Mapping carbon and water vapor fluxes in a chaparral ecosystem using vegetation indices derived from AVIRIS

Using simple models derived from spectral reflectance, we mapped the patterns of ecosystem CO₂ and water fluxes in a semi-arid site in southern California during a period of extreme disturbance, marked by drought and fire. Employing a combination of low (∼ 2 km) and high (∼ 16 km) altitude images from the hyperspectral Airborne Visible Infrared Imaging Spectrometer (AVIRIS), acquired between April 2002 and September 2003, and ground data collected from an automated tram system, several vegetation indices were calculated for Sky Oaks field station, a FLUXNET and SpecNet site located in northern San Diego County (CA, USA). Based on the relationships observed between the fluxes measured by the eddy covariance tower and the vegetation indices, net CO₂ and water vapor flux maps were derived for the region around the flux tower. Despite differences in the scale of the images (from ∼ 2 m to 16 m pixel size) as well as marked differences in environmental conditions (drought in 2002, recovery in early 2003, and fire in mid 2003), net CO₂ and water flux modeled from AVIRIS-derived reflectance indices (NDVI, PRI and WBI) effectively tracked changes in tower fluxes across both drought and fire, and readily revealed spatial variation in fluxes within this landscape. After an initial period of net carbon uptake, drought and fire caused the ecosystem to lose carbon to the atmosphere during most of the study period. Our study shows the power of integrating optical and flux data in LUE models to better understand factors driving surface-atmosphere carbon and water vapor flux cycles, one of the main goals of SpecNet.     

A thermal-based remote sensing technique for routine mapping of land-surface carbon,water and energy fluxes from field to regional scales

Robust yet simple remote sensing methodologies for mapping instantaneous land-surface fluxes of water, energy and CO₂ exchange within a coupled framework add significant value to large-scale monitoring networks like FLUXNET, facilitating upscaling of tower flux observations to address questions of regional carbon cycling and water availability. This study investigates the implementation of an analytical, light-use efficiency (LUE) based model of canopy resistance within a Two-Source Energy Balance (TSEB) scheme driven primarily by thermal remote sensing inputs. The LUE model computes coupled canopy-scale carbon assimilation and transpiration fluxes, and replaces a Priestley–Taylor (PT) based transpiration estimate used in the original form of the TSEB model. In turn, the thermal remote sensing data provide valuable diagnostic information about the sub-surface moisture status, obviating the need for precipitation input data and prognostic modeling of the soil water balance. Both the LUE and PT forms of the model are compared with eddy covariance tower measurements acquired in rangeland near El Reno, OK. The LUE method resulted in improved partitioning of the surface energy budget, capturing effects of midday stomatal closure in response to increased vapor pressure deficit and reducing errors in half-hourly flux predictions from 16 to 12%. The spatial distribution of CO₂ flux was mapped over the El Reno study area using data from an airborne thermal imaging system and compared to fluxes measured by an aircraft flying a transect over rangeland, riparian areas, and harvested winter wheat. Soil respiration contributions to the net carbon flux were modeled spatially using remotely sensed estimates of soil surface temperature, soil moisture, and leaf area index. Modeled carbon and water fluxes from this heterogeneous landscape compared well in magnitude and spatial pattern to the aircraft fluxes. The thermal inputs proved to be valuable in modifying the effective LUE from a nominal species-dependent value. The model associates cooler canopy temperatures with enhanced transpiration, indicating higher canopy conductance and carbon assimilation rates. The surface energy balance constraint in this modeling approach provides a useful and physically intuitive mechanism for incorporating subtle signatures of soil moisture deficiencies and reduced stomatal aperture, manifest in the thermal band signal, into the coupled carbon and water flux estimates.     

Water interception by canopies for remote sensing based evapotranspiration models

ABSTRACT

Evaporation of intercepted water by canopies accounts for a non-negligible portion of total land surface evapotranspiration. While monitoring evapotranspiration from space technology is increasingly demanded, most evapotranspiration retrieval algorithms face the problem of providing accurate estimation of evaporation from canopy interception. Because of the operations constraints or of the uncertain quality of the near-real-time rainfall estimates from satellites, the implementation of a diagnostic method is preferred to a dynamical model based on a differential equation ruling the evolution of the water storage on the canopy. In this contribution, an empirical model detecting and quantifying intercepted water on canopies, based on one meteorological variable, is optimized with forecasts from a general circulation model. This diagnostic model of interception is implemented in an evapotranspiration retrieval algorithm using mostly space measurements and its impact is commented.     

Effective tree scattering and opacity at L-band

This paper investigates vegetation effects at L-band by using a first-order radiative transfer (RT) model and truck-based microwave measurements over natural conifer stands to assess the applicability of the τ ? ω (tau–omega) model over trees. The tau–omega model is a zero-order RT solution that accounts for vegetation effects with two vegetation parameters (vegetation opacity and single-scattering albedo), which represent the canopy as a whole. This approach inherently ignores multiple-scattering effects and, therefore, has a limited validity depending on the level of scattering within the canopy. The fact that the scattering from large forest components such as branches and trunks is significant at L-band requires that zero-order vegetation parameters be evaluated (compared) along with their theoretical definitions to provide a better understanding of these parameters in the retrieval algorithms as applied to trees.This paper compares the effective vegetation opacities, computed from multi-angular pine tree brightness temperature data, against the results of two independent approaches that provide theoretical and measured optical depths. These two techniques are based on forward scattering theory and radar corner reflector measurements, respectively. The results indicate that the effective vegetation opacity values are smaller than but of similar magnitude to both radar and theoretical estimates. The effective opacity of the zero-order model is thus set equal to the theoretical opacity and an explicit expression for the effective albedo is then obtained from the zero- and first-order RT model comparison. The resultant albedo is found to have a similar magnitude as the effective albedo value obtained from brightness temperature measurements. However, both are less than half of the single-scattering albedo estimated using the theoretical calculations (0.5?0.6 for tree canopies at L-band). This lower observed effective albedo balances the scattering darkening effect of the large theoretical single-scattering albedo with a first-order multiple-scattering contribution. The retrieved effective albedo is different from theoretical definitions and not the albedo of single forest elements anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy, including multiple-scattering and canopy ground interaction.     

MODIS spectral signals at a flux tower site: Relationships with high-resolution data, and CO2 flux and light use efficiency measurements

In this study, spectral indices were calculated from single date HyMap (3 m; 126 bands), Hyperion (30 m; 242 bands), ASTER (15/30 m; 9 bands), and a time series of MODIS nadir BRDF-adjusted reflectance (NBAR; 1 km, 7 bands) for a study area surrounding the Tumbarumba flux tower site in eastern Australia. The study involved: a) the calculation of a range of physiologically-based vegetation indices from ASTER, HyMap, Hyperion and MOD43B NBAR imagery over the flux tower site; b) comparison across scales between HyMap, Hyperion and MODIS for the normalized difference water index (NDWI) and the Red-Green ratio; c) analysis of relationships between tower-based flux and light use efficiency (LUE) measurements and seasonal and climatic constraints on growth; and d) examination of relationships between fluxes, LUE and time series of NDVI, NDWI and Red-Green ratio. Strong seasonal patterns of variation were observed in NDWI and Red/Green ratio from MODIS NBAR. Correlations between fine (3 and 30 m) and coarse (1 km) scale indices for a small region around the flux tower site were moderately good for Red/Green ratio, but poor for NDWI. Hymap NDWI values for the understorey canopy were much lower than values for the tree canopy. MODIS NDWI was negatively correlated with CO₂ fluxes during warm and cool seasons. The correlation indicated that surface reflectance, affected by a spectrally bright grassland understorey canopy, was decoupled from growth of trees with access to deep soil moisture. The application of physiologically-based indices at earth observation scale requires careful attention to applicability of band configurations, contribution of vegetation components to reflectance signals, mechanistic relationships between biochemical processes and spectral indexes, and incorporation of ancillary information into any analysis.     

Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations

Models estimating surface energy fluxes over partial canopy cover with thermal remote sensing must account for significant differences between the radiometric temperatures and turbulent exchange rates associated with the soil and canopy components of the thermal pixel scene. Recent progress in separating soil and canopy temperatures from dual angle composite radiometric temperature measurements has encouraged the development of two-source (soil and canopy) approaches to estimating surface energy fluxes given observations of component soil and canopy temperatures. A Simplified Two-Source Energy Balance (STSEB) model has been developed using a “patch” treatment of the surface flux sources, which does not allow interaction between the soil and vegetation canopy components. A simple algorithm to predict the net radiation partitioning between the soil and vegetation is introduced as part of the STSEB patch modelling scheme. The feasibility of the STSEB approach under a full range in fractional vegetation cover conditions is explored using data collected over a maize (corn) crop in Beltsville Maryland, USA during the 2004 summer growing season. Measurements of soil and canopy component temperatures as well as the effective composite temperature were collected over the course of the growing season from crop emergence to cob development. Comparison with tower flux measurements yielded root-mean-square-difference values between 15 and 50 W m^− 2 for the retrieval of the net radiation, soil, sensible and latent heat fluxes. A detailed sensitivity analysis of the STSEB approach to typical uncertainties in the required inputs was also conducted indicating greatest model sensitivity to soil and canopy temperature uncertainties with relative errors reaching ∼ 30% in latent heat flux estimates. With algorithms proposed to infer component temperatures from bi-angular satellite observations, the STSEB model has the capability of being applied operationally.     

Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0-13.5 μm) imagery

High spatial and spectral resolution thermal infrared imagery (8.0-13.5 μm) from the SEBASS airborne sensor was used to analyze and map tree canopy spectral features at the State Arboretum of Virginia, near Boyce, Virginia. Fifty tree species were analyzed and about half were directly identified with varying degrees of success on the basis of spectral matched filtering that utilized laboratory-measured leaf spectra as the target signatures. Spectral averages of pixels extracted from SEBASS emissivity data compared favorably with laboratory spectra of leaves collected from individual tree species. Best results were obtained from species having relatively strong spectral contrast, wide and flat leaves, closed planophile canopies, and/or large canopy areas. Tree species having small leaves or unfavorable leaf orientations showed spectral attenuation likely resulting from cavity blackbody effects. Increased spatial resolution and better image calibration and atmospheric correction might lead to further improvements in thermal infrared plant species identification.     

镜面杂质与水汽吸放对露点仪影响的实验研究

显微成像露点仪在研制和测试过程中发现镜面杂质和内腔材质吸放水汽等影响测量精度的问题。针对镜面杂质对显微成像露点仪测量的影响开展了镜面图像特征的实验研究，结果表明：镜面杂质点处露珠凝结具有优先性，且反复凝结消散后镜面出现杂质沉降现象。针对水汽吸放对显微成像露点仪的影响开展了水汽释放与吸附效应的实验研究，结果表明：当温度发生变化时，显微成像露点仪感应舱内壁氧化铝材质存在释放（或吸附）水汽现象，使得显微成像露点仪测量值偏大（或偏小）。研究结果为露点仪在功能设置及镜面与腔体材料选择方面提供了参考。     

Relation between vegetation canopy surface temperature and the Sun-surface geometry in a mountainous region of central Italy

Evapotranspiration is the dominant energy exchange process in dense vegetated environments with an adequate water supply. If water is available vegetation canopy temperatures do not respond immediately upon intercepting solar radiation because of the apportionment of absorbed solar radiation into sensible and latent heat. This lag in the thermal conditions of vegetation canopy following the incident solar flux can be even more complex after sunrise because the presence of dew on the foliage requires more available energy investment in evaporating water and less energy spent in warming the foliage. The aim of this Letter, which is based on remotely-sensed thermal data obtained from Landsat Thematic Mapper in the daytime of a clear summer day, is to investigate the relationship between canopy surface temperatures and the incident solar radiation for a forested montainous landscape of central Italy. Results show that, under the conditions of our experiment, a time lag of one hour considerably increases the linear relation between vegetation canopy temperature and local solar illumination angle.     

Impact of rain interception by vegetation and mulch on the L-band emission of natural grass

This paper explores the effect of rain intercepted by vegetation and mulch on the L-band emission of natural grass. The study is based on radiometric, meteorological, and biophysical measurements obtained during the SMOSREX Experiment (Toulouse, France). Several approaches were followed to evaluate interception effects. Firstly, the analysis of microwave brightness temperature (TB) measurements at L-band indicated that interception increases vegetation emission at both polarisations. Secondly, the use of microwave indices to detect the presence/absence of interception was examined. In particular, a modified polarisation ratio at 50° was found to be well related to the interception status of the standing vegetation. Finally, the vegetation optical depth (τ), which parameterises the extinction across the vegetation layer, was retrieved from the TB observations. It was found that τ increases with the increase in the water content stored within the vegetation and mulch after rainfall. The study highlights the strong impact of intercepted water in otherwise weakly attenuating covers such as grasses. Interception might therefore be an issue to consider in order to improve soil moisture retrieval algorithms from L-band observations.     

Monitoring drought effects on vegetation water content and fluxes in chaparral with the 970 nm water band index

The goal of this study was to explore the utility of the 970 nm water band index (WBI) in estimating evapotranspiration and vegetation water status for a semiarid shrubland ecosystem. Between 2001 and 2003, spectral reflectance coupled with CO₂ and water flux data were collected at Sky Oaks Biological Field Station, a chaparral-dominated ecosystem in southern California, and one of the sites within the SpecNet network. The reflectance data were collected either by walking along a 100 m transect or by using a semi-automated tram system installed later at the site along the same 100 m transect. CO₂ and water flux data were gathered with an eddy covariance flux tower adjacent to the tram system. The 970 nm WBI and normalized difference vegetation index (NDVI) were derived from the spectral reflectance. The two indices were expressed both as points approximately a meter apart along the transect and as whole-transect averages, where all of the reflectance values along the transect were averaged together, simulating a large pixel. This study encompassed a wet year with normal precipitation (2001), a 100-year record drought (2002), and a recovery year (2003), allowing for comparison over time and between precipitation regimes. Species-specific responses to wet and dry periods were evident in the reflectance spectra, providing a basis for separating species based on their optical properties. The WBI was significantly correlated with the NDVI revealing a strong link between canopy water content and green canopy structure; however this relationship varied with species and water status, providing evidence for the independence of these two optical indices. The WBI was also strongly linked to surface-atmosphere fluxes, explaining 49% of the variance in the water vapor flux, and 24% of the carbon dioxide fluxes. These results suggest that WBI or other similar water status indices may be useful variables in modeling CO₂ and water fluxes when combined with other physiological, environmental, and atmospheric factors.     

Estimation of evapotranspiration in a mid-latitude forest using the Microwave Emissivity Difference Vegetation Index (EDVI)

We developed an algorithm to estimate evapotranspiration (ET) from dense vegetation covered area from the first principle of surface energy balance model by using satellite retrieved Microwave Emissivity Difference Vegetation Index (EDVI). This algorithm can be used under both clear sky and cloudy sky conditions. Long term seasonal trend of EDVI is linked to variance of canopy resistance due to the interrelationship among leaf development, environmental condition and microwave radiation. Short term changes of EDVI caused by synoptic scale weather variations is used to parameterize the responds of vegetation resistance to the quick changes of environmental factors including water vapor deficit, water potential and others. The performance of this algorithm was test at the Harvard forest site by using satellite measurements from the SSM/I F13 and F14 sensors. Validation at the site with 169 samples shows that the correlation coefficient (R²) between estimated and observed ETs is 0.83 with a mean bias of 3.31 Wm^− 2 and a standard deviation of 79.63 Wm^− 2. The overall uncertainty of our ET retrieval is ~30%, which is within the uncertainty of current ground based ET measurements. Furthermore, the estimated ET in different local times (up to 4 times per day) successfully captured the diurnal cycle of ET. It is the first time that the diurnal variations of vegetation-atmosphere interactions were directly monitored from space. This study demonstrates that the technique reported here extends the current satellite capability of vegetation property and ET flux remote sensing from daytime, clear-sky conditions to day and night times and from intermediate leaf area index (LAI) to all range of vegetation states.     

Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?

We used daily MODerate resolution Imaging Spectroradiometer (MODIS) imagery obtained over a five-year period to analyze the seasonal and inter-annual variability of the fraction of absorbed photosynthetically active radiation (FAPAR) and photosynthetic light use efficiency (LUE) for the Southern Old Aspen (SOA) flux tower site located near the southern limit of the boreal forest in Saskatchewan, Canada. To obtain the spectral characteristics of a standardized land area to compare with tower measurements, we scaled up the nominal 500 m MODIS products to a 2.5 km × 2.5 km area (5 × 5 MODIS 500 m grid cells). We then used the scaled-up MODIS products in a coupled canopy-leaf radiative transfer model, PROSAIL-2, to estimate the fraction of absorbed photosynthetically active radiation (APAR) by the part of the canopy dominated by chlorophyll (FAPAR_chl) versus that by the whole canopy (FAPAR_canopy). Using the additional information provided by flux tower-based measurements of gross ecosystem production (GEP) and incident PAR, we determined 90-minute averages for APAR and LUE (slope of GEP:APAR) for both the physiologically active foliage (APAR_chl, LUE_chl) and for the entire canopy (APAR_canopy, LUE_canopy).The flux tower measurements of GEP were strongly related to the MODIS-derived estimates of APAR_chl (r² = 0.78) but only weakly related to APAR_canopy (r² = 0.33). Gross LUE between 2001 and 2005 for LUE_chl was 0.0241 µmol C µmol^− 1 PPFD whereas LUE_canopy was 36% lower. Time series of the 5-year normalized difference vegetation index (NDVI) were used to estimate the average length of the core growing season as days of year 152-259. Inter-annual variability in the core growing season LUE_chl (µmol C µmol^− 1 PPFD) ranged from 0.0225 in 2003 to 0.0310 in 2004. The five-year time series of LUE_chl corresponded well with both the seasonal phase and amplitude of LUE from the tower measurements but this was not the case for LUE_canopy. We conclude that LUE_chl derived from MODIS observations could provide a more physiologically realistic parameter than the more commonly used LUE_canopy as an input to large-scale photosynthesis models.     

A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km × 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr^− 1 for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.     

Substrate age and precipitation effects on Hawaiian forest canopies from spaceborne imaging spectroscopy

We used spaceborne imaging spectroscopy provided by the Earth Observing-1 Hyperion sensor to quantify the relative importance of precipitation and substrate age that control ecosystem development and functioning in Metrosideros polymorpha rainforests of Hawaii. Four hyperspectral vegetation indices provided metrics of forest canopy structure, biochemistry and physiology to compare along gradients of annual rainfall (750 to > 6000 mm year^− 1) and substrate age (0 to 250,000 years). The canopy greenness index NDVI increased with annual precipitation and substrate age, but saturated in forests with rainfall of 3000 mm year^− 1. Precipitation and substrate age were roughly equal contributors to the observed greenness of the forests. A canopy water content index (NDWI) also increased with precipitation and substrate age, but did not reach a maximum until very wet (> 5000 mm year^− 1) forest conditions were encountered on the oldest substrates. The water index appears superior to the NDVI in capturing spatial and climate-substrate driven variations in canopy structure. The photochemical reflectance index (PRI) indicated highest light-use efficiency levels in canopies on the most developed substrates and at annual precipitation levels of 3-4500 mm year^− 1. A leaf carotenoid index (CRI) suggested a maximum canopy photosynthetic capacity at ∼ 4000 mm rainfall year^− 1 on the oldest substrates. These results quantify the sensitivity of rainforest canopies to changing precipitation and soil conditions, and they corroborate plot-scale analyses in native Hawaiian forests ecosystems. Structural and functional studies of remote rainforest regions are possible with spaceborne imaging spectroscopy, and could be used to understand the dynamics of rainforests with climate change.     

Parameterization of a diagnostic carbon cycle model for continental scale application

Diagnostic carbon cycle models depend on parameterization to establish model sensitivity to climate variables and site factors. Here we acquired meteorological and carbon flux data from a diverse set (N = 18) of eddy covariance (EC) flux towers, along with MODIS data on FPAR (the fraction of incident photosynthetically active radiation that is absorbed by the plant canopy) at the sites, and used the data to develop a parameter set for the application of a diagnostic carbon cycle model over North America. The parameter optimization approach relied on goodness of fit between model simulations and tower estimates of gross primary production and net ecosystem production (NEP). Parameters such as light use efficiency (LUE) and base rate of heterotrophic respiration varied widely between sites representing different plant functional types (PFTs), thus supporting the value of stratification by PFT when parameterizing the model. Where multiple EC sites were available within a PFT, overall prediction error and bias in mean NEP was reduced by cross-site optimization as opposed to reliance on a single site. Optimization with the MODIS Enhanced Vegetation Index (EVI) instead of MODIS FPAR resulted in a similar goodness of fit, however, LUE values were pushed to levels that were not physiologically realistic when using EVI. The increasing availability of gap-filled EC tower data is rapidly improving the opportunities for direct coupling of satellite and ground observational data for parameterizing of diagnostic carbon flux models.     

Influence of woody elements of a Norway spruce canopy on nadir reflectance simulated by the DART model at very high spatial resolution

A detailed sensitivity analysis investigating the effect of woody elements introduced into the Discrete Anisotropic Radiative Transfer (DART) model on the nadir bidirectional reflectance factor (BRF) for a simulated Norway spruce canopy was performed at a very high spatial resolution (modelling resolution 0.2 m, output pixel size 0.4 m). We used such a high resolution to be able to parameterize DART in an appropriate way and subsequently to gain detailed understanding of the influence of woody elements contributing to the radiative transfer within heterogeneous canopies. Three scenarios were studied by modelling the Norway spruce canopy as being composed of i) leaves, ii) leaves, trunks and first order branches, and finally iii) leaves, trunks, first order branches and small woody twigs simulated using mixed cells (i.e. cells approximated as composition of leaves and/or twigs turbid medium, and large woody constituents). The simulation of each scenario was performed for 10 different canopy closures (CC = 50-95%, in steps of 5%), 25 leaf area index (LAI = 3.0-15.0 m² m^− 2, in steps of 0.5 m² m^− 2), and in four spectral bands (centred at 559, 671, 727, and 783 nm, with a FWHM of 10 nm). The influence of woody elements was evaluated separately for both, sunlit and shaded parts of the simulated forest canopy, respectively. The DART results were verified by quantifying the simulated nadir BRF of each scenario with measured Airborne Imaging Spectroradiometer (AISA) Eagle data (pixel size of 0.4 m). These imaging spectrometer data were acquired over the same Norway spruce stand that was used to parameterise the DART model.The Norway spruce canopy modelled using the DART model consisted of foliage as well as foliage including robust woody constituents (i.e. trunks and branches). All results showed similar nadir BRF for the simulated wavelengths. The incorporation of small woody parts in DART caused the canopy reflectance to decrease about 4% in the near-infrared (NIR), 2% in the red edge (RE) and less than 1% in the green band. The canopy BRF of the red band increased by about 2%. Subsequently, the sensitivity on accounting for woody elements for two spectral vegetation indices, the normalized difference vegetation index (NDVI) and the angular vegetation index (AVI), was evaluated. Finally, we conclude on the importance of including woody elements in radiative transfer based approaches and discuss the applicability of the vegetation indices as well as the physically based inversion approaches to retrieve the forest canopy LAI at very high spatial resolution.     

Detection of foliage conditions and disturbance from multi-angular high spectral resolution remote sensing

Disturbance of forest ecosystems, an important component of the terrestrial carbon cycle, has become a focus of research over recent years, as global warming is about to increase the frequency and severity of natural disturbance events. Remote sensing offers unique opportunities for detection of forest disturbance at multiple scales; however, spatially and temporally continuous mapping of non-stand replacing disturbance remains challenging. First, most high spatial resolution satellite sensors have relatively broad spectral ranges with bandwidths unsuitable for detection of subtle, stress induced, features in canopy reflectance. Second, directional and background reflectance effects, induced by the interactions between the sun-sensor geometry and the observed canopy surface, make up-scaling of empirically derived relationships between changes in spectral reflectance and vegetation conditions difficult. Using an automated tower based spectroradiometer, we analyse the interactions between canopy level reflectance and different stages of disturbance occurring in a mountain pine beetle infested lodgepole pine stand in northern interior British Columbia, Canada, during the 2007 growing season. Directional reflectance effects were modelled using a bidirectional reflectance distribution function (BRDF) acquired from high frequency multi-angular spectral observations. Key wavebands for observing changes in directionally corrected canopy spectra were identified using discriminant analysis and highly significant correlations between canopy reflectance and field measured disturbance levels were found for several broad and narrow waveband vegetation indices (for instance, r²_NDVI = 0.90; r²_CHL3 = 0.85; p < 0.05). Results indicate that multi-angular observations are useful for extraction of disturbance related changes in canopy reflectance, in particular the temporally and spectrally dense data detected changes in chlorophyll content well. This study will help guide and inform future efforts to map forest health conditions at landscape and over increasingly coarse scales.     

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were recorded at 400 Hz over three intensive areas of 1 km² where transects were spaced at 200 m, and along 64 transects spaced 1 km apart (total of ca. 2500 km²). LIDAR and field measurements of canopy height were similar in the three intensive study areas, with the 80th percentile of LIDAR returns explaining the greatest amount of variability (79%). Correlations between LIDAR data and aboveground tree biomass measured in the field were highly significant when all three 1 km² areas were analyzed collectively, with the 80th percentile again explaining the greatest amount of variability (74%). However, when intensive areas were analyzed separately, correlations were poor for Oak/Pine and Pine/Scrub Oak stands. Similar results were obtained using FIA data; at the landscape scale, mean canopy height was positively correlated with aboveground tree biomass, but when forest types were analyzed separately, correlations were significant only for some wetland forests (Pitch Pine lowlands and mixed hardwoods; r² = 0.74 and 0.59, respectively), and correlations were poor for upland forests (Oak/Pine, Pine/Oak and Pine/Scrub Oak, r² = 0.33, 0.11 and 0.21, respectively). When LIDAR data were binned into 1-m height classes, more LIDAR pulses were recorded from the lowest height classes in stands with greater shrub biomass, and significant differences were detected between stands where recent prescribed fire treatments had been conducted and unburned areas. Our research indicates that single-beam LIDAR can be used for regional-scale (forest biomass) estimates, but that relationships between height and biomass can be poorer at finer scales within individual forest types. Binned data are useful for estimating the presence of ladder fuels (vertical continuity of leaves and branches) and horizontal fuel continuity below the canopy.