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Barber, J.

Publications and source records attributed to Barber, J..

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

The red edge of plant leaf reflectance

A detailed study of the red edge spectral feature of green vegetation based on laboratory reflectance spectrophotometry is presented. A parameter lambda is defined as the wavelength is defined as the wavelength of maximum slope and found to be dependent on chlorophyll concentration. Species, development stage, leaf layering, and leaf water content of vegetation also influences lambda. The maximum slope parameter is found to be independent of simulated ground area coverage. The results are interpreted in terms of Beer's Law and Kubelka-Munk theory. The chlorophyll concentration dependence of lambda seems to be explained in terms of a pure absorption effect, and it is suggested that the existence of two lambda components arises from leaf scattering properties. The results indicate that red edge measurements will be valuable for assessment of vegetative chlorophyll status and leaf area index independently of ground cover variations, and will be particularly suitable for early stress detection.

Horler, D. N. H.↗
NASA NTRS1983

Approaches to detection of geochemical stress in vegetation

Work has been carried out to elucidate fundamental relationships between spectral properties of plants and geochemical stress, and a programme of field and laboratory work is in progress. The most significant results and conclusions at this stage are described and attention is focused on the new concepts for stress detection which have been generated. The applications of the research are relevant to the understanding of current remotely sensed data as well as relating to ideas for new instrumentation.

Horler, D. N. H.↗
NASA NTRS1983

Red edge measurements for remotely sensing plant chlorophyll content

The feasibility of using the wavelength of the maximum slope of the red edge of leaf reflectance spectra, Lambda(re), as an indication of plant chlorophyll status was examined in the laboratory for single leaves of several species. Lambda(re) for each sample was determined by derivative reflectance spectroscopy. A high positive correlation was found between Lambda(re) and leaf chlorophyll content for all species, although there were some differences in the quantitative nature of the relationship for plants of different types. The position of the red edge was found to be unaffected by simulated change in ground cover, but multiple leaf layers produced a shift in its position. Appropriate spectral measurements and processing for obtaining useful information from the red edge are discussed, and the potential of the red edge in relation to other spectral measurements is considered.

Horler, D. N. H.↗
NASA NTRS1980

Effects of heavy metals on the absorbance and reflectance spectra of plants

The spectral responses of plants to various concentrations of heavy metals in their rooting media are investigated in relation to the application of remote sensing methods to the detection of vegetation under stress. Absorption photometry of chloroplasts, measurements of metal and chlorophyll concentrations and reflectance spectrometry were performed on leaves of pea, sunflower and soybean plants grown under greenhouse conditions with the addition of various concentrations of Cd, Cu, Pb and Zn to their rooting media and on leaves of oak trees growing naturally in an area of a copper-arsenic mineralization. Under laboratory conditions, the most general effect observed was growth inhibition and ultimately death, with pea plants also exhibiting changes of chlorophyll a/ chlorophyll b ratios with Cd and Cu and reflectance increases in the visible and decreases in the infrared. Although results for other species indicate that reflectance effects are dependent on species, correlations between reflectance and metal exposure is confirmed by the field investigations. It is concluded that a remote sensing system would be improved by the inclusion of bands around 1.65 and 2.20 microns to detect soil mineralization from plant spectra.

Horler, D. N. H.↗