Engineering topics

Curran, Paul J.

Publications and source records attributed to Curran, Paul J..

At least 19 records

NASA NTRS2003

The Biosphere: A Decadal Vision

This paper focuses on biosphere-climate interactions including the influences of human activities. Recognizing this is only one aspect of biospheric processes, this places an emphasis of those biogeochemical processes that have a profound effect on numerous other aspects of the biosphere and the services it provides, services which are critical to sustaining life on Earth. And, the paper will focus on the various scientific aspects of assessing the availability of fresh water, including its sensitivity to climate variance and land use changes. Finally, this paper hopes to emphasize the potential role that greatly expanded space observations and interactive modeling can play in developing our understanding of Earth and its the living systems.

Peterson, David L.↗

NASA NTRS1995

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression.

Dawson, Terence P.↗

NASA NTRS1993

AVIRIS spectra correlated with the chlorophyll concentration of a forest canopy

Imaging spectrometers have many potential applications in the environmental sciences. One of the more promising applications is that of estimating the biochemical concentrations of key foliar biochemicals in forest canopies. These estimates are based on spectroscopic theory developed in agriculture and could be used to provide the spatial inputs necessary for the modeling of forest ecosystem dynamics and productivity. Several foliar biochemicals are currently under investigation ranging from those with primary absorption features in visible to middle infrared wavelengths (e.g., water, chlorophyll) to those with secondary to tertiary absorption features in this part of the spectrum (e.g., nitrogen, lignin). The foliar chemical of interest in this paper is chlorophyll; this is a photoreceptor and catalyst for the conversion of sunlight into chemical energy and as such plays a vital role in the photochemical synthesis of carbohydrates in plants. The aim of the research reported here was to determine if the chlorophyll concentration of a forest canopy could be correlated with the reflectance spectra recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Kupiec, John↗

NASA NTRS1993

The effect of signal noise on the remote sensing of Foliar biochemical concentration

Spectral measurements made using an imaging spectrometer contain systematic and random noise, while the former can be corrected the latter remains a source of error in the remotely sensed signal. A number of investigators have tried to determine the signal-to-noise-ratio (SNR) of the instrument, or the resultant imagery. However, the level of noise at which spectra are too noisy to be useful is not usually determined. The first attempt was by Goetz and Calvin, who suggested that the depth of the absorption feature should be at least an order of magnitude greater than the noise and more recently Dekker suggested a SNR of around 600:1 was required in visible/near infrared wavelengths to measure a 1/gl change in chlorophyll a concentration water. The wide range of applications of imaging spectroscopy make it difficult to set SNR specifications as they are dependent on a number of factors, one of the most important being reflectance of a particular target. For example, the SNR of imagery for vegetated targets is relatively low simply because vegetation has a relatively low level of reflectance. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being used to estimate the concentration of biochemicals within vegetation canopies. This paper reports a study undertaken to identify first, wavebands that were highly correlated with foliar biochemical concentration and second, to determine how sensitive these correlations were to sensor noise.

Smith, Geoffrey M.↗

NASA NTRS1993

Leaf Areas And Spectral Properties Of Slash Pine

NASA technical memorandum describes experiments to test feasibility of estimating seasonal leaf areas of forest canopies from spectral radiances measured by remote instruments. Accurate estimates of seasonal leaf areas of forests necessary for studies of seasonal exchanges of energy between forest canopies and atmosphere. Potential use of remote sensing in estimating seasonal changes in leaf area index (LAI).

Curran, Paul J.↗

NASA NTRS1992

Classification Of Land Cover From Airborne MSS Data

Method for processing images of rural uplands produced by airborne multispectral scanner (MSS), semiautomatically classifies types of land cover, and involves selection of wavelength bands, radiometric calibration, correction for effects of scan angle and atmosphere, training, and assessment of accuracy. Basic version involves classification of each picture element according to spectrum. Augmented with five refinements to increase accuracy: per-field sampling; low-pass filtering; image texture; prior probabilities; and imagery from two dates.

Curran, Paul J.↗

NASA NTRS1992

Exploring the remote sensing of foliar biochemical concentrations with AVIRIS data

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data shows promise for the estimation of foliar biochemical concentrations at the scale of the canopy. There are, however, several problems associated with the use of AVIRIS data in this way and these are detailed in recent Plant Biochemical Workshop Report. The research reported was concentrated upon three of these problems: field sampling of forest canopies, wet laboratory assay of foliar chemicals, and the visualization of AVIRIS data.

Smith, Geoffrey M.↗

NASA NTRS1992

Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration

Remotely sensed plant-canopy data in the visible and near-IR ranges are used to establish relations between the canopy reflectance and the chemical content of the leaves. The mathematical relation is generated by means of stepwise regression based on the derivative reflectance at certain wavelengths. Fourier filtering and sample control are used to minimize instrument noise and spectral overlap respectively, and absorption features are noted that correspond to sugar and protein. The coefficients of determination between estimated and measured concentrations are at least 0.82 for such substances as starch and chlorophyll. It is recommended in the analysis of remotly sensed canopy data that the chemicals with strong spectral overlaps with the chemical of interest be accounted for in order to estimate foliar chemical concentrations accurately.

Curran, Paul J.↗

NASA NTRS1992

Seasonal LAI in slash pine estimated with Landsat TM

The leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LAI seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values derived using Lnandsat Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on 3 dates. Linear relationships existed between NDVI and LAI with R (sup 2) values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March, 1989, respectively. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass. Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6 percent of the mean LAI. This demonstrates the potential use of Landsat TM data for studying seasonal dynamics in forest canopies.

Curran, Paul J.↗

NASA NTRS1991

Estimating The SNR Of AVIRIS Data

Combination of established statistical and filtering techniques yields improved estimates of signal-to-noise ratio (SNR) of multispectral imagery produced by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Method yields more accurate estimate of random variability in AVIRIS imagery. Combination of techniques called "geostatistical" method. In first step of method, periodic noise removed by notch filtering in frequency domain. In subsequent steps, sensor noise and variability within picture elements isolated by use of semi-variance of picture elements.

Curran, Paul J.↗

NASA NTRS1991

The effect of a red leaf pigment on the relationship between red edge and chlorophyll concentration

The effect of a leaf pigment - red amaranthin - on red edge and chlorophyll concentration is investigated in amaranth leaves by means of treatments with nitrate and salts. A near-linear relationship between red edge and chlorophyll concentration is observed for leaves with low amaranthin concentration, and no relationship is noted at high concentrations. The study demonstrates the limitation inherent in estimating chlorophyll concentration by using remotely sensed red edge.

Curran, Paul J.↗

NASA NTRS1990

Airborne MSS for land cover classification II

A basic methodology for land cover classification using airborne multispectral scanner (MSS) imagery is outlined. This includes waveband selection and radiometric calibration; correction for scan angle and atmosphere; training and classification and accuracy assessment. Refinements to this basic methodology include per-field sampling and the addition of low-pass filtering, image texture, prior probabilities and two dates of imagery. For a study area in upland England, eight land covers were classified with a mean accuracy of 52.6 percent using the basic methodology. This was increased to 79.0 percent by using a suitability refined methodology. Per-field sampling accounted for the largest proportion of this increase.

Curran, Paul J.↗

NASA NTRS1990

An image recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

The airborne visible/infrared imaging spectrometer (AVIRIS) is described, and an example of a false-color image recorded by this device is provided. The AVIRIS is capable of sensing in 209 visible and near-infrared wavebands with an 11km swath and a 20m spatial resolution. Evaluation flights for AVIRIS were made at an altitude of approximately 20km x 10.2km of low-lying and relatively flat irrigated land near Yuba City and Sacramento, California. Raw data were converted from digital numbers to radiance and radiometrically corrected at the NASA Jet Propulsion Laboratory. Notch filtering in the frequency domain of the image was used to remove periodic noise. The illustration of both spatial and spectral properties on the false-color image are explained. AVIRIS is designed to be flown in an ER-2 aircraft and will serve as a test-bed sensor for the High-Resolution Imaging Spectrometer (HIRIS) planned for the Earth Observing System.

Curran, Paul J.↗

NASA NTRS1990

Seasonal LAI in slash pine estimated with LANDSAT TM

The leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LAI seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values derived using LANDSAT Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on 3 dates. Linear relationships existed between NDVI and LAI with R(sup 2) values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March, 1989, respectively. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass. Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6 percent of the mean LAI. This demonstrates the potential use of LANDSAT TM data for studying seasonal dynamics in forest canopies.

Curran, Paul J.↗

NASA NTRS1990

Exploring the Relationship Between Reflectance Red Edge and Chlorophyll Content in Slash Pine

Chlorophyll is a key indicator of the physiological status of a forest canopy. However, its distribution may vary greatly in time and space, so that the estimation of chlorophyll content of canopies or branches by extrapolation from leaf values obtained by destructive sampling is labor intensive and potentially inaccurate. Chlorophy11 content is related positively to the point of maximum slope in vegetation reflectance spectra which occurs at wavelengths between 690-740 nm and is known as the "red edge." The red edge of needles on individual slash pine (Piniis elliottii Engelm.) branches and in whole forest canopies was measured with a spectroradiometer. Branches were measured on the ground against a spectrally flat reflectance target and canopies were measured from observation towers against a spectrally variable understory and forest floor. There was a linear relationship between red edge and chlorophyll content of branches (R(exp 2) = 0.91). Measurements of the red edge and this relationship were used to estimate the chlorophyll content of other branches with an error that was lower than that associated with the colorimetric (laboratory) method. There was no relationship between the red edge and the chlorophyll content of whole canopies. This can be explained by the overriding influence of the understory and forest floor, an influence that was illustrated by spectral mixture modeling. The results suggest that the red edge could be used to estimate the chlorophyll content in branches but it is unlikely to be of value for the estimation of chlorophyll content in canopies unless the canopy cover is high.

Curran, Paul J.↗

NASA NTRS1989

Remote sensing of foliar chemistry

Remotely sensed data are being used to estimate foliar chemical content. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content.

Curran, Paul J.↗

NASA NTRS1989

Estimation of signal-to-noise - A new procedure applied to AVIRIS data

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Curran, Paul J.↗

NASA NTRS1988

Estimating the signal-to-noise ratio of AVIRIS data

Curran, Paul J.↗