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Milton, N. M.

Publications and source records attributed to Milton, N. M..

7 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Preliminary measurements of spectral signatures of tropical and temperate plants in the thermal infrared

Spectral reflectance measurements of seven tropical species and six deciduous species were carried out in thermal infrared to establish the species-dependent spectral characteristics and to investigate the effect on spectral signatures of environmental variables, such as leaf maturity, drought, and metal stress. Seasonal variations of spectral signatures occurred between spring and summer leaves, but such variations were minimal during summer and early fall. Overall reflectance of senescent leaves was higher than that of young leaves, as was the reflectance of leaves from trees growing in metal-enriched soils, as compared with leaves from the control area. However, the characteristic spectral features were not changed in either case. It was also found that water stress did not have any effect on the infrared signatures: trees grown during a drought season maintained their characteristic spectral signatures.

Salisbury, John W.↗
NASA NTRS1986

Geobotanical studies at Pilot Mountain, North Carolina using the airborne imaging spectrometer

Airborne Imaging Spectrometer (AIS) data were acquired for several vegetation types within the humid temperate eastern United States. The spectral region covered, 0.9 to 2.1 microns, was little used in vegetation studies. A preliminary analysis of spectral curves suggests that variations between vegetation spectra may be useful for discriminating plant communities. Calibration and normalization procedures must be refined to compensate for cloud cover, detector and other system noise, and possible second-order effects.

Milton, N. M.↗
NASA NTRS1983

Seasat synthetic aperture radar /SAR/ response to lowland vegetation types in eastern Maryland and Virginia

Examination of Seasat SAR images of eastern Maryland and Virginia reveals botanical distinctions between vegetated lowland areas and adjacent upland areas. Radar returns from the lowland areas can be either brighter or darker than returns from the upland forests. Scattering models and scatterometer measurements predict an increase of 6 dB in backscatter from vegetation over standing water. This agrees with the 30-digital number (DN) increase observed in the digital Seasat data. The brightest areas in the Chickahominy, Virginia, drainage, containing P. virginica about 0.4 m high, contrast with the brightest areas in the Blackwater, Maryland, marshes, which contain mature loblolly pine in standing water. The darkest vegetated area in the Chickahominy drainage contains a forest of Nyssa aquatica (water tupelo) about 18 m high, while the darkest vegetated area in the Blackwater marshes contains the marsh plant Spartina alterniflora, 0.3 m high. The density, morphology, and relative geometry of the lowland vegetation with respect to standing water can all affect the strength of the return L band signal.

Krohn, M. D.↗
NASA NTRS1983

Thematic mapper data analysis

The geological applications of remote sensing technology are discussed, with emphasis given to the analysis of data from the Thematic Mapper (TM) instrument onboard the Landsat 4 satellite. The flight history and design characteristics of the Landsat 4/TM are reviewed, and some difficulties endountered in the interpretation of raw TM data are discussed, including: the volume of data; residual noise; detector-to-detector striping; and spatial misregistration between measurements. Preliminary results of several geological, lithological, geobotanical mapping experiments are presented as examples of the geological applications of the TM, and some areas for improving the guality of TM imagery are identified.

Settle, M.↗
NASA NTRS1983

The importance of geobotany in geological remote sensing applications

A description of the different effects of variations in ground cover vegetation on remote sensing data in geological and prospecting applications is presented. The different variations are divided into three categories: structural; taxonomic and spectral. Structural variations include changes in the physical appearance of ground cover which may be detectable by a remote sensing instrument. Taxonomic variations occur in those plant communities which are associated with specific geological regions. Spectral variations are due to specific geochemical stresses which may be useful in characterizing geological features at a site. The need for a general scheme for the interpretation of geobotanical remote sensing data is discussed: Geosat data for the field reflectance spectra of different tree species in West Virginia are presented as examples.

Mouat, D. A.↗