Spatial scale variations in vegetation indices and above-ground biomass estimates: Implications for MERIS

The Medium Resolution Imaging Spectrometer (MERIS) is one of the sensors carried by Envisat. MERIS is a fully programmable imaging spectrometer, however a standard 15-channel band set will be transmitted for each 300 m pixel (over land while over the ocean the pixels will be aggregated to 1200 m spatial resolution) covering visible and near-infrared wavelengths. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS's performance relative to the scale of observation using simulated datasets degraded to various spatial resolutions in the range of 6-300 m. Algorithms to simulate MERIS data using airborne imaging spectrometer datasets were presented, including a case study from DAIS (i.e. Digital Airborne Imaging Spectrometer) 79-channel imaging spectrometer data acquired on 8 July 1997 over the Le Peyne test site in southern France. For selected target endmembers garrigue, maquis, mixed oak forest, pine forest and bare agricultural field, regions-of-interest (ROI) were defined in the DAIS scene. For each of the endmembers, the vegetation index values in the corresponding ROI is calculated for the MERIS data at the spatial resolutions ranging from 6 to 300 m. We applied the NDVI, PVI, WDVI, SAVI, MSAVI, MSAVI2 and GEMI vegetation indices. Above-ground biomass (AGB) was estimated in the field and derived from the DAIS image and the MERIS datasets (6-300 m spatial resolution). The vegetation indices are shown to be constant with the spatial scale of observation. The strongest correlation between the MERIS and DAIS NDVI is obtained when using a linear model with an offset of 0.15 ( r =0.31). A Pearson correlation matrix between AGB measured in the field and each spectral band reveals a modest but significant ( p <0.05) correlation for most spectral bands. When mathematical functions are fitted through the NDVI and biomass data, an exponential fit shows the extinction and saturation at larger vegetation biomass values. The correlation between biomass and NDVI for DAIS as well as for the MERIS simulated dataset is modest. Further research is required to analyse the scale effects that limit the correlation between field and image AGB estimates.     

Forage quality of savannas — Simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery

Savanna covers about two-thirds of Africa, with forage quantity and quality being important factors determining the distribution and density of wildlife and domestic stock. Testing hypotheses about the distribution of herbivores is hampered by the absence of reliable methods for measuring the variability of vegetation quality (e.g. biochemical composition) across the landscape. It is demonstrated that hyperspectral remote sensing fills this gap by revealing simultaneously the spatial variation of foliar nitrogen (crude protein) as well as the total amount of polyphenols, in grasses and trees. For the first time, the pattern of resources important for feeding preferences in herbivores (polyphenols and nitrogen) is mapped across an extensive landscape and the modeled foliar concentrations are shown to fit with ecological knowledge of the area. We explain how estimates of nitrogen (crude protein) and polyphenols may be scaled up from point-based observations to reveal their spatial pattern, and how the variation in forage quality can influence the management of savannas, including farms, communal grazing areas, and conservation areas. It provides a glimpse of the choices herbivores must face in selecting food resources of different qualities.     

Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland

Radiative transfer models have seldom been applied for studying heterogeneous grassland canopies. Here, the potential of radiative transfer modeling to predict LAI and leaf and canopy chlorophyll contents in a heterogeneous Mediterranean grassland is investigated. The widely used PROSAIL model was inverted with canopy spectral reflectance measurements by means of a look-up table (LUT). Canopy spectral measurements were acquired in the field using a GER 3700 spectroradiometer, along with simultaneous in situ measurements of LAI and leaf chlorophyll content. We tested the impact of using multiple solutions, stratification (according to species richness), and spectral subsetting on parameter retrieval. To assess the performance of the model inversion, the normalized RMSE and R² between independent in situ measurements and estimated parameters were used. Of the three investigated plant characteristics, canopy chlorophyll content was estimated with the highest accuracy (R² = 0.70, NRMSE = 0.18). Leaf chlorophyll content, on the other hand, could not be estimated with acceptable accuracy, while LAI was estimated with intermediate accuracy (R² = 0.59, NRMSE = 0.18). When only sample plots with up to two species were considered (n = 107), the estimation accuracy for all investigated variables (LAI, canopy chlorophyll content and leaf chlorophyll content) increased (NRMSE = 0.14, 0.16, 0.19, respectively). This shows the limits of the PROSAIL radiative transfer model in the case of very heterogeneous conditions. We also found that a carefully selected spectral subset contains sufficient information for a successful model inversion. Our results confirm the potential of model inversion for estimating vegetation biophysical parameters at the canopy scale in (moderately) heterogeneous grasslands using hyperspectral measurements.     

De-tethering of high aspect ratio metallic and polymeric MEMS/NEMS parts for the direct pick-and-place assembly of 3D microsystem

We report our study on several de-tethering methods for various high aspect ratio metallic and polymeric MEMS and NEMS parts including 5:1 aspect ratio 50 μm thick metallic (nickel) MEMS parts, 3:1 aspect ratio 1 μm thick sub-micron (350 nm) feature size metallic NEMS actuators, and 10:1 aspect ratio 100 μm thick polymer/metal bi-layer MEMS actuators. Resistive heating was found to be effective for the de-tethering of high aspect ratio metallic MEMS parts. In order to de-tether metallic NEMS parts and polymer/metal bi-layer devices, we performed the milling of tethers using a focused ion beam. Very low current (20 pA) ion beam was found to be effective means of de-tethering the metallic NEMS parts. Relatively larger current (0.3–20 nA) ion beam was found to be good for the polymer/metal bi-layer parts. We demonstrated 3D assembly and complete packaging of the de-tethered high aspect ratio metallic and metal/polymer bilayer MEMS parts.     

Phase diagram and structure-property relationships in the lead-free piezoelectric system: Na0.5K0.5NbO3-LiTaO3

A phase-diagram for the Na(0.5)K(0.5)NbO(3)-LiTaO(3) solid solution series (NKN-LT) is presented for compositions ≤ 10 mol% LT, based on the combined results of temperaturevariable X-ray powder diffraction and dielectric measurements. In addition to the reported orthorhombic and tetragonal polymorphs of NKN-LT, a monoclinic phase is revealed. Changes to electrical properties as a function of LT substitution are correlated to phase content. Increasing the LT content from 5 to 7 mol% LT led to improved temperature stability of piezoelectric properties because of the avoidance of the monoclinic-tetragonal polymorphic phase transition during thermal cycling (at >25°C). For 7 mol% LT samples: d(33) = 200 pC/N; T(c) = 440°C; ε(r) = 550 and tan δ = 0.02 (at 20°C). Modification of this composition by solid solution with BiScO(3) led to a decrease in d(33) values. Transmission electron microscopy of a sample of 0.95[0.93 NKN-0.07LT]-0.05BiScO(3) indicated a core-shell grain structure which led to temperature-stable dielectric properties.     

Spectral discrimination of vegetation types in a coastal wetland

Remote sensing is an important tool for mapping and monitoring vegetation. Advances in sensor technology continually improve the information content of imagery for airborne, as well as space-borne, systems. This paper investigates whether vegetation associations can be differentiated using hyperspectral reflectance in the visible to shortwave infrared spectral range, and how well species can be separated based on their spectra. For this purpose, the field reflectance spectra of 27 saltmarsh vegetation types of the Dutch Waddenzee wetland were analysed in three steps. Prior to analysis, the spectra were smoothed with an innovative wavelet approach.In the first stage of the analysis, the reflectance spectra of the vegetation types were tested for differences between type classes. It was found that the reflectance spectra of saltmarsh vegetation types are statistically significantly different for various spectral regions.Secondly, it was tested whether this statistical difference could be enhanced by using continuum removal as a normalisation technique. For vegetation spectra, continuum removal improves the statistical difference between vegetation types in the visible spectrum, but weakens the statistical difference of the spectra in the near-infrared and shortwave infrared part of the spectrum.Thirdly, after statistical differences were found, it was determined how distant in spectral space the vegetation type classes were from each other, using the Bhattacharyya (BH) and the Jeffries-Matusita (JM) distance measures. We selected six wavelengths for this, based on the statistical analysis of the first step. The potential of correct classification of the saltmarsh vegetation types using hyperspectral remote sensing is predicted by these distance measures.It is concluded that the reflectance of vegetation types is statistically different. With high quality radiometric calibration of hyperspectral imagery, it is anticipated that vegetation species may be identified from imagery using spectral libraries that were measured in the field during the time of image acquisition.     

Developmental changes in localization of steroid synthesis enzymes in camelid placenta

The uninucleate trophoblast of epitheliochorial camelid placenta produces multinucleate giant cells starting between day 30 and day 35 of pregnancy. The giant cells are found scattered along the trophoblast at similar frequency throughout gestation. Light microscope immunocytochemistry indicates that the four steroid synthesis enzymes (cholesterol side chain cleavage, 3beta-hydroxysteroid de-hydrogenase, 17alpha-hydroxylase and aromatase) are present in all uninucleate trophoblast cells between day 14 and day 30 of pregnancy, but are found only in the giant cells once they are established, and that this localization persists until term. The giant cells show massive amounts of smooth endoplasmic reticulum and numerous small mitochondria, again as has been shown in other steroid-producing cells. As progesterone from the corpus luteum is necessary throughout gestation in camels, the capacity for oestrogen production by the trophoblast presumably has an important role, but one limited mostly to the immediate vicinity of the fetomaternal interface.     

Channel-Forming Discharge Selection in River Restoration Design

The concept of channel-forming (Qcf) or dominant discharge is now a cornerstone of river channel restoration design. Three measures of channel-forming discharge are most commonly applied: effective discharge (Qeff), bankfull discharge (Qbf), and a discharge of a certain recurrence interval (Qri), which theoretically are similar in geomorphically stable channels. The latter two measures have become particularly widely applied in some channel restoration design procedures, often to the exclusion of Qeff analyses, despite the additional utility of Qeff analysis for most channel design problems. We quantify the three measures of Qcf for four case studies and then follow this with a synthesis of previously published studies to illustrate sources of variability. This synthesis suggests that agreement among the three measures of Qcf is best for snowmelt-hydrology, nonincised channels with coarse substrate. Departures from these conditions result in greater discrepancy between the measures. Channel incision produces Qbf far greater than Qeff, and flashy hydrology is associated with generally larger, briefer, and more frequent Qeff. Regional mean or median values for the relative magnitudes of the three measures can be tightly constrained, but site to site variation is quite large. The construction of a cumulative sediment discharge curve and associated determination of Qeff allows quantification of the sediment budget of a channel for a given hydrologic regime, which provides process-based insight of drivers of current and future trajectories of channel stability, and is thus the recommended measure of channel-forming discharge. Reliance on only return-interval or bankfull discharge for channel design is not recommended for channel design activities.     

Diode arrays, crystals, and thermal management for solid-statelasers

We summarize our efforts in the development of solid-state lasers, including the laser diode arrays, pump light delivery, approaches to thermal management, and novel gain media. Our interests are in developing unique solid-state lasers, including those operating at higher powers, offering less common wavelengths, and having other specialized features. In this paper, we discuss high-power Tm:YAG and Yb:YAG lasers. The gas cooled slab laser concept using Yb:S-FAP, and side-pumped Er:YAG and Cr:ZnSe lasers. We address the optical and thermal physics of these systems and also mention several additional gain media that have the potential of offering unique performance characteristics: Ce:LiSAF, APG-2 laser glass, Dy:LaCl₃, and Yb:BCBF     

HYDROGEOMORPHIC CLASSIFICATION OF WASHINGTON STATE RIVERS TO SUPPORT EMERGING ENVIRONMENTAL FLOW MANAGEMENT STRATEGIES

As demand for fresh water increases in tandem with human population growth and a changing climate, the need to understand the ecological tradeoffs of flow regulation gains greater importance. Environmental classification is a first step towards quantifying these tradeoffs by creating the framework necessary for analysing the effects of flow variability on riverine biota. Our study presents a spatially explicit hydrogeomorphic classification of streams and rivers in Washington State, USA and investigates how projected climate change is likely to affect flow regimes in the future. We calculated 99 hydrologic metrics from 15 years of continuous daily discharge data for 64 gauges with negligible upstream impact, which were entered into a Bayesian mixture model to classify flow regimes into seven major classes described by their dominant flow source as follows: groundwater (GW), rainfall (RF), rain‐with‐snow (RS), snow‐and‐rain (SandR), snow‐with‐rain (SR), snowmelt (SM) and ultra‐snowmelt (US). The largest class sizes were represented by the transitional RS and SandR classes (14 and 12 gauges, respectively), which are ubiquitous in temperate, mountainous landscapes found in Washington. We used a recursive partitioning algorithm and random forests to predict flow class based on a suite of environmental and climate variables. Overall classification success was 75%, and the model was used to predict normative flow classes at the reach scale for the entire state. Application of future climate change scenarios to the model inputs indicated shifts of varying magnitude from snow‐dominated to rain‐dominated flow classes. Lastly, a geomorphic classification was developed using a digital elevation model (DEM) and climatic data to assign stream segments as either dominantly able or unable to migrate, which was cross‐tabulated with the flow types to produce a 14‐tier hydrogeomorphic classification. The hydrogeomorphic classification provides a framework upon which empirical flow alteration–ecological response relationships can subsequently be developed using ecological information collected throughout the region. Copyright © 2011 John Wiley & Sons, Ltd.