of a photointerpreted determination of percent canopy closure of 0 to 100 percent for 32 sites. The sites selected were situated on plateaus at an elevation of approximately 3 km with slope or = 10 percent. The predominant tree species were ponderosa pine and aspen. The mean TMS response per band per site was calculated from data acquired by aircraft during mid-September, 1981. A correlation analysis of TMS response vs. canopy closure resulted in the following correlation coefficients for bands 1 through 7, respectively: -0.757, -0.663, -0.666, -0.088, -0.797, -0.763. Two model regressions were applied to the TMS data set to create a map of predicted percent forest canopy closure for the study area. Results indicated percent predictive accuracies of 71, 74, and 57 for percent canopy closure classes of 0-25, 25-75, and 75-100, respectively.
Butera, M. K.↗
Remote sensing of wetlands
Results are given for three separate investigations of remote sensing over wetlands, including the delineations of roseau cane and mangrove from both Landsat and aircraft MSS data, and the delineation of wetland communities for potential waste assimilation in a coastal river floodplain from Landsat MSS data only. Attention is also given to data processing and analysis techniques of varying levels of sophistication, which must increase with surface cover diversity. All computer processing in these studies was performed on a minicomputer configured with the adequate memory, image display capability, and associated peripherals, using state-of-the-art digital MSS data analysis software.
Butera, M. K.↗
Assessment of wetland productive capacity from a remote-sensing-based model - A NASA/NMFS joint research project
NASA and the U.S. National Marine Fisheries Service have undertaken the development of Landsat Thematic Mapper (TM) technology for the evaluation of the usefulness of wetlands to estuarine fish and shellfish production. Toward this end, a remote sensing-based Productive Capacity model has been developed which characterizes the biological and hydrographic features of a Gulf Coast Marsh to predict detrital export. Regression analyses of TM simulator data for wetland plant production estimation are noted to more accurately estimate the percent of total vegetative cover than biomass, indicating that a nonlinear relationship may be involved.
Butera, M. K.↗
Computer-implemented remote sensing techniques for measuring coastal productivity and nutrient transport systems
An automatic technique has been developed to measure marsh plant production by inference from a species classification derived from Landsat MSS data. A separate computer technique has been developed to calculate the transport path length of detritus and nutrients from their point of origin in the marsh to the shoreline from Landsat data. A nutrient availability indicator, the ratio of production to transport path length, was derived for each marsh-identified Landsat cell. The use of a data base compatible with the Landsat format facilitated data handling and computations.
Butera, M. K.↗
A determination of Marsh detrital export from Landsat MSS data - A function of transport distance and water body characterization
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Butera, M. K.↗
Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data
The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.
Butera, M. K.↗
A Determination of the Optimum Time of Year for Remotely Classifying Marsh Vegetation from LANDSAT Multispectral Scanner Data
The author has identified the following significant results. A technique was used to determine the optimum time for classifying marsh vegetation from computer-processed LANDSAT MSS data. The technique depended on the analysis of data derived from supervised pattern recognition by maximum likelihood theory. A dispersion index, created by the ratio of separability among the class spectral means to variability within the classes, defined the optimum classification time. Data compared from seven LANDSAT passes acquired over the same area of Louisiana marsh indicated that June and September were optimum marsh mapping times to collectively classify Baccharis halimifolia, Spartina patens, Spartina alterniflora, Juncus roemericanus, and Distichlis spicata. The same technique was used to determine the optimum classification time for individual species. April appeared to be the best month to map Juncus roemericanus; May, Spartina alterniflora; June, Baccharis halimifolia; and September, Spartina patens and Distichlis spicata. This information is important, for instance, when a single species is recognized to indicate a particular environmental condition.
Butera, M. K.↗
A demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data
The author has identified the following significant results. Major vegetative classes identified by the remote sensing technique were cypress swamp, pine, wetland grasses, salt grass, mixed mangrove, black mangrove, Brazilian pepper. Australian pine and melaleuca were not satisfactorily classified from LANDSAT. Aircraft scanners provided better resolution resulting in a classification of finer surface detail. An edge effect, created by the integration of diverse spectral responses within boundary elements of digital data, affected the wetlands classification. Accuracy classification for aircraft was 68% and for LANDSAT was 74%.
Butera, M. K.↗
The mapping of marsh vegetation using aircraft multispectral scanner data
Aircraft multispectral scanner data were applied to the identification and mapping of Louisiana marsh vegetation species for salinity ozone determination.
Butera, M. K.↗
A technique for the determination of Louisiana marsh salinity zone from vegetation mapped by multispectral scanner data: A comparison of satellite and aircraft data
Vegetation in selected study areas on the Louisiana coast was mapped using low altitude aircraft and satellite (LANDSAT) multispectral scanner data. Fresh, brackish, and saline marshes were then determined from the remotely sensed presence of dominant indicator plant associations. Such vegetational classifications were achieved from data processed through a standard pattern recognition computer program. The marsh salinity zone maps from the aircraft and satellite data compared favorably within the broad salinity regimes. The salinity zone boundaries determined by remote sensing compared favorably with those interpolated from line-transect field observations from an earlier year.
Butera, M. K.↗
The mapping of marsh vegetation using aircraft multispectral scanner data
A test was conducted to determine if salinity regimes in coastal marshland could be mapped and monitored by the identification and classification of marsh vegetative species from aircraft multispectral scanner data. The data was acquired at 6.1 km (20,000 ft.) on October 2, 1974, over a test area in the coastal marshland of southern Louisiana including fresh, intermediate, brackish, and saline zones. The data was classified by vegetational species using a supervised, spectral pattern recognition procedure. Accuracies of training sites ranged from 67% to 96%. Marsh zones based on free soil water salinity were determined from the species classification to demonstrate a practical use for mapping marsh vegetation.
Butera, M. K.↗