Showing papers on "VNIR published in 2006"

An automatic atmospheric correction algorithm for visible/NIR imagery

Abstract: The automatic correction of atmospheric effects currently requires visible to short‐wave spectral bands (400–2500 nm) to derive high accuracy surface reflectance data. Common techniques employ spectral correlations of dark targets in the short‐wave infrared (SWIR, around 2.2 µm), blue (480 nm) and red (660 nm) regions to derive the aerosol optical depth. A large number of current Earth‐observing satellite sensors have only three or four spectral channels in the visible and near‐infrared (VNIR) region (400–1000 nm), making an automatic image‐based atmospheric correction very difficult. This contribution presents a new algorithm and first results with VNIR imagery. The method starts with the assumption of average clear atmospheric conditions (aerosol optical depth AOD = 0.27, corresponding to a visibility of 23 km) and calculates the surface reflectance in the red and near‐infrared (NIR) bands. The second step derives a mask of dark vegetation pixels. It is calculated using multiple thresholds of vegetation...

Development of four-dimensional imaging spectrometers (4D-IS)

Abstract: The incentive for the 4D-IS concept was driven by the need to adequately resolve all four dimensions of data (2D spatial, spectral, and temporal) with a single, radiometrically calibrated sensor. Very fast changing phenomena are of interest; including missile exhaust plumes, missile intercept events, and lightning strikes, hypervelocity impacts, etc. Present sensor capabilities are limited to imaging sensors (producing spatial image), spectrometers (that produce a mean signature over an entire field of view with no spatial resolution), radiometers (producing in-band radiance over an entire FOV), or imaging spectrometers (or hyperspectral sensors, tunable filter type, pushbroom scanning, imaging Fourier Transform, Fabry-Perot, or CTHIS type) that produce a data cube containing spatial/spectral information but suffer from the fact that the cube acquisition process may take longer time than the temporal scale during which the event changes. The Computer Tomography Imaging Spectrometer (CTIS) is another sensor capable of 4D data collection. However, the inversion process for CTIS is computationally extensive and data processing time may be an issue in real-time applications. Hence, the 4D-IS concept with its ability to capture a full image cube at a single exposure and provide real time data processing offers a new and enhanced capability over present sensors. The 4D-IS uses a reformatter fiber optics to map a 2D image to a linear array that serves as an input slit to an imaging spectrometer. The paper describes three such instruments, a VNIR, a MWIR, and a dual band MW/LWIR. The paper describes the sensors' architecture, mapping, calibration procedures, and remapping the FPA plane into an image cube. Real-time remapping software is used to aid the operator in alignment of the sensor is described. Sample data are shown for rocket motor firings and other events.

Preprocessing of EO-1 Hyperion data

Abstract: A procedure for processing hyperspectral data acquired with Hyperion has been developed with an aim to correct for sensor artifacts and atmospheric and geometric effects. Advances in preprocessing of hyperspectral remote sensing data have enabled more accurate atmospheric correction and have led to the development of new information extraction techniques in the areas of agriculture, forestry, geosciences, and environmental monitoring. These processing and analysis tools have been incorporated into Imaging Spectrometer Data Analysis Systems (ISDAS), a software package developed at the Canada Centre for Remote Sensing (CCRS). The procedure, as applied for Hyperion data, begins with geometric corrections to the short-wave infrared (SWIR) component to register the SWIR and visible near-infrared (VNIR) data spatially. This is followed by the removal of stripes and pixel (column) dropouts and noise reduction, using recently developed automated software tools. The data cube is subsequently analyzed using keyston...

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

Abstract: 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 r...

Evaluating Ecological Condition Using Soil Biogeochemical Parameters and Near Infrared Reflectance Spectra

Abstract: Rapid, repeatable assessment of ecological condition is critical for quantitative ecosystem monitoring. Soils provide a sensitive, integrative indicator for which sampling and analysis techniques are well defined. We evaluated soil properties as indicators of ecological condition (subjectively classified into minimally/moderately/severely degraded based on vegetative, hydrologic and edaphic cues) at 526 sites within Ft. Benning military installation (Georgia, USA). For each sample, we measured 17 biogeochemical parameters, and collected high-resolution diffuse reflectance spectra using visible/near infrared reflectance spectroscopy (VNIRS). VNIR spectra have been related to numerous soil attributes - we examine them here for diagnosing integrated response (i.e., ecological condition). We used ordinal logistic regression (OLR) and classification trees (CT) to discriminate between condition categories using both sets of predictors (biogeochemistry and spectra). Sixteen biogeochemical parameters were significantly different across condition categories; however, multivariate models greatly improved discrimination ([calibration, validation] accuracy of [69%, 66%] and [96%, 73%] for OLT and CT models, respectively). Important predictors included total C, total P, and Mehlich K/Ca/Mg. VNIR spectra further improved discrimination ([calibration, validation] accuracy of [74%, 70%] and [96%, 75%] for OLR and CT models, respectively). While spectra were comparably effective at discriminating minimally degraded sites, they were significantly more effective at discriminating severely degraded sites. Error rates across confounding factors suggest that watershed of origin and landscape position were the only important confounders, likely due to imbalanced sampling. We conclude that multivariate diagnosis improves accuracy, and that VNIR spectroscopy, which yields substantial cost and logistical improvements over conventional analyses, provides an effective tool for rapid condition diagnosis.

New Cloud Detection Algorithm for Multispectral and Hyperspectral Images: Application to ENVISAT/MERIS and PROBA/CHRIS Sensors

Abstract: This work presents a new methodology that faces the problem of accurate identification of location and abundance of clouds in multispectral images acquired by space-borne sensors working in the visible and near-infrared (VNIR) spectral range. The amount of images acquired over the globe every day by the instruments on board Earth Observation satellites makes inevitable that many of these images present cloud covers. The objective of this work is to develop and validate a method that takes advantage of the high spectral and radiometric resolution, and the specific band locations (e.g. the oxygen band) of present multispectral sensors to increase the cloud detection accuracy. Moreover, the method provides probability and cloud abundance rather than flags, which can be used to describe detected clouds (subpixel coverage, cloud type, height, etc) more accurately.

Scene-based Nonuniformity Correction and Bad-pixel Identification for Hyperspectral VNIR/SWIR Sensors

Abstract: We propose and evaluate a new scene-based method for computing nonuniformity corrections for visible or shortwave infrared pushbroom sensors. This method can be used to compute new nonuniformity correction values or to repair or refine existing radiometric calibrations. We demonstrate our methods with data from several different sensor systems.

Intercomparison of Terra ASTER, MISR, and MODIS, and Landsat-7 ETM+

Abstract: The Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) are all onboard the Terra platform. The Landsat-7 platform is in orbit approximately 30 minutes ahead of Terra carrying the Enhanced Thematic Mapper Plus (ETM+) sensor. An important aspect of the use of these sensors, and other Earth Science Enterprise sensors, has been the characterization and calibration of the sensors and validation of their data products to allow synergistic use of the sensor data. The Remote Sensing Group at the University of Arizona has been active in the area of calibration and intercomparison through the use of ground-based test sites. This paper presents the results from the reflectance-base approach using the Railroad Valley Playa test site in Nevada for ASTER, ETM+, MISR, and MODIS and thus effectively a cross-calibration between all four sensors. The results show that there is good agreement between the sensors in the VNIR and all sensors show similar standard deviations of the average with MISR showing the smallest standard deviations and ASTER the largest. ETM+, MISR, and MODIS agree to better than 4% in all bands and better than 2% in equivalent MISR bands land 2. Agreement in the shortwave infrared is not as close with Band 4 of ASTER, Band 5 of ETM+, and Band 6 of MODIS disagreeing by more than 6%. ASTER show large standard deviations and the percent differences for bands 6-9 that are much larger than those seen for MODIS and ETM+.

Survey and analysis of fore-optics for hyperspectral imaging systems

Abstract: Applications for imaging spectrometers are expanding to cover a broader spectral range with higher fidelity, often from the VNIR to the SWIR with one common aperture. These fore-optic systems range from short focal length refractive optics for micro-UAV platforms, to large all-reflective telescopes for surveillance systems. Off-the-shelf lenses and standard prescription telescopes typically do not have the telecentricity and color correction performance to meet foreoptic system requirements for low distortion and broadband operation. This paper evaluates several wide- and narrowfield VIS-SWIR fore-optics designs, describes the effects of fore-optics aberrations on spectrometer performance, and outlines the effects of these constraints on aperture, spectral coverage, and optimal packaging.

Estimation of incident solar radiation on the ground from multispectral satellite sensor imagery

Abstract: A simple and fast, physically based method for the estimation of global radiation is presented It is applicable for clear‐sky multispectral satellite sensor imagery with channels at least in the VNIR region and works without the need for additional ground data The atmospheric influence is taken into account using look‐up tables based on standard atmospheres from the MODTRAN code The algorithm was tested with a time series of nine Landsat‐7 ETM+ scenes of a region in north‐eastern Germany Remotely sensed global radiation is in close agreement with in situ measurements of the German Meteorological Service as indicated by RMS deviations of 20–24 W m−2 depending on the bands and atmospheric parameterization employed The image‐derived global radiation at this level of accuracy is a useful supplement for studies in landscape ecology and related fields, for example as input for regional modelling of evapotranspiration

Anomaly detection using the hyperspectral polarimetric imaging testbed

Abstract: The Hyperspectral Polarimetric Imaging Testbed contains a VNIR, SWIR, and three-axis imaging polarimeter, each operating simultaneously through a common fore-optic. The system was designed for the detection of man-made objects in natural scenes. The imagery produced by the various imaging legs of the system is readily fused, due to the identical image format, FOV and IFOV of each optical leg. The fused imagery is shown to be useful for the detection of a variety of man-made surfaces. This paper describes the general design and function of the mature system, the Stochastic Gaussian Classifier processing method used for hyperspectral anomaly detection, the polarimetric image processing methods, and a logical decision structure for the identification of various surface types. The paper will also describe in detail the detection results for a variety of targets obtained in field testing conducted with the system.

Imaging Spectrometry for Geological Applications

Abstract: Reflectance and emittance spectra have been used for many years to obtain compositional information about the Earth's surface. Electronic transition and charge transfer processes associated with transition-metal ions such as Fe, Ti, Cr, and so on produce diagnostic absorption features in the visible and near-infrared (VNIR) wavelength region of the spectra of minerals and rocks, while vibrational processes in H2O and OH− produce fundamental overtone absorptions in the shortwave infrared (SWIR) portion of the spectrum. Field and laboratory studies have demonstrated that reflectance spectroscopy can be used for mineral identification and further geological studies. The translation of these measurements to imaging data led to the development of the field of imaging spectrometry in remote sensing. Imaging spectrometers acquire images in a large number of narrow contiguous spectral bands to enable the extraction of reflectance spectra at a pixel scale that can be directly compared with similar spectra measured either in the field or in a laboratory. In this chapter, the use of imaging spectrometer data for geological applications is discussed by describing the processing chain of data analysis from the raw data acquisition to prospective applications. Several topics are addressed. An appraisal of future spaceborne imaging spectrometer missions and potential prospective applications provides insight into this vastly growing field of research.

Field imaging spectroscopy: A new methodology to assist the description, interpretation, and archiving of paleoseismological information from faulted exposures

Abstract: [1] We present a new methodology to acquire, interpret, and store stratigraphic and structural information from paleoseismic exposures. For this study we employed portable hyperspectral cameras to acquire field-based visible near-infrared (VNIR) and short-wave infrared (SWIR) high spatial/spectral resolution images. We first analyzed 400 small sediments cores using a hand-held, single-pixel spectrometer (VNIR-SWIR) to determine the feasibility of the method and to assess its potential problems. We then acquired high-spatial resolution (submillimeter) spectral data of a large sample (60 × 60 cm) and four cores (7.5 × 60 cm) of faulted sediments from a paleoseismic excavation using portable push broom AISA hyperspectral scanner. These data, which contain 244 (VNIR) and 245 (SWIR) narrow contiguous spectral bands between 400 and 1000 and 960 to 2403 nm, respectively, were processed to obtain the reflectance spectra at each pixel. In this study we are focusing on the analysis of the short-wave infrared data sets (SWIR). The SWIR data were transformed into relative reflectance and geometrically corrected and processed with well-known imaging processing algorithms. Selected spectra were then used to create false color composite images that best display the faulted stratigraphy. We compared the hyperspectral images to those recorded by a digital camera as well as directly to the field sample and show that the reflectance properties of the materials in the SWIR region cannot only enhance the visualization of the sedimentary layers and other features that are not obvious to the human eye but can also make visible many detailed features that were not visible in the digital photography. This new data collection and interpretation methodology, herein termed field imaging spectroscopy, makes available, for the first time, a tool to quantitatively analyze paleoseismic and stratigraphic information. In addition, hyperspectral data sets in the visible short-wave infrared spectral range provide a better alternative for data storage. The reflectance spectra at each pixel of the images provide unbiased compositional information that can be processed in a variety of ways to assist with the interpretation of stratigraphy and structure at a site.

New method and instrument to diagnose crop growth status in greenhouse based on spectroscopy

Abstract: Spectral reflectance of cucumber leaves in greenhouse was measured using an ASD FieldSpec Pro VNIR spectrometer with natural illumination. Two sensitive wavelengths, 527 nm and 762 nm, were selected to evaluate the nitrogen content of the cucumber leaves. A model was established and validated using normal difference color index(NDCI) with the correlation coefficient of 0.881. Based on the above efforts, a handheld spectral instrument was developed to diagnose the growth status of the crop in greenhouse using fiber optics. The instrument was mainly composed of four parts: reflected light acquisition system, light intensity measurement unit, signal conditioning unit, and data acquisition system. The sunlight reflected by the crop was transmitted by the fiber, and passed through the light filter to obtain light at the sensitive wavelengths. Finally it was transformed into electronic signal by the photoelectric transistor, and was used to diagnose the growth status of the crop according to the evaluation model. The result showed that the developed instrument was practical.

Miniaturization of a VNIR hyperspectral imager

Abstract: A new approach for the design and fabrication of a miniaturized Hyperspectral imager is described. A unique and compact instrument has been developed by taking advantage of light propagation within bonded solid blocks of fused silica. The resulting microHSI is a VNIR hyperspectral sensor capable of operating in the 400-1000 nm wavelength range developed, patented, and built by NovaSol. The microHSI spectrograph weighs 12.4 oz from slit input to camera output. The microHSI can accommodate either custom foreoptics or C-mount input lenses to adapt to a wide range of fields-of-view (FOV). The prototype microHSI uses a telecentric F2.8 foreoptic, with 36 mm focal length, to cover a 15 degree FOV. It can resolve 960 spatial pixels, resulting in a 280 μrad IFOV for this particular foreoptics implementation. With a 1 nm/unbinned pixel dispersion, the spectrometer spectral resolution is 3.5 nm. Results of field and laboratory testing of the prototype microHSI are presented and show that the sensor consistently meets technical performance predictions. The prototype microHSI employs a holographic diffraction grating embedded within the optical blocks resulting in a 19% diffraction efficiency. Future units are anticipated to incorporate a blazed grating for improved throughput and SNR. The microHSI concept can be extended to operation over other wavelength regions. Designs are nearing completion for a SWIR version of the device, and a miniaturized LWIR microHSI sensor is currently at the conceptual design stage.

Airborne VNIR and SWIR Imaging Spectrometer and its Multi-sensor Remote Sensing Applications

Abstract: An Airborne VNIR and SWIR Imaging Spectrometer (AVSIS) system is fully integrated with grating-based VNIR and SWIR imaging spectrographs, a customized CCD camera and an InGaAs camera, a precision GPS/IMU setup, a specially- configured instrument PC, and a dedicated AVSIS operation autonomous software package. AVSIS is a fast hyperspectral imaging system capable of imaging simultaneously 129 spectral bands across a 1,392-pixel swathwidth with 1-meter resolution in a 445-900 nm spectral range, along with 228 additional synchronized SWIR bands in a 900-1700 nm range with a 320 coarse pixel swath, which matches the maximum acrosstrack viewing angle that the VNIR part covers. All of these bands are digitized at 12 bits each with the same pushbroom scanning rate up to 60 scanlines/sec. AVSIS is interoperational with a multispectral framing camera system for simultaneous stereo pairs. Its initial hyperspectral/multispectral/stereo synthetic remote sensing applications have been discussed; and mapping- quality data samples are presented.

Vicarious calibration of ASTER backward-looking telescope

Abstract: The Remote Sensing Group at the University of Arizona has successfully used various vicarious calibration methods for the absolute radiometric calibration of over 13 separate sensors since 2000 including nearly 40 sets of ground-based data collected at large uniform test sites imaged by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The results from this work have been used to examine the VNIR and SWIR bands showing differences that exceed 10% in some bands. The current work extends the reflectance-based approach to the backward-looking telescope of the VNIR system of ASTER that is used for development of digital elevation models. The off-nadir band, Band 3B is identical to the NIR band of ASTER Band 3 except with a view of 23.5 degrees relative to the nadir-looking telescope. The study of Band 3B is done relative to Band 3 using the playa sites in California and Nevada as well as reflectance-based calibration approaches. The calibration of the nadir and off-nadir views agreed to better than 0.7% for five dates spanning 2000-2002 in the summer months at Ivanpah Playa. Other dates and sites showed differences much larger than can be explained by radiative transfer modeling and atmospheric effects pointing to a possible surface directional effect.

Spectral unmixing of hyperspectral data to map bauxite deposits

Abstract: This paper presents a study about the potential of remote sensing in bauxite exploration in the Kolli hills of Tamilnadu state, southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM - DEM in this study. A new approach of spectral unmixing of ASTER image data delineated areas rich in alumina. Various geological and geomorphological parameters that control bauxite formation were also derived from the ASTER image. All these information, when integrated, showed that there are 16 cappings (including the existing mines) that satisfy most of the conditions favouring bauxitization in the Kolli Hills. The study concludes that spectral unmixing of hyperspectral satellite data in the VNIR and SWIR regions may be combined with the terrain parameters to get accurate information about bauxite deposits, including their quality.

The study of infrared spectrum of space target

Abstract: The detecting and identifying the space target using infrared spectrum of space target is very effective method.The principle of satellite infrared spectrum is discussed,and the infrared spectrum on detectors was simulated by the mathematic model,and the influences of the parameters to the infrared spectrum of the target and infrared spectrum of space target are analyzed.

Parametric prediction of the POD and PFA for reflective hyperspectral imaging systems: dependencies on target, scene and sensor design characteristics, and detection algorithms

Abstract: Advanced ground and space-based hyperspectral imager (HSI) concepts are being developed for a wide variety of scientific, civil, and military applications. Users and developers of these systems often require the specification of system performance in terms of receiver-operator characteristic (ROC) curves which plot probability-of-detection (POD) versus probability-of-false-alarm (PFA). In this paper we describe and illustrate the use of a scene-based modeling tool used to explore ROC curve parametric dependencies on target, scene, and HSI sensor design characteristics and detection algorithms in the visible/near infrared to shortwave infrared (VNIR/SWIR) spectral regime (i.e. from 0.4 to 2.5 microns). The magnitudes of the target and background spectral signatures are synthesized using MODTRAN; this accounts for pertinent solar elevation angle and albedo assumptions. Selected spectral input scenes (based on measured data) are used assuming imbedded spectral targets (selectable), where a fill-factor parameter is used to account for target dimension compared to sensor ground footprint. The HSI sensor sensitivity characteristics are imbedded via the noise-equivalent reflectivity difference (NEuρ) figure-of-merit which is computed spectrally based on a given sensor design configuration. Finally the POD, PFA and hence ROC parametrics are generated using a distinct candidate detection algorithm. The roles of scene clutter, illumination conditions, and sensor signal-to-noise ratio are made clear in simulation examples. In addition the impact of limited scene extent (limited scene pixel count) on the accuracy of the PFA predictions is noted and discussed.

Airborne hyperspectral data collection with the UMBC VNIR sensor

Abstract: The University of Maryland Baltimore County (UMBC) airborne Visible-Near Infrared (VNIR) hyperspectral sensor is a grating spectrometer that collects data in the 380 to 985 nm spectral range with spectral resolution as high as 1.15 nm. This imager is a push-broom type sensor utilizing a two dimensional charge coupled device (CCD, 480×640) camera to collect the spectral information along a single line on the ground perpendicular to the aircraft flight line. The UMBC sensor can provide measurements for a variety of studies, including land development and land use, cultivated and natural vegetation and forestry, and water turbidity and coastal environments. Due to the sensor's wealth of spectral bands, high signal-to-noise, and narrow band widths, a number of atmospheric constituents can be also detected that can be incorporated into atmospheric correction models to benefit the retrievals of surface properties. We present a detailed description of the sensor as well as preliminary results of its calibration in this paper. Related on-going research and some potential applications of this sensor are summarized.

Onboard calibration status of ASTER

Abstract: The ASTER is a high-resolution optical sensor for observing the Earth on the Terra satellite launched in 1999. The ASTER consists of three radiometers, the VNIR in the visible and near-infrared region, the SWIR in the shortwave infrared region, and the TIR in the thermal infrared region. The on-board calibration devices of the VNIR and the SWIR were two halogen lamps and photodiode monitors. In orbit three bands of the VNIR showed a rapid decrease in the output signal while all SWIR bands remained stable. The TIR has one on-board blackbody and is unable to see the dark space. Therefore the temperature of the on-board blackbody of the TIR remains at 270 K in the short-term calibration for the offset calibration, and is varied from 270 K to 340 K in the long term calibration for the offset and gain calibration. The long term calibration showed a decrease of the TIR response in orbit. The radiometric calibration coefficients of the VNIR and the TIR were fit to smooth functions.