Visible To Near-infrared Research Articles

Visible to near-infrared optical properties of pure synthetic olivine across the olivine solid solution

Olivine exhibits highly diagnostic absorption features across visible to near-infrared (VNIR) wavelengths due to electronic transitions of Fe2+ in its crystal structure. The properties of these absorptions vary with composition, enabling compositional analysis of olivine through VNIR spectroscopy, both in the laboratory and through remote sensing. Previous analyses of these trends have relied on natural olivine samples, which are influenced by the presence of minor cations that can affect the diagnostic absorptions. We conduct a systematic analysis of a suite of synthetic (pure Mg/Fe) olivine samples with VNIR (300–2600 nm) reflectance spectroscopy and quantitative spectral deconvolutions. From the full suite of samples described and characterized by Dyar et al. (2009), we identify a small suite of well-characterized and chemically pure olivine samples that demonstrates consistent and reliable spectral reflectance properties across visible to near-infrared wavelengths. This suite covers the stoichiometric olivine solid solution from x = Mg/(Mg+Fe) = 0 to x = 70 (Fo to Fo70). Because of their tight compositional control, these synthetic samples improve on previous analyses of natural samples. The results of this study provide a new standard for spectral reflectance properties of olivine across visible to near-infrared wavelengths for the compositions present in the suite. We present updated data on the trends in olivine band position as a function of olivine composition, which are the basis for remote compositional evaluation of olivine with visible to near-infrared reflectance spectroscopy. For these reasons, these improved olivine band position trends are of major importance to remote compositional analyses of terrestrial planets.

A Novel UAV-Based Ultra-Light Weight Spectrometer for Field Spectroscopy

A novel hyperspectral measurement system for unmanned aerial vehicles (UAVs) in the visible to near infrared (VIS/NIR) range (350-800 nm) was developed based on the Ocean Optics STS microspectrometer. The ultralight device relies on small open source electronics and weighs a ready-to-fly 216 g. The airborne spectrometer is wirelessly synchronized to a second spectrometer on the ground for simultaneous white reference collection. In this paper, the performance of the system is investigated and specific issues such as dark current correction or second order effects are addressed. Full width at half maximum was between 2.4 and 3.0 nm depending on the spectral band. The functional system was tested in flight at a 10-m altitude against a current field spectroscopy gold standard device Analytical Spectral Devices Field Spec 4 over an agricultural site. A highly significant correlation was found in reflection comparing both measurement approaches. Furthermore, the aerial measurements have a six times smaller standard deviation than the hand held measurements. Thus, the present spectrometer opens a possibility for low-cost but high-precision field spectroscopy from UAVs.

Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21)

Land Surface Temperature and Emissivity (LST&E) data determine the amount of net longwave radiation emitted from the Earth's surface and are therefore critical variables for studying a variety of surface–atmosphere processes over land such as evapotranspiration, land cover change, and surface composition. Because emissivity is an intrinsic property of the surface, multispectral thermal infrared emissivity data have the potential for enhancing our ability to monitor landscape changes in environmentally sensitive zones beyond what is currently possible from standard practices used today. The most common of these practices is the use of visible to short-wave infrared data, in particular the Normalized Difference Vegetation Index (NDVI). Two algorithms are currently used to generate the LST&E products from MODIS data, but studies have identified several issues with both these algorithms that limit their usefulness for land cover change detection. These issues have been recently addressed by applying the ASTER Temperature Emissivity Separation (TES) algorithm to MODIS thermal infrared data to generate LST and a dynamically varying multispectral emissivity product for bands 29, 31, and 32 at 1-km resolution. The new product (MOD21) will be released with MODIS Collection 6 during fall 2013. This study demonstrates the utility of the dynamic MOD21 multispectral emissivity product to detect land cover changes over a broad range of different Earth surface domains including land degradation in dryland regions, snow melt characteristics on glaciers and ice sheets, extreme ecosystem disturbances, and agricultural activities. The MOD21 spectral emissivity provided increased sensitivity to land cover change in a more consistent manner than is currently possible with other emissivity products and, depending on the application, standard visible to near infrared (VNIR) data. The results suggest that synergistic use of thermal and VNIR data will help us to better identify and understand changes in the Earth surface system, and reduce uncertainties in estimating their magnitudes and trends.

Development and applications of ruggedized VIS/NIR spectrometer system for oilfield wellbores

The development and applications of a ruggedized visible to near-infrared (VIS/NIR) spectrometer system capable of measuring fluid spectra in oilfield wellbores are presented. Real-time assessment of formation fluid properties penetrated by an oilfield wellbore is critically important for oilfield operating companies to make informed decisions to optimize the development plan of the well and hydrocarbon reservoir. A ruggedized VIS/NIR spectrometer was designed and built to measure and analyze hydrocarbon spectra reliably under the harsh conditions of the oilfield wellbore environment, including temperature up to 175 °C, pressure up to 170 MPa, and severe mechanical shocks and vibrations. The accuracy of hydrocarbon group composition analysis was compared well with gas chromatography results in the laboratory.

Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands

Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized using AMSR-E enhanced land surface parameters for the period from April through October for 2003 through 2010. Growing degree-days (GDDs) were calculated from AMSR-E air temperature retrievals using both ascending and descending passes with a base of 0 ° C and then accumulated (AGDD) with an annual restart each 1 April. Tracking the AMSR-E parameters as a function of AGDD revealed the expected seasonal pattern of thermal limitation in mid-latitude croplands. Vegetation optical depth (VOD), a microwave analog of a vegetation index, was modeled as a function of AGDD with the resulting fitted convex quadratic models yielding both high coefficients of determination (r2 > 0.90) and phenometrics that could characterize cropland differences between the Russian and North American sites. The AMSR-E data were also able to capture the effects of the 2010 heat wave that devastated grain production in European Russia. These results showed the potential of AMSR-E in monitoring and modeling cropland dynamics.

Detection of multiple stresses in Scots pine growing at post-mining sites using visible to near-infrared spectroscopy

Heavy metal contamination, low pH and high substrate heterogeneity are multiple stress factors that often occur at the post-mining sites and make difficult the biological reclamation. Efficient tools for detection of the status of reclaimed vegetation at post-mining sites are needed. We tested the potential of visible to near-infrared (VNIR) spectroscopy to detect multiple stresses in Scots pine (Pinus sylvestris L.) at acidic substrates rich in As. The needle chemical traits (chlorophyll a + b - Cab; carotenoids - Car; Car/Cab; relative water content - RWC; soluble phenolics; lignin contents) were tested for sensitivity to different soil conditions of post-mining sites. For Scots pine growing on degraded substrates, at least three non-specific stress indicators (RWC, photosynthetic pigments and phenolics) are required to achieve good site separability corresponding to the stress load. We constructed and validated empirical models of selected needle chemical traits using VNIR spectroscopy: calibration of Cab (R(2) = 0.97, RMSE = 0.17 mg g(-1)), RWC (R(2) = 0.88, RMSE = 1.41 mg g(-1)), Car (R(2) = 0.66, RMSE = 0.08 mg g(-1)), phenolics (R(2) = 0.64, RMSE = 23.01 mg g(-1)) and lignin (R(2) = 0.45, RMSE = 3.32 mg g(-1)). The reflectance data yielded comparable site separability with the separability calculated from the laboratory data. The presented approach has potential for large-scale monitoring of Scots pine status, thus, assessment of reclamation quality in post-mining regions using air-born or satellite hyperspectral data.

Effects of UV-, Visible-, Near-Infrared Beams in Three Therapy Resistance Case Studies of Fungal Skin infections

Fungal and bacterial diseases, directly infecting various parts of body, have received much attention in recent years. Bacterial infections, such as Tinea Pedis, Pityriasis versicolor and Mycetoma can secondarily occur in superficial fungal damaged skin. They often occur in immune compromised individuals including diabetics and patients with peripheral arterial diseases. Mycetoma infections can travel through the bloodstream affecting different organs. In this paper, we investigate the photo-inactivation of the pathogens causing Tinea Pedis, Pityriasis versicolor, and Mycetoma infections in three therapy resistant patients without photosensitizing drugs. We have used a combination of visible to near-infrared (VIS/NIR) laser beams in association with blue (B), red (R) and ultra-violet (UV) light emitted diodes (LEDs) with incident doses of 0.63 - 21.43 J/cm 2 . These beams have minimum side effects on the normal part of the skin. According to the physicians’ assessments, all case study patients achieved an observable progress such as decreases in inflammatory lesions, rapid process of wound healing and scars improvements. Side effects such as inflammation, crusting, or hypopigmentation were not observed. The presented irradiation protocol may be a valuable complementary treatment for patients suffering from fungal and bacterial skin infections.

Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion

The Carnegie Airborne Observatory (CAO) was developed to address a need for macroscale measurements that reveal the structural, functional and organismic composition of Earth's ecosystems. In 2011, we completed and launched the CAO-2 next generation Airborne Taxonomic Mapping Systems (AToMS), which includes a high-fidelity visible-to-shortwave infrared (VSWIR) imaging spectrometer (380–2510nm), dual-laser waveform light detection and ranging (LiDAR) scanner, and high spatial resolution visible-to-near infrared (VNIR) imaging spectrometer (365–1052nm). Here, we describe how multiple data streams from these sensors can be fused using hardware and software co-alignment and processing techniques. With these data streams, we quantitatively demonstrate that precision data fusion greatly increases the dimensionality of the ecological information derived from remote sensing. We compare the data dimensionality of two contrasting scenes — a built environment at Stanford University and a lowland tropical forest in Amazonia. Principal components analysis revealed 336 dimensions (degrees of freedom) in the Stanford case, and 218 dimensions in the Amazon. The Amazon case presents what could be the highest level of remotely sensed data dimensionality ever reported for a forested ecosystem. Simulated misalignment of data streams reduced the effective information content by up to 48%, highlighting the critical role of achieving high precision when undertaking multi-sensor fusion. The instrumentation and methods described here are a pathfinder for future airborne applications undertaken by the National Ecological Observatory Network (NEON) and other organizations.

Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor

The regional mapping of grass nutrients is of interest in the sustainable planning and management of livestock and wildlife grazing. The objective of this study was to estimate and map foliar and canopy nitrogen (N) at a regional scale using a recent high resolution spaceborne multispectral sensor (i.e. RapidEye) in the Kruger National Park (KNP) and its surrounding areas, South Africa. The RapidEye sensor contains five spectral bands in the visible-to-near infrared (VNIR), including a red-edge band centered at 710nm. The importance of the red-edge band for estimating foliar chlorophyll and N concentrations has been demonstrated in many previous studies, mostly using field spectroscopy. The utility of the red-edge band of the RapidEye sensor for estimating grass N was investigated in this study. A two-step approach was adopted involving (i) vegetation indices and (ii) the integration of vegetation indices with environmental or ancillary variables using a stepwise multiple linear regression (SMLR) and a non-linear spatial least squares regression (PLSR). The model involving the simple ratio (SR) index (R805/R710) defined as SR54, altitude and the interaction between SR54 and altitude (SR54*altitude) yielded the highest accuracy for canopy N estimation, while the non-linear PLSR yielded the highest accuracy for foliar N estimation through the integration of remote sensing (SR54) and environmental variables. The study demonstrated the possibility to map grass nutrients at a regional scale provided there is a spaceborne sensor encompassing the red edge waveband with a high spatial resolution.

Remote compositional analysis of lunar olivine-rich lithologies with Moon Mineralogy Mapper (M3) spectra

[1] A systematic approach for deconvolving remotely sensed lunar olivine-rich visible to near-infrared (VNIR) reflectance spectra with the Modified Gaussian Model (MGM) is evaluated with Chandrayaan-1 Moon Mineralogy Mapper (M3) spectra. Whereas earlier studies of laboratory reflectance spectra focused only on complications due to chromite inclusions in lunar olivines, we develop a systematic approach for addressing (through continuum removal) the prominent continuum slopes common to remotely sensed reflectance spectra of planetary surfaces. We have validated our continuum removal on a suite of laboratory reflectance spectra. Suites of olivine-dominated reflectance spectra from a small crater near Mare Moscoviense, the Copernicus central peak, Aristarchus, and the crater Marius in the Marius Hills were analyzed. Spectral diversity was detected in visual evaluation of the spectra and was quantified using the MGM. The MGM-derived band positions are used to estimate the olivine's composition in a relative sense. Spectra of olivines from Moscoviense exhibit diversity in their absorption features, and this diversity suggests some variation in olivine Fe/Mg content. Olivines from Copernicus are observed to be spectrally homogeneous and thus are predicted to be more compositionally homogeneous than those at Moscoviense but are of broadly similar composition to the Moscoviense olivines. Olivines from Aristarchus and Marius exhibit clear spectral differences from those at Moscoviense and Copernicus but also exhibit features that suggest contributions from other phases. If the various precautions discussed here are weighed carefully, the methods presented here can be used to make general predictions of absolute olivine composition (Fe/Mg content).

Lithologic mapping in the Oscar II Coast area, Graham Land, Antarctic Peninsula using ASTER data

The results of the first attempt to use Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for the purposes of lithologic mapping on the Antarctic Peninsula are presented for an area on the Oscar II Coast, eastern Graham Land. This study included undertaking laboratory reflectance spectroscopy of ∼70 rock samples from the study area and spectral lithologic analysis of two ASTER scenes. Spectra of the granitoids, silicic volcanic/volcaniclastic and terrestrial sedimentary rocks in the study area display a limited range of absorption features associated with muscovite, smectite and chlorite that are generally present as the alteration products of regional metamorphism. ASTER data analysis was undertaken using the reflective bands of the Level 1B registered radiance at-sensor data and the standard thermal infrared (TIR) emissivity product (AST05). For both wavelength regions, standard qualitative image processing methods were employed to define image end-members that were used as reference within Matched Filter (MF) processing procedures. The results were interpreted with reference to existing field observations, and photogeologic analysis of the ASTER visible to near-infrared (VNIR)/shortwave infrared (SWIR) data was used to resolve ambiguities in the spectral mapping results. The results have enabled the discrimination of most of the major lithologic groups within the study area as well as delineation of hydrothermal alteration zones of propylitic, and argillic grades associated with the Mesozoic Mapple Formation volcanics. The results have extended the mapped coverage of the Mapple Formation into un-investigated regions further north and validated previously inferred geological observations concerning other rocks throughout the study area. The outcomes will enable important revisions to be made to the existing geological map of the Oscar II Coast and demonstrate that ASTER data offers potential for improving geological mapping coverage across the Antarctic Peninsula.

Combining multispectral aerial imagery and digital surface models to extract urban buildings

Please click here to download the map associated with this article. This paper presents an automated classification of buildings in Coleraine, Northern Ireland. The classification was generated using very high spatial resolution data (10 cm) from a Digital Mapping Camera (DMC) for March 2009. The visible to near infrared (VNIR) bands of the DMC enabled a supervised classification to be performed to extract buildings from vegetation. A Digital Surface Model (DSM) was also created from the image to differentiate between buildings and other land classes with similar spectral profiles, such as roads. The supervised classification had the lowest classification accuracy (50%) while the DSM had an accuracy of 81%. The combination of the DSM and the supervised classification achieved an overall classification accuracy of 95%. Two spatial metrics (percentage of the landscape and number of patches) were also used to test the level of agreement between the classification and digitised building data. The results suggest that fine resolution multispectral aerial imagery can automatically detect buildings to a very high level of accuracy. Current space borne sensors, such as IKONOS and QuickBird, lag behind airborne sensors with VNIR bands provided at a much coarser spatial resolution (4m and 2.4m respectively). Techniques must be developed from current airborne sensors that can be applied to new space borne sensors in the future. The ability to generate DSMs from high resolution aerial imagery will afford new insights into the three-dimensional aspects of urban areas which will in turn inform future urban planning.

Characterization of Navajo Sandstone concretions: Mars comparison and criteria for distinguishing diagenetic origins

The eolian Jurassic Navajo Sandstone spheroidal hydrous ferric oxide (HFO) concretions are divided into two size classes: macro-concretions of > 5 mm diameter and micro-concretions of < 5 mm diameter. Three internal structural end-members of macro-concretions are described as rind, layered, and solid. Two end-members of micro-concretions are rind and solid. Chemical and mineralogical gradients (μm- to mm-scale) are identified with QEMSCAN (Quantitative Elemental Mineralogy using a SCANning electron microscope) and visible to near infrared (VNIR) reflectance spectroscopy. Three HFO phases are identified using VNIR reflectance spectroscopy. i. An amorphous HFO phase is typically located in the rinds. ii. Goethite is present along interior edges of rinds and throughout the interiors of layered and solid concretions. iii. Hematite is present in the centers of rind concretions. A synthesis of petrographic, mineralogical and chemical analyses suggests that concretions grow pervasively (as opposed to radially expanding). Our model proposes that concretions precipitate initially as an amorphous HFO that sets the radius and retains some original porosity. Subsequent precipitation fills remaining pore space with younger mineral phases. Inward digitate cement crystal growth corroborates concretion growth from a set radius toward the centers. Internal structure is modified during late stage precipitation that diffuses reactants through semi-permeable rinds and overprints the interiors with younger cements. Physical characterization of textures and minerals provides diagnostic criteria for understanding how similar concretions (“blueberries”) form in Meridiani Planum, Mars. The analogous Navajo Sandstone concretions show similar characteristics of in situ self-organized spacing, spheroidal geometries, internal structures, conjoined forms, and precursor HFO phases that dehydrate to goethite or hematite. These characteristics indicate a common origin via groundwater diagenesis.

Late Cenozoic deformation of the Kura fold-thrust belt, southern Greater Caucasus

Although the geometry and kinematics of the first-order structures accommodating Arabia-Eurasia convergence are relatively well known in Turkey and Iran, major shortening structures remain poorly understood within the central portion of the collision zone, in eastern Anatolia and the Caucasus. New remotely sensed neotectonic mapping, synthesis of regional geologic and stratigraphic data, and balanced cross sections suggest that the Kura fold-thrust belt has accommodated the majority of Arabia-Eurasia convergence since the early Pliocene between the longitudes of ∼45°E and ∼49°E. This belt lies southeast of the N80°W-striking Greater Caucasus Mountains and forms an eastward-narrowing band of elevated topography that roughly parallels the range front for ∼400 km along strike. The belt is separated from the Greater Caucasus to the north by the 10- to 25-km-wide Alazani Basin and comprises a series of predominantly south-verging folds deforming Eocene–Quaternary flysch and molasse. To document structural geometries within the Kura fold-thrust belt, we have used the Real-time Interactive Mapping System (RIMS) software to analyze Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), visible to near-infrared (VNIR), and digital elevation model (DEM) data. This neotectonic mapping indicates an along-strike, eastward decrease in both structural complexity and the degree to which deformed geomorphic surfaces are dissected. Existing geologic maps indicate a corresponding eastward decrease in the depth of exposure. By integrating the structural geometries determined in our analysis of remote-sensing data with existing geologic data, we have constructed two balanced cross sections, which suggest these systematic along-strike variations result from a west-to-east decrease in total shortening within the Kura fold-thrust belt. We interpret this variable shortening to stem from eastward propagation of the Kura fold-thrust belt. Comparison of our preliminary total shortening estimates with those predicted by current plate motions suggest that the Kura fold-thrust belt has accommodated ∼30%–40% (∼25 km) of total Arabia-Eurasia convergence since 5 Ma, and thus forms a first-order structural system within the central portion of the collision zone.

Investigations of the March 2006 African dust storm using ground‐based column‐integrated high spectral resolution infrared (8–13 μm) and visible aerosol optical thickness measurements: 2. Mineral aerosol mixture analyses

The mineral aerosol mixture composition for the March 2006 Saharan dust storm is assessed in this paper on the basis of the analysis of visible to near‐infrared (VIS‐NIR) and infrared (IR) aerosol optical thickness (AOT) spectra obtained during the Portable Infrared Aerosol Transmission Experiment (PIRATE). The AOT spectra from 8 to 13 μm were determined using column‐integrated solar transmission measurements using a Fourier transform infrared spectrometer. To determine the mineralogy and mixture composition of the dust, we determined the expected mineralogy of dust from the Algerian source region in a dust storm environment. Then we computed the modeled VIS‐IR AOT spectra using Mie theory for external and internal mixtures. We compared the modeled VIS‐NIR AOT spectra and derived index of refraction and single‐scattering albedo with the measured values from AERONET and compared the modeled IR AOT spectra with the values from our IR measurements. The fit between the measured and modeled values was best when we used an extinction resonance correction to the Mie theory results to better account for the exact wavelengths and shapes of some of the AOT peaks for mineral particles. The mineralogy and mixture composition of the best dust model includes external mixtures, internal mixtures, and mineralogy dominated by quartz, illite, and calcite. The modeled mean radius was determined, and several modes were computed in agreement with AERONET results.

Remote monitoring of hypersaline environments in San Francisco Bay, CA, USA

As part of a historic remediation project, approximately 61 km2 of salt evaporation ponds in the southern portion of San Francisco Bay, CA (USA) are scheduled for restoration to natural tidal marsh habitat over the next several decades. We have investigated the correlation of remotely sensed infrared spectral information with in situ field measurements and sampling, and evaluated the usefulness of a remote sensing approach to monitor salinity and population distributions of microbial communities in the hypersaline ponds. The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument operated by the Jet Propulsion Laboratory has created a ten‐year archive of spectral information concerning these ponds. We utilized spectral signatures of microbial populations that are sensitive to salinity, and trained a supervised classification algorithm to identify physical parameters from an AVIRIS scene based upon microbe spectra gathered in the field using a portable visible to near‐infrared (VNIR) spectrometer. Our results indicate that automated analyses of hyperspectral observations are capable of detecting variations in microbial populations and discriminating corresponding salinity levels.

Seeking phyllosilicates in thermal infrared data: A laboratory and Martian data case study

Previous analyses of Thermal Emission Spectrometer (TES) data produce results that could suggest a widespread distribution of phyllosilicate minerals over the surface of Mars, whereas studies of visible to near‐infrared (VNIR) data indicate a more limited distribution. We use VNIR detections of phyllosilicates in the vicinity of the Nili Fossae to determine the spectral characteristics of phyllosilicate‐bearing material in the thermal infrared (TIR). By investigating areas of VNIR phyllosilicate detection in more detail, we find that the phyllosilicate‐bearing material corresponds to spectral variation in Thermal Emission Imaging System decorrelation‐stretched TIR images and differences in infrared spectral shape that are consistent with, but not uniquely attributable to, mixtures of phyllosilicates and basalt. Phyllosilicate phases are modeled from TES data at abundances that average 5% over the region and at abundances near the 10–15% detection limit in our specific regions of interest. Deconvolution of numerical mixtures of phyllosilicate and basalt spectra indicates that these low abundances of phyllosilicates likely are not influenced by uncertainties greater than the 10–15% uncertainty of the method. TES spectra and modeled abundances vary between the phyllosilicate‐bearing material and the surrounding region, but this difference in composition cannot be attributed solely to the presence of phyllosilicates. We believe the inconsistencies in phyllosilicate occurrence between TES and VNIR analyses may be explained by the inclusion of phyllosilicates in the models of TES data as substitutes for poorly crystalline phases (e.g., allophane) not currently available in public infrared spectral libraries.

Integrating multi-temporal spectral and structural information to map wetland vegetation in a lower Connecticut River tidal marsh

This study examines the effectiveness of using multi-temporal satellite imagery, field spectral data, and LiDAR top of canopy data to classify and map the common plant communities of the Ragged Rock Creek marsh, located near the mouth of the Connecticut River. Visible to near-infrared (VNIR) reflectance spectra were measured in the field over the 2004–2006 growing seasons to assess the phenological variability of the dominant marsh plant species, Spartina patens, Phragmites australis and Typha spp. Phragmites was best distinguished from other species by its high NIR response late in the growing season. Typha spp. had a high red/green ratio and S. patens had a unique green/blue ratio relative to other species throughout the bulk of the growing season. The field spectra and single date (2004) LiDAR canopy height data were used to define an object-oriented classification methodology for the three plant communities in multi-temporal QuickBird multispectral imagery collected over the same time interval. The classification was validated using an extensive field inventory of marsh species. Overall maximum fuzzy accuracy for the classification was 97% for Phragmites, 63% for Typha spp. and 80% for S. patens meadows and improved to 97%, 76%, and 92%, respectively, using a fuzzy acceptable match measure. This study demonstrated the importance of the timing of image acquisition for the identification of targeted plant species in a heterogeneous marsh. These datasets and protocols may provide coastal resource managers, municipal officials and researchers a set of recommended guidelines for remote sensing data collection for marsh inventory and monitoring.

A Comparative Evaluation of ISODATA and Spectral Angle Mapping for the Detection of Saltcedar Using Airborne Hyperspectral Imagery

Nonnative plant species often cause adverse ecological and environmental impacts on the indigenous species of an area. Remote sensing methods have had mixed successes in providing spatial information on the distribution characteristics of specific vegetation species. Such research has been limited to broad‐band satellite based sensor systems whose spatial and spectral capabilities may not be adequate. Our research focuses on using hyperspectral data and innovative image processing techniques for mapping specific invasive species based on their spectral characteristics. Using the Airborne Imaging Spectroradiometer for Applications (AISA) hyperspectral imager (from Visible to Near Infrared (VNIR)). This research evaluated two methods of processing hyperspectral imagery including the Iterative Self‐Organizing Data (ISODATA) algorithm and Spectral Angle Mapping (SAM) for detecting saltcedar (Tamarix sp.) in Lake Meredith Recreational Area, Texas. A Minimum Noise Fraction (MNF) algorithm was used to remove the inherent noise and redundancy within the dataset during the SAM classification. Validation procedures revealed higher accuracies for the SAM method (83%) when compared to ISODATA (76%) in identifying saItcedar. The immediate benefit of this research has been to provide improved information on the spatial extent and density of saltcedar to land managers for the effective implementation of management programs to control this invasive plant.

Acousto-optic-tunable-filter-based spectropolarimetric imagers for medical diagnostic applications—instrument design point of view

Compact optical imagers that can detect both spectral and polarization signatures are required in many biomedical applications. An acousto-optic-tunable-filter (AOTF)-based imager is ideally suited to provide both agile spectral and polarization signatures. Such an imager can be readily used for real-time in vivo medical diagnostic applications. We develop a family of small, robust, and programmable hyperspectral imagers operating from the ultraviolet (UV) to the long-wave IR (LWIR). Such imagers require minimal data processing because they can acquire images at only select wavelengths of interest. We use AOTFs made of KDP, TeO2, and TAS with Si-based CCD, InGaAs, InSb, and HgCdTe cameras to cover different spectral regions from the UV to the LWIR. Operation of each of these imagers and image acquisition is computer controlled. The most developed imager covers the visible to near-infrared (VNIR) region from 400 to 900 nm, with a 10-nm spectral resolution at 600 nm, it uses an electronically tunable TeO2 AOTF as a bandpass filter, and a nematic liquid crystal retarder to change polarization. We describe our concept in the development of these imagers and present new results obtained using the VNIR imager.