Carol A. Wessman

Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis

Accuracy of vegetation cover fractions, computed with spectral mixture analysis, may be compromised by variation in canopy structure and biochemistry when a single endmember represents top-of-canopy reflectance. In this article, endmember variability is incorporated into mixture analysis by representing each endmember by a set or bundle of spectra, each of which could reasonably be the reflectance of an instance of the endmember. Endmember bundles are constructed from the data itself by an extension to a previously described method of manually deriving endmembers from remotely sensed data. Applied to remotely sensed images, bundle unmixing produces maximum and minimum fraction images bounding the correct cover fractions and specifying error due to endmember variability. In this article, endmember bundles and bounding fraction images were created for an airborne visible/infrared imaging spectrometer (AVIRIS) subscene simulated with a canopy radiative transfer/geometric-optical model. Variation in endmember reflectance was achieved using ranges of parameter values including leaf area index (LAI) and tissue optical properties observed In a North Texas savanna. The subscenes spatial pattern was based on a 1992 Landsat Thematic Mapper image of the study region. Bounding fraction images bracketed the cover fractions of the simulated data for 98% of the pixels for soil, 97% for senescent grass and 93% for trees. Averages of bounding images estimated fractional coverage used in the simulation with an average error of /spl les/0.05, a significant improvement over previous methods with important implications for regional-scale research on vegetation extent and dynamics.

Long-term studies of snow-vegetation interactions

Relationships among vegetation, wind, snow, and temperature regimes may help predict effects of climate change. This paper presents a hierarchic geographic information system (HGIS) which helps examine links between species distributions at the plot level, at the level of landscape patterns of plant communities, and at the level of regional patterns of greeness. Geographically referencing ecological data, mapping techniques, landscape and regional scale mapping, and linking ground-level observations to remotely sensed information are all discussed. Results include discussion of specific plant species-snow relationships, landscape-level patterns of specific plant communities, regional patterns of the normalized difference vegetation index (NDVI), and linking patterns to variations in climate or direct anthropogenic impacts. 50 refs., 12 figs., 3 tabs.

Remote sensing of forest canopy and leaf biochemical contents

Abstract Remote detection and measurement of the nitrogen and lignin contents of forest canopies could allow predictions of biogeochemical processes such as productivity, decomposition, and nutrient turnover rates. Spectral absorption features characteristic of proteins (containing nitrogen), lignin and other leaf constituents occur throughout the shortwave infrared region (1200–2400 nm). The lignin and nitrogen concentration of dried and ground deciduous leaves have been predicted from reflectance spectra obtained in the laboratory. The optimum wavelengths for prediction were selected using stepwise multiple linear regression. The prediction errors were comparable to chemical techniques. Analysis of the reflectance spectra of fresh, whole leaves has been limited thus far to conifer leaves but indicate spectral features predictive of nitrogen and lignin also found in airborne spectra. Airborne Imaging Spectrometer (AIS) were evaluated for whole forest canopy physical and chemical properties. Variations in spectral brightness were associated with variations in total water content of the foliar biomass. Comparison of forest spectra with spectrally flat targets revealed absorption features common to the canopy spectra between 1500 and 1700 nm which were tentatively attributed to absorption by lignin and starch. The AIS and laboratory data indicate strongly that absorption in the infrared region is influenced by biochemical characteristics.

Impact of Tissue, Canopy, and Landscape Factors on the Hyperspectral Reflectance Variability of Arid Ecosystems

Changes in vegetation distribution and condition commonly occur in arid ecosystems due to land use and climate variability. Most arid land remote sensing efforts have focused on detecting vegetation change using spectral indices, such as the normalized vegetation index, with limited success. Less attention has focused on using the continuous shortwave spectrum (0.4 μm to 2.5 μm) for studying vegetation in arid environments. Using field measurements and a photon transport model, we quantified the absolute and relative importance of tissue, canopy, and landscape factors that drive pixel-level shortwave reflectance variation along a land-cover gradient in the Chihuahuan Desert, New Mexico. Green foliage, wood, standing litter, and bare soil had distinctive spectral properties, often via specific, narrow absorption features and through overall differences in the shape of their shortwave spectra. While the amount of each plant material varied significantly along the land-cover gradient, foliar optical properties remained relatively stable, supporting the hypothesis that resource variation (e.g., water and nutrients) is more strongly resolved at the scale of whole plant canopies (e.g., via allocation and production) than at the leaf level. Significant variation in vegetation type and condition along the gradient resulted in only subtle changes in pixel-level reflectance variability, which could be determined in high spectral resolution Airborne Visible and Infrared Imaging Spectrometer data. Most important, the relative impact of tissue, canopy, and landscape factors on pixel-level reflectance shifted with plant composition and phenology. We compared the ability to resolve these vegetation and soil factors using Airborne Visible and Infrared Imaging Spectrometer, Moderate Resolution Imaging Spectrometer, and Landsat Thematic Mapper optical channels and found that few factors could be accounted for unless most of the spectral range was adequately sampled.

Textural analysis of historical aerial photography to characterize woody plant encroachment in South African Savanna

Transitions from grassland to shrubland through woody plant encroachment result in potentially significant shifts in savanna ecosystem function. Given high resolution imagery, a textural index could prove useful for mapping woody plant densities and monitoring woody plant encroachment across savanna landscapes. Spatial heterogeneity introduced through mixtures of herbaceous and woody plants challenges quantitative assessments of changing woody plant density using remotely sensed imagery. Moreover, woody plant encroachment occurs across decadal time scales, restricting remote sensing analyses to historical aerial photograph records. Heterogeneity in vegetation structure has a significant influence on local pixel variance in high resolution images. We scanned black and white aerial photographs for 18 sites of varying woody plant density, producing images of 2-m grain size. Omnidirectional variograms derived from these images had ranges of approximately 10 m and sills highly sensitive to woody plant density, prompting us to use a textural index to indicate landscape variation in woody plant density. For validation purposes, we measured several woody overstory structural parameters in the field; a factor analysis revealed woody stem count as the best correlate with image texture. Significance of the regression of image texture on woody stem count declined as grain size of the 2-m images was coarsened to simulate that of SPOT and Landsat satellite sensors. At 10-m resolution, our textural index proved a significant indicator of woody plant density. We mosaicked sequential aerial photographs scanned at 10-m resolution and then applied our textural filter, producing maps of historical woody plant distribution that reflected patterns in soil and vegetation type. More accurate maps of canopy structure and structural change are needed to explore potential effects of woody plant encroachment on biophysical and biogeochemical processes at large scales.

Ecological Research Needs from Multiangle Remote Sensing Data

Abstract Remotely sensed land surface reflectance depends upon changing sun and sensor viewing geometry, and this dependence is governed by the bidirectional reflectance distribution function (BRDF). Because the reflectance distribution of vegetation is strongly anisotropic, multi-view angle (MVA) observations of terrestrial ecosystems contain additional and unique information beyond that acquired with nadir or single-angle spectral measurements alone. With the NASA EOS instruments MODIS and MISR and Frances POLDER, new capabilities in MVA remote sensing will become widely available for ecological, biogeochemical, and land-surface biophysical research. However, a communication gap exists between the remote sensing and ecological communities in terms of the capabilities of the former and the needs of the latter. In this article, we present a summary of ecological research needs for remotely sensed data. Based on these needs, we present a review of some of the most promising MVA remote sensing methods for fulfilling these requirements. With this article, we hope to facilitate increased communication between the remote sensing, ecological, and biogeochemical research communities.

Variability in Leaf and Litter Optical Properties: Implications for BRDF Model Inversions Using AVHRR, MODIS, and MISR

Abstract Canopy radiative transfer models simulate the bidirectional reflectance distribution function (BRDF) of vegetation covers with differing leaf and soil spectral and canopy structural characteristics. Numerical inversion of these models has provided estimates of vegetation structural and biophysical characteristics from multiangle, remotely sensed optical data. The number of angularly unique observations compared to BRDF model parameters largely determines the accuracy of retrievals. To increase this ratio, additional observations of a target must be acquired and the BRDF models and inversions must be simplified. The former will occur when the EOS instruments become available. Previous studies suggest that simplification of BRDF model inversions may best be accomplished by constraining the leaf optical parameters. This study focused on full-range (400–2500 nm) leaf and litter spectral properties convolved to AVHRR, MODIS, and MISR optical channels. Using a diverse array of woody plant and grass species, we found robust and readily usable interrelationships among spectra through correlation, regression, and principal components analyses. Significant differences between green leaf and litter optical properties and their sensor-specific interrelationships indicate that green leaf optical constraints may be useful with BRDF retrievals to detect the onset of canopy senescence. These findings will provide increased efficiency in canopy BRDF model inversions by decreasing the number of observations required to retrieve canopy structural and biophysical information from multiangle remotely sensed data.

SCALE DEPENDENCE OF ABSORPTION OF PHOTOSYNTHETICALLY ACTIVE RADIATION IN TERRESTRIAL ECOSYSTEMS

The fraction of photosynthetically active radiation absorbed by plant can- opies (fAPAR) is a critical biophysical variable for extrapolating ecophysiological mea- surements from the leaf to landscape scale. Quantification of fAPAR determinants at the landscape level is needed to improve the interpretation of remote sensing data, to facilitate its use in constraining ecosystem process models, and to improve synoptic-scale links between carbon and nutrient cycles. Most canopy radiation budget studies have focused on light attenuation in plant canopies, with little regard for the importance of the scale- dependent biophysical and structural factors (e.g., leaf and stem optical properties, leaf and stem area, and extent of vegetation structural types) that ultimately determine fAPAR at canopy and landscape scales. Most studies have also assumed that nonphotosynthetic veg- etation (litter and stems) contributes little to fAPAR. Using a combined field measurement and radiative transfer modeling approach, we quantified (a) the relative role of the leaf-, canopy-, and landscape-level factors that determine fAPAR in terrestrial ecosystems and (b) the magnitude of PAR absorption by grass litter and woody plant stems. Variability in full spectral-range (400-2500 nm) reflectance/transmittance and PAR (400-700 nm) absorption at the level of individual leaf, stem, and litter samples was quantified for a wide array of broadleaf arborescent and grass species along a 900-km north-south Texas savanna transect. Among woody growth forms, leaf reflectance and transmittance spectra were statistically comparable between populations, species within a genus, and functional types (deciduous vs. evergreen, legume vs. nonlegume). Within the grass life-form, spectral properties were statistically comparable between species and C3/C4 physiologies. We found that tissue-level PAR absorption among species, genera, functional groups, and growth forms and between climatologically diverse regions was statistically similar, and for fresh leaves, it represented the most spectrally similar region of the short- wave spectrum. Subsequent modeling analyses indicated that the measured range of leaf, woody stem, and litter optical properties explained only a small proportion of the variance in tree and grass canopy fAPAR. However, the presence of nonphotosynthetic vegetation (e.g., stem and litter) had a significant effect on canopy fAPAR. In trees with a leaf area index (LAI) <3.0, stem surfaces increased canopy fAPAR by 10-40%. Standing grass litter canopies absorbed almost as much PAR as green grass canopies. Modeling the radiation regime in plant canopies should therefore account for the absorption of PAR by nonphotosynthetic plant components. Failure to do so may lead to overestimates of primary production, es- pecially in woodlands, savannas, and shrublands dominated by species with optically thin canopies and in grasslands that accumulate senescent material. Further sensitivity analyses revealed that the extent and LAI of vegetation structural types (trees and grasses) were the dominant controls on savanna landscape-level fAPAR, accounting for 60-80% of the total variation. Variation in leaf-level and all other canopy- level factors contributed individually to explain only a small proportion (<11%) of the variance in landscape fAPAR; however, when considered as a group, they accounted for 20-40% of the variation in landscape fAPAR. These results emphasize the need for more mechanistic analyses of canopy-level radiative transfer, and subsequent carbon flux and trace gas processes, in plant canopies and across landscapes comprising heterogeneous mixtures of plant growth forms and life-forms.

Woody plants in grasslands: post-encroachment stand dynamics.

Woody plant abundance is widely recognized to have increased in savannas and grasslands worldwide. The lack of information on the rates, dynamics, and extent of increases in shrub abundance is a major source of uncertainty in assessing how this vegetation change has influenced biogeochemical cycles. Projecting future consequences of woody cover change on ecosystem function will require knowledge of where shrub cover in present-day stands lies relative to the realizable maximum for a given soil type within a bioclimatic region. We used time-series aerial photography (1936, 1966, and 1996) and field studies to quantify cover and biomass of velvet mesquite (Prosopis velutina Woot.) following its proliferation in a semidesert grassland of Arizona. Mapping of individual shrubs indicated an encroachment phase characterized by high rates of bare patch colonization. Upon entering a stabilization phase, shrub cover increases associated with recruitment and canopy expansion were largely offset by contractions in canopy area of other shrub patches. Instances of shrub disappearance coincided with a period of below-average rainfall (1936-1966). Overall, shrub cover (mean +/- SE) on sandy uplands with few and widely scattered shrubs in 1902 was dynamically stable over the 1936-1996 period averaging approximately 35% +/- 5%. Shrub cover on clayey uplands in 1936 was 17% +/- 2% but subsequently increased twofold to levels comparable to those on sandy uplands by 1966 (36% +/- 7%). Cover on both soils then decreased slightly between 1966 and 1996 to 28% +/- 3%. Thus, soil properties influenced the rate at which landscapes reached a dynamic equilibrium, but not the apparent endpoint. Although sandy and clayey landscapes appear to have stabilized at comparable levels of cover, shrub biomass was 1.4 times greater on clayey soils. Declines in shrub cover between 1966 and 1996 were accompanied by a shift to smaller patch sizes on both sandy and clayey landscapes. Dynamics observed during the stabilization phase suggest that density-dependent regulation may be in play. If woody cover has transitioned from directional increases to a dynamic equilibrium, biomass projections will require monitoring and modeling patch dynamics and stand structure rather than simply changes in total cover.

An evaluation of imaging spectrometry for estimating forest canopy chemistry

Abstract High spectral resolution Airborne Imaging Spectrometer (AIS) data were acquired over 20 well-studied Wisconsin forest sites to evaluate the potential of remote sensing for estimating forest canopy chemistry. Intensive nutrient cycling research in these forests demonstrates that canopy lignin content is strongly related to measured annual nitrogen mineralization at the undisturbed sites and may serve as an accurate index for nitrogen cycling rates. Ground measurements were made of foliar biomass and canopy nitrogen and lignin content, the latter within two weeks of the AIS overflight. The spectral data were transformed using derivative techniques modified from laboratory spectroscopy. Stepwise regression assisted in determining combinations of wavelengths most highly correlated with canopy chemistry and biomass. Strong correlations between AIS data and total canopy lignin content in deciduous forests and canopy lignin concentration (total lignin/biomass) in both deciduous and coniferous stands ind...