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NASA NTRS1991

The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

Justice, Christopher O.↗

NASA NTRS1991

Spectral modelling of multicomponent landscapes in the Sahel

Simple additive models are used to examine the infuence of differing soil types on the spatial average spectral reflectance and normalized difference vegetation index (NDVI). The spatial average NDVI is shown to be a function of the brightness (red plus near-infrared reflectances), the NDVI, and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of vegetation. The red and near-infrared component reflectances of soil and vegetation are determined on the basis of aerial photoradiometer data from Mali. The relationship between the vegetation component NDVI and plant cover is found to be better than between the NDVI of the entire landscape and plant cover. It is concluded that the usefulness of this modeling approach depends on the existence of clearly distinguishable landscape components.

Hanan, N. P.↗

NASA NTRS1991

Synergism between NOAA-AVHRR and Meteosat data for studying vegetation development in semi-arid West Africa

Rainfall estimates, based on cold cloud duration estimated from Meteosat data, are compared with vegetation development depicted by data of the normalized difference vegetation index (NDVI) from the NOAA AVHRR for part of the Sahel. Decadal data from the 1985 and 1986 growing seasons are examined to determine the synergism of the datasets for rangeland monitoring. There is a general correspondence between the two datasets with a marked lag between rainfall and NDVI of between 10 and 20 days. This time lag is particularly noticeable at the beginning of the rainy season and in the more northern areas where rainfall is the limiting factor for growth. Principal component analysis was used to examine deviations from the general relationship between rainfall and the NDVI. Areas of low NDVI values for a given input of rainfall were identified: at a regional scale, they give an indication o areas of low production potential and possible degradation of ecosystems.

Justice, C. O.↗

NASA NTRS1990

The use of remotely sensed surface temperature and a spectral vegetation index for evaluating heat fluxes over the Konza Prairie

The relationship between surface temperature T(s) and the normalized difference vegetation index (NDVI) is examined to determine whether it can be used to characterize latent heat fluxes (LEs). The regression of T(s) on NDVI is studied in the context of surface heat fluxes over the prairie with a limited data set for four flux-measurement sites. The 17 flux-measurement stations at the sites provided data that are consistently significant at the 99-percent confidence level for the regression of T(s) on NDVI. Variations in the regression slopes are found to correlate with variations in the ground heat flux but not with LE. Important components of the regression of T(s) on NDVI include fractional vegetation cover and surface-soil moisture conditions. The relationship is important for determining the relative contributions of the soil and vegetation components of an area's total evaporative flux.

Hope, A. S.↗

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 NTRS1992

Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model

Relationships are studied between the normalized-difference vegetation index (NDVI) and absorbed photosynthetically active radiation (APAR) in a vegetation canopy. The SAIL model of bidirectional canopy radiative transfer is employed to compare NDVI measurements that are instantaneous with diurnally integrated canopy APAR capacity. The NDVI measurements - taken at solar-zenith angles of more than 60 deg and sensor views of less than 40 deg from nadir - give stable near-linear estimates of diurnal APAR capacity. Discrepancies in the relations between APAR and NDVI are associated with variations in the optical properties of the canopy and with background spectral reflectance. The results are significant for the practical use of these remote sensing techniques but suggest that instantaneous observations can be used to characterize the diurnally integrated APAR in vegetation canopies.

Goward, Samuel N.↗

NASA NTRS1992

Atmospheric correction algorithm for NOAA-AVHRR products - Theory and application

The present evaluation of the effects of atmospheric constituents on NOAA AVHRR visible and near-IR data first gives attention to the general remote sensing equation and then addresses the magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirectional reflectance. Possible approaches to the acquisition of atmospheric data are then considered, and examples of atmospheric correction of surface reflectance and NDVI are discussed. The correction of the aerosol effect is essential in the case of NDVI study of densely vegetated areas.

Tanre, Didier↗

NASA NTRS1992

Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS

ARVI, which is here proposed as a tool for the remote sensing of vegetation by the EOS MODIS sensor, takes advantage of the presence of the blue channel in MODIS, together with the red and near-IR channels composing the normalized-difference vegetation index (NDVI). Unlike the NDVI, ARVI resists atmospheric effects via a self-correction process for the effects of the atmosphere on the red channel. ARVI is presently shown to have a dynamic range similar to NDVI's, but is on average less sensitive to atmospheric effects by a factor of 4. A single combination of the blue and red channels in the ARVI may be used in all or most remote-sensing applications.

Kaufman, Yoram J.↗

NASA NTRS1992

Upscale integration of normalized difference vegetation index - The problem of spatial heterogeneity

An analysis is conducted of the correspondence between the normalized difference vegetation index (NDVI) calculated from average reflectances, or M(NDVI), and the I(NDVI) that is integrated from individual NDVIs, by simulating AVHRR data from high spatial resolution SPOT 1 radiometer and Landsat TM data. The West African and French sites analyzed at 300-1000 m scale show a strong correlation between the two types of index; the relationship is almost perfectly linear, with a slope that is somewhat dependent on vegetation cover. Effecting the scale change using M(NDVI) instead of I(NDVI) does not introduce significant errors.

Aman, Angora↗

NASA NTRS1992

Estimation of photosynthetic capacity using MODIS polarization: 1988 proposal to NASA Headquarters

The remote sensing community has clearly identified the utility of NDVI (normalized difference vegetation index) and SR (simple ratio) and other vegetation indices for estimating such metrics of landscape ecology as green foliar biomass, photosynthetic capacity, and net primary production. Both theoretical and empirical investigations have established cause and effect relationships between the photosynthetic process in plant canopies and these combinations of remotely sensed data. Yet it has also been established that the relationships exhibit considerable variability that appears to be ecosystem-dependent and may represent a source of ecologically important information. The overall hypothesis of this proposal is that the ecosystem-dependent variability in the various vegetation indices is in part attributable to the effects of specular reflection. The polarization channels on MODIS provide the potential to estimate this specularly reflected light and allow the modification of the vegetation indices to better measure the photosynthetic process in plant canopies. In addition, these polarization channels potentially provide additional ecologically important information about the plant canopy.

Vanderbilt, Vern C.↗

NASA NTRS1992

The impact of misregistration on change detection

The impact of images misregistration on the detection of changes in land cover was studied using spatially degraded Landsat MSS images. Emphasis is placed on simulated images of the Normalized Difference Vegetation Index (NDVI) at spatial resolutions of 250 and 500 m. It is pointed out that there is the need to achieve high values of registration accuracy. The evidence from simulations suggests that misregistrations can have a marked effect on the ability of remotely sensed data to detect changes in land cover. Even subpixel misregistrations can have a major impact, and the most marked proportional changes will tend to occur at the finest misregistrations.

Townshend, John R. G.↗

NASA NTRS1992

Remote sensing of vegetation canopy photosynthetic and stomatal conductance efficiencies

The problem of remote sensing the canopy photosynthetic and stomatal conductance efficiencies is investigated with the aid of one- and three-dimensional radiative transfer methods coupled to a semi-empirical mechanistic model of leaf photosynthesis and stomatal conductance. Desertlike vegetation is modeled as clumps of leaves randomly distributed on a bright dry soil with partial ground cover. Normalized difference vegetation index (NDVI), canopy photosynthetic (Ep), and stomatal efficiencies (Es) are calculated for various geometrical, optical, and illumination conditions. The contribution of various radiative fluxes to estimates of Ep is evaluated and the magnitude of errors in bulk canopy formulation of problem parameters are quantified. The nature and sensitivity of the relationship between Ep and Es to NDVI is investigated, and an algorithm is proposed for use in operational remote sensing.

Myneni, R. B.↗

NASA NTRS1993

Functional patterns in an annual grassland during an AVIRIS overflight

This study relates Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery to ground measurements of vegetation distribution, physiology, and productivity at Stanford University's Jasper Ridge Biological Preserve. Primary efforts focused on a 9-ha region of annual grassland where we completed a detailed ground-based study in conjunction with a 15 May 1991 AVIRIS overflight. Spectral mixture analysis and the normalized difference vegetation index (NDVI) calculated from AVIRIS data were used to evaluate spatial patterns of vegetation type, productivity, and potential physiological activity. Concurrent ground sampling revealed a high degree of correlation between NDVI and estimates of canopy chemistry, structure, productivity, and CO2 flux, supporting the use of imaging spectrometry to estimate spatial and temporal trends in vegetation physiology and productivity in this relatively simple grassland ecosystem. Geostatistical analyses of both ground and AVIRIS data supported the conclusion that the AVIRIS pixel size was suitable for describing the influence of major landscape features in this grassland and that spatial detail would be lost at slightly larger pixel sizes typical of other imaging spectrometers.

Gamon, John A.↗

NASA NTRS1993

On the relationship between thermal emissivity and the Normalized Difference Vegetation Index for natural surfaces

The spatial variation of both the thermal emissivity (8-14 microns) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-IR radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0.94. This empirical relationship is of potential use for energy balance studies using thermal IR remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Van De Griend, A. A.↗

NASA NTRS1992

Testing the Li-Strahler four-component canopy reflectance model in the HAPEX-Sahel shrub savanna sites using ground reflectance data

The rate at which a light field decays in water is characterized by the diffuse attenuation coefficient k. The Li-Strahler discrete-object canopy reflectance model was tested in two sites, a shrub grass savanna and a degraded shrub savanna on bare soil, in the proposed HAPEX (Hydrologic Atmospheric Pilot Experiment) II/Sahel study area in Niger, West Africa. Average site reflectance was predicted for each site from the reflectances and cover proportions of four components: shrub canopy, background (soil or grass and soil), shaded canopy, and shaded background. Component reflectances were sampled in the SPOT wavebands using a hand-held radiometer. Predicted reflectance was compared to average site reflectance measured using the same radiometer mounted on a backpack with measurements recorded every 5 m along two 1-km transects, also in the SPOT (Systeme Probatoire d'Observation de la Terre) bands. Measurements and predictions were made for each of the three days during the summer growing season, approximately two weeks apart. Red, near infrared reflectance, and the NDVI (normalized difference vegetation index) were all predicted with a high degree of accuracy for the shrub/grass site and with reasonable accuracy for the degraded shrub site.

Franklin, J.↗

NASA NTRS1993

Red edge spectral measurements from sugar maple leaves

Many sugar maple stands in the northeastern United States experienced extensive insect damage during the 1988 growing season. Chlorophyll data and high spectral resolution spectrometer laboratory reflectance data were acquired for multiple collections of single detached sugar maple leaves variously affected by the insect over the 1988 growing season. Reflectance data indicated consistent and diagnostic differences in the red edge portion (680-750 nm) of the spectrum among the various samples and populations of leaves. These included differences in the red edge inflection point (REIP), a ratio of reflectance at 740-720 nm (RE3/RE2), and a ratio of first derivative values at 715-705 nm (D715/D705). All three red edge parameters were highly correlated with variation in total chlorophyll content. Other spectral measures, including the Normalized Difference Vegetation Index (NDVI) and the Simple Vegetation Index Ratio (VI), also varied among populations and over the growing season, but did not correlate well with total chlorophyll content. Leaf stacking studies on light and dark backgrounds indicated REIP, RE3/RE2 and D715/D705 to be much less influenced by differences in green leaf biomass and background condition than either NDVI or VI.

Vogelmann, J. E.↗

NASA NTRS1993

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Mcgwire, K.↗

NASA NTRS1993

The use of a vegetation index for assessment of the urban heat island effect

A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

Gallo, K. P.↗