Showing papers on "VNIR published in 2005"

Determination of visible near-IR absorption coefficients of mammalian fat using time- and spatially resolved diffuse reflectance and transmission spectroscopy.

Abstract: In-vivo optical spectroscopy and the determination of tissue absorption and scattering properties have a central role in the development of novel optical diagnostic and therapeutic modalities in medicine. A number of techniques are available for the optical characterization of tissue in the visible near-IR region of the spectrum. An important consideration for many of these techniques is the reliability of the absorption spectrum of the various constituents of tissue. The availability of accurate absorption spectra in the range 600 to 1100 nm may allow for the determination of the concentration of key tissue constituents such as oxy- and deoxy-hemoglobin, water, and lipids. The objective of the current study is the determination of a reliable absorption spectrum of lipid(s) that can be used for component analysis of in-vivo spectra. We report the absorption spectrum of a clear purified oil obtained from pig lard. In the liquid phase above 36°C, the oil is transparent and thus suitable for collimated transmission measurements. At room temperature, the oil is a solid grease that is highly scattering. The absorption and scattering properties in this solid phase are measured using time- and spatially resolved diffuse reflectance spectroscopy. Using these three independent measurement techniques, we have determined an accurate estimate for the absorption spectrum of mammalian fat.

Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi- and hyperspectral imagery

Abstract: We describe a new visible-near infrared short-wavelength infrared (VNIR-SWIR) atmospheric correction method for multi- and hyperspectral imagery, dubbed QUAC (QUick Atmospheric Correction) that also enables retrieval of the wavelength-dependent optical depth of the aerosol or haze and molecular absorbers. It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The approach is based on the empirical finding that the spectral standard deviation of a collection of diverse material spectra, such as the endmember spectra in a scene, is essentially spectrally flat. It allows the retrieval of reasonably accurate reflectance spectra even when the sensor does not have a proper radiometric or wavelength calibration, or when the solar illumination intensity is unknown. The computational speed of the atmospheric correction method is significantly faster than for the first-principles methods, making it potentially suitable for real-time applications. The aerosol optical depth retrieval method, unlike most prior methods, does not require the presence of dark pixels. QUAC is applied to atmospherically correction several AVIRIS data sets and a Landsat-7 data set, as well as to simulated HyMap data for a wide variety of atmospheric conditions. Comparisons to the physics-based Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) code are also presented.

ASTER geometric performance

Abstract: The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system acquires multispectral images ranging from the visible to thermal infrared region. The ASTER system consists of three subsystems: visible and near-infrared (VNIR), short-wave infrared (SWIR) and thermal infrared (TIR) radiometers. The VNIR subsystem has a backward-viewing telescope as well as a nadir one. To deliver data products of high quality from the viewpoint of geolocation and band-to-band registration performance, a fundamental program, called Level-1 data processing, has been developed for images obtained using four telescopes with a cross-track pointing function. In this work, the methodology of the geometric validation is first described. Next, the image quality of ASTER data products is evaluated in view of the geometric performance over a period of four years. The band-to-band registration accuracy in the subsystem is better than 0.1 pixels and that between subsystems is better than 0.2 pixels. This means that the geometric database is determined accurately and the image matching method based on a cross-correlation function is effective in the operational usage.

Polarimetric Remote Sensing in the Visible to Near Infrared

Abstract: Polarization adds another dimension to the spatial intensity and spectral information typically acquired in remote sensing. Polarization imparted by surface reflections contains unique and discriminatory signatures which may augment spectral target-detection techniques. While efforts have been made toward quantifying the polarimetric bidirectional reflectance distribution function (pBRDF) responsible for target material polarimetric signatures, little has been done toward developing a description of the polarized background or scene clutter. An approach is presented for measuring the pBRDF of background materials such as vegetation. The governing equation for polarized radiance reaching a sensor aperture is first developed and serves as a basis for understanding outdoor pBRDF measurements, as well as polarimetric remote sensing. The pBRDF measurements are acquired through an imaging technique which enables derivation of the BRDF variability as a function of the ground separation distance (GSD). An image subtraction technique is used to minimize measurement errors resulting from the partially polarized downwelled sky radiance. Quantifying the GSD-dependent BRDF variability is critical for background materials which are typically spatially inhomogeneous. Preliminary results from employing the measurement technique are presented.

Integrated VIS-NIR Hyperspectral / Thermal-IR Electro-Optical Payload System for a Mini-UAV

Abstract: This paper presents the development of a modern electro-optical payload system for remote sensing from a mini-UAV. It is aimed at applications of natural disasters monitoring, in particular forest fires. Both the sensor and the mini-UAV platform are being developed at the Dept. of Space Science and Engineering (DISIS) of the University of Naples “Federico II.” The core of the system is an integrated, multi-band sensor that includes a thermal imager and a hyperspectral sensor in VNIR band. Instrument characterization, laboratory tests, and payload architecture are discussed.

Radiometric performance evaluation of ASTER VNIR, SWIR, and TIR

Abstract: Radiometric performance of the Advanced Spectrometer for Thermal Emission and Reflection Radiometer (ASTER) is characterized by using acquired imagery data. Noise-equivalent reflectance and temperature, sensitivity (gain), bias (offset), and modulation transfer function (MTF) are determined for the visible and near-infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR) radiometers that constitute ASTER. The responsivity evaluated from onboard calibration (OBC) and from instrumented scenes show similar trends for the VNIR: the OBC data yield 2.7% to 5.5% a year for the VNIR. The SWIR response changed less than 2% in the 3.5 years following launch. The zero-radiance offsets of most VNIR and SWIR bands have increased about 1/2 digital number per year. The in-orbit noise levels, calculated by the standard deviation of dark (VNIR and SWIR) or ocean (TIR) scenes, show that all bands are within specification. The MTF at Nyquist and 1/2 Nyquist frequencies was determined for all bands using the Moon (VNIR and SWIR) or terrestrial scenes with lines of sharp thermal contrast. In-orbit performance along-track and cross-track is better than prelaunch for the VNIR and SWIR bands in nearly all cases; the TIR effectively meets specification in-orbit.

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

Abstract: 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, TeO 2 , 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 TeO 2 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

Onboard calibration of the ASTER instrument

Abstract: The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution optical sensor for observing the Earth carried on the National Aeronautics and Space Administration Terra satellite. ASTER consists of three radiometers covering the following regions: visible and near-infrared (VNIR), shortwave infrared (SWIR), and thermal infrared (TIR). The preflight calibration of VNIR and SWIR utilized standard large integrating spheres whose radiance levels were traceable to primary standard fixed-point blackbodies. The onboard calibration devices for the VNIR and SWIR consist of two halogen lamps with photodiode monitors. In orbit, all three bands of the VNIR showed rapid decreases in the output signal while all SWIR bands remained stable. The TIR onboard blackbody was calibrated against a standard blackbody from 100-400 K in a vacuum chamber before launch. The TIR is unable to see the dark space. The temperature of the TIR onboard blackbody remains at 270 K for a short-term calibration to determine any offset and is varied from 270-340 K for a long-term calibration of both the offset and gain. The long-term calibration just after launch was consistent with the prelaunch calibration but then showed a steady decrease of the TIR response over the five years of operation to date.

Spatial resolution enhancement of ASTER thermal bands

Abstract: Image fusion aims at the exploitation of the information conveyed by data acquired by different imaging sensors. A notable application is merging images acquired from space by panchromatic and multi- or hyper-spectral sensors that exhibit complementary spatial and spectral resolution. Multiresolution analysis has been recognized efficient for image fusion. The Generalized Laplacian Pyramid (GLP), in particular, has been proven as the most efficient scheme due to its capability of managing images whose scale ratios are fractional numbers (non-dyadic data) and to its simple and easy implementation. Data merge based on multiresolution analysis, however, requires the definition of a model establishing how the missing spatial details to be injected into the multi-spectral bands are extracted from the panchromatic image. The model can be global over the whole image or depend on the local space-spectral context. This paper reports results on the fusion of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Each of the five thermal infrared (TIR) images (90m) is merged with the most correlated visible-near infrared (VNIR) image (15m). Due to the 6:1 scale ratio, the GLP has been utilized. The injection of spatial details has been ruled by means of the Spectral Distortion Minimizing (SDM) model that minimizes the spectral distortion between the resampled and fused images. Notwithstanding the lack of a spectral overlap between the VNIR and the TIR bands, experimental results show that the fused images keep their spectral characteristics while the spatial resolution is enhanced.

Preprocessing of EO-1 Hyperion Hyperspectral Data

Abstract: EO-1′s Hyperion sensor provides a new class of earth observation data for improved Earth surface characterization.Hyperion acquires data in pushbroom mode with two spectrometers,one in the visible and near infrared(VNIR)range and another in the short-wave infrared(SWIR)range.Although data has been radiometricly corrected,but preprocessing of Hyperion data is required before analysis.The preprocessing for Hyperion data includes:(1) Remove of zeroed bands and strongest water vapour bands;(2) Re-calibration,because the data were scaled by 40 for the VRIN and 80 for the SWIR;(3) Fixing of bad pixels;(4) Remove of dark vertical strips;(5) Hyperion Smile reduction;(6) Atmospheric correction and smooth of spectral bands;(7)Geometric correction.After the preprocessing 176 bands out of a total of 242 bands were ready for further analysis.

Spaceborne visible and thermal infrared lithologic mapping of impact-exposed subsurface lithologies at the Haughton impact structure, Devon Island, Canadian High Arctic: Applications to Mars

Abstract: This study serves as a proof-of-concept for the technique of using visible-near infrared (VNIR), short-wavelength infrared (SWIR), and thermal infrared (TIR) spectroscopic observations to map impact-exposed subsurface lithologies and stratigraphy on Earth or Mars. The topmost layer, three subsurface layers and undisturbed outcrops of the target sequence exposed just 10 km to the northeast of the 23 km diameter Haughton impact structure (Devon Island, Nunavut, Canada) were mapped as distinct spectral units using Landsat 7 ETM+ (VNIR/SWIR) and ASTER (VNIR/SWIR/ TIR) multispectral images. Spectral mapping was accomplished by using standard image contrast- stretching algorithms. Both spectral matching and deconvolution algorithms were applied to image- derived ASTER TIR emissivity spectra using spectra from a library of laboratory-measured spectra of minerals (Arizona State University) and whole-rocks (Ward's). These identifications were made without the use of a priori knowledge from the field (i.e., a "blind" analysis). The results from this analysis suggest a sequence of dolomitic rock (in the crater rim), limestone (wall), gypsum-rich carbonate (floor), and limestone again (central uplift). These matched compositions agree with the lithologic units and the pre-impact stratigraphic sequence as mapped during recent field studies of the Haughton impact structure by Osinski et al. (2005a). Further conformation of the identity of image- derived spectra was confirmed by matching these spectra with laboratory-measured spectra of samples collected from Haughton. The results from the "blind" remote sensing methods used here suggest that these techniques can also be used to understand subsurface lithologies on Mars, where ground truth knowledge may not be generally available.

Resolution enhancement of ASTER shortwave and thermal infrared bands based on spectral similarity

Abstract: The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) consists of three subsystems divided by the wavelength region: Visible and Near-Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR) subsystems. The VNIR, SWIR and TIR subsystems have 3, 6, and 5 spectral bands with the spatial resolution of 15, 30, and 90m, respectively. The purpose of this study is to propose an algorithm for generating SWIR and TIR imagery with a 15m resolution based on spectral similarity. In the algorithm, SWIR images are first super-resolved using VNIR images, and TIR images are then super-resolved using VNIR and super-resolved SWIR images. The first step is as follows: 1) degrade the resolution of the VNIR images to 30m by pixel aggregation with the point spread function (PSF) of SWIR, 2) generate a homogeneous pixel map with a 30m resolution from the original VNIR images, 3) generate a multi-way tree for VNIR and SWIR spectra by stepwise clustering for the 30m-resolution VNIR and SWIR images, 4) generate super-resolved SWIR images by allocating the most likely SWIR spectrum to each 15m-resolution pixel based on spectral similarity in VNIR using the 30m-resolution VNIR and SWIR images, and the multi-way tree, and 5) modify the super-resolved SWIR images using the PSF as to be fully restorable to the original images. The second step is similar, except that super-resolved TIR images are derived from both the VNIR and the super-resolved SWIR images. In the latter part of the study, the algorithm is validated using ASTER data.

Megacollect 2004: hyperspectral collection experiment of terrestrial targets and backgrounds of the RIT Megascene and surrounding area (Rochester, New York)

Abstract: This paper describes a collaborative collection campaign to spectrally image and measure a well characterized scene for hyperspectral algorithm development and validation/verification of scene simulation models (DIRSIG). The RIT Megascene, located in the northeast corner of Monroe County near Rochester, New York, has been modeled and characterized under the DIRSIG environment and has been simulated for various hyperspectral and multispectral systems (e.g., HYDICE, LANDSAT, etc.). Until recently, most of the electro-optical imagery of this area has been limited to very high altitude airborne or orbital platforms with low spatial resolutions. Megacollect 2004 addresses this shortcoming by bringing together, in June of 2004, a suite of airborne sensors to image this area in the VNIR, SWIR, MWIR, and LWIR regions. These include the COMPASS (hyperspectral VNIR,SWIR), SEBASS (hyperspectral LWIR), WASP (broadband VIS, SWIR, MWIR, LWIR) and MISI (hyperspectral VNIR, broadband SWIR, MWIR, LWIR). In conjunction with the airborne collections, an extensive ground truth measurement campaign was conducted to characterize atmospheric parameters, select targets, and backgrounds in the field. Laboratory measurements were also made on samples to confirm the field measurements. These spectral measurements spanned the visible and thermal region from 0.4 to 20 microns. These measurements will help identify imaging factors that affect algorithm robustness and areas of improvement in the physical modeling of scene/sensor phenomena. Reflectance panels have also been deployed as control targets to both quantify sensor characteristics and atmospheric effects. A subset of these targets have also been deployed as an independent test suite for target detection algorithms. Details of the planning, coordination, protocols, and execution of the campaign will be discussed with particular emphasis on the ground measurements. The system used to collect the metadata of ground truth measurements and disseminate this data will be described. Lastly, lessons learned in the field will be underscored to highlight additional measurements and changes in protocol to improve future collections of this area.

Cloud detection for CHRIS/Proba hyperspectral images

Abstract: Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant source of error in both sea and land cover biophysical parameter retrieval. Sensors with spectral channels beyond 1 um have demonstrated good capabilities to perform cloud masking. This spectral range can not be exploited by recently developed hyperspectral sensors that work in the spectral range between 400- 1000 nm. However, one can take advantage of their high number of channels and spectral resolution to increase the cloud detection accuracy, and to describe properly the detected clouds (cloud type, height, subpixel coverage, could shadows, etc.) In this paper, we present a methodology for cloud detection that could be used by sensors working in the VNIR range. First, physically-inspired features are extracted (TOA reflectance and their spectral derivatives, atmospheric oxygen and water vapour absorptions, etc). Second, growing maps are built from cloud-like pixels to select regions which potentially could contain clouds. Then, an unsupervised clustering algorithm is applied in these regions using all extracted features. The obtained clusters are labeled into geo-physical classes taking into account the spectral signature of the cluster centers. Finally, an spectral unmixing algorithm is applied to the segmented image in order to obtain an abundance map of the cloud content in the cloud pixels. As a direct consequence of the detection scheme, the proposed system is capable to yield probabilistic outputs on cloud detected pixels in the image, rather than flags. Performance of the proposed algorithm is tested on six CHRIS/Proba Mode 1 images, which presents a spatial resolution of 32 m, 62 spectral bands with 6-20 nm bandwidth, and multiangularity.

Prediction of the radiometric calibration coefficients of ASTER/TIR

Abstract: Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), on the NASA Terra satellite, has three radiometers, the VNIR, SWIR and TIR. The TIR radiometer has five bands (10 to 14) in the thermal infrared region with a spatial resolution of 90 m. These TIR bands are radiometrically calibrated by a single onboard blackbody whose temperature can be changed between 270 K and 340 K. In the normal operation mode the blackbody is kept at 270 K, and a constant coefficient in a quadratic radiometric calibration equation for each detector is adjusted at that temperature before each Earth observation. Once in 33 days the gain term can be updated by a long term calibration in which the blackbody is measured at 270, 300, 320, and 340 K. The sensor response of all bands (particularly band 12) has been degrading since the launch, and periodical updating of the gain coefficient does not fully follow the degradation, so that the calibration error on level-1 products is sometimes unacceptable. We therefore have developed approximation equations for the coefficients to predict the most reasonable radiometric calibration coefficients (RCC) at the time of the observation. This will be implemented soon in the Level-1 data processing.

Correction of stray light and filter scratch blurring for ASTER imagery

Abstract: Stray light components in images obtained by the shortwave infrared (SWIR) and visible near-infrared (VNIR) radiometers of the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) were investigated. A simple method, which is equivalent to the van Cittert method of deconvolution, was used for correction. The stray light components were estimated using the image obtained during lunar observation, and the improvement in image quality was examined after stray light correction. The calculation is performed in the space domain, and application to the filter scratch problem of the ASTER/SWIR sensor, which has a scratch on the interference filter resulting in partially degenerated images, is also demonstrated.

A short wave infrared hyperspectral imager for landmine detection

Abstract: DRDC Suffield and Itres Research have jointly investigated the use of visible and infrared hyperspectral imaging for landmine detection since 1988. There has been considerable success detecting surface-laid landmines by classification of their visible/near infrared (VNIR - 400 to 1000 nm wavelength) spectral signatures, but it has not been possible to find VNIR spectral characteristics that would generically distinguish anthropogenic objects from natural features such as rocks, vegetation, soil, etc. Preliminary studies in 1998 suggested that it might be possible to develop such a generic classifier in the short wave infrared (SWIR) and that detection performance might improve. Because of a lack of available SWIR hyperspectral imagers with adequate performance for mine detection, a prototype pushbroom SWIR hyperspectral imager was developed and completed in summer 2002. The now commercially available instrument, sasi , has 160 bands over a spectral range of 850 to 2450 nm, signal to noise ratio of 400:1 with f/1.8 fore-optics, and 600 pixels over a 37.7° field of view. A number of mission flights have been carried out and excellent imagery obtained. In October 2003, Itres and DRDC Suffield personnel obtained field SWIR hyperspectral imagery in the DRDC Suffield Mine Pen of numerous surface-laid mines, one buried mine, other surface-laid human-made items, background materials and people from a horizontally scanning personnel-lift at an altitude of roughly 5 m. Preliminary indications are that a simple generic classification decision boundary should be able to distinguish surface-laid landmines from many human-made artifacts and natural materials. The buried mine was not detected, but the mine had been buried for several years and hence there would be no residual surface disturbance. Furthermore, the small sample size and limited observation time make it difficult to generalize about SWIR performance for buried mines. The instrument is described and the preliminary results of the trial, planned improvements and future research are discussed.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

SNR estimation for advanced hyperspectral space instrument

Abstract: EnMAP (Environmental Mapping and Analysis Program) is one of the selected proposals for the national German Space Program. The EnMap project includes the technological design of the Hyperspectral Spaceborne Instrument and the algorithms development of the classification. EnMap will be developed to meet the requirements of the observation and investigation of ecosystem parameters for forestry, soil/geological environments and coastal zones/inland waters. It provides high-quality calibrated data and data products to be used as inputs for improved modelling and understanding of biospheric/geospheric processes, high-spectral resolution observations of biophysical, biochemical, and geochemical variables. This contribution describes some technological and theoretical aspects of the technical solution of the Hyperspectral Pushbroom Sensor working in the VNIR and SWIR spectral range. The Hyperspectral Pushbroom Imaging Spectrometer requires at least two different 2−dimensional detector array types, with one dimension for the spatial and the second dimension for the image information. The VNIR quantum detector will be sensitive from 420 nm up to 1030 nm and the SWIR detector from 950 nm up to 2450 nm. The VNIR modelling shows the difficulties of the SNR of the blue channels. Some measures will be discussed to improve this situation. The discussion will be lead to the requirements of the CCD, focal plane and to the data acquisition scenarios. The SWIR stability modelling gives an overview of the requirements to the detector and of some problems of the detector related system design.

Experimental Study on Total Nitrogen Concentration in Soil by VNIR Reflectance Spectrum

Abstract: In this paper,the experimental study on extracting total nitrogen in soil by VNIR (visible-near infrared) spectrum is introduced.First,the relationships between absorption features and nitrogen concentration to select the absorption features significantly correlated with nitrogen are analyzed.Then several parameters of spectra in the selected absorption features are calculated,including inverse spectra (1/R),first derivative reflectance spectra (FDR),inverse-log spectra (log (1/R)) and Depth.Using stepwise multiple regression method,the authors establish the statistical relationships between these parameters and nitrogen concentration.The results show good prediction performance: R~2a for model samples are 0.789,0.736,0.753 and 0.699 respectively,and R~2a for test samples are 0.759,0.794,0.468 and 0.725 respectively.The study indicates that soil spectrum in the VNIR range has the potential for the rapid simultaneous prediction of nitrogen concentration.

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

Abstract: To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

Aerial high resolution imaging of the mistletoe for the assessment of forest decline in fir stands

Abstract: Silver fir (Abies alba Mill.) is the most widely distributed and the most important commercial conifer species in Croatia. The growing stock of silver fir accounts for about 65% of the total conifer growing stock in Croatia. However, silver fir is also the most endangered tree species in these regions. The results of field research show a significant presence of mistletoe (Viscum album L. ssp. abietis (Wiesb.) Abrom.) on silver firs in Croatia. The current work deals with the issue of mistletoe detection. The purpose of preliminary research was to develop an efficient method of mistletoe detection. Ground-based tests, performed in May 2004 on mistletoe and silver fir, were aimed at formulating a method that will be implemented in the aerial acquisition system. A high-resolution digital camera MS-3100 (four 8 bit channels in VNIR wavelengths, 1392x1039 pixels) and a hyper spectral line scanner V9 (up to 90 channels in VNIR wavelengths) were used with the acquisition systems. The expectation that mistletoe can successfully be detected with a high-resolution digital VNIR camera MS3100 was confirmed by preliminary results.

Spatial enhancement of tir aster data via vnir images and generalized laplacian decomposition

Abstract: Image fusion aims at the exploitation of the information conveyed by data acquired by different imaging sensors. A notable application is merging images acquired from space by panchromatic and multi- or hyper-spectral sensors that exhibit complementary spatial and spectral resolution. Multiresolution analysis has been recognized efficient for image fusion. The Generalized Laplacian Pyramid (GLP), in particular, has been proven as the most efficient scheme due to its capability of managing images whose scale ratios are fractional numbers (non-dyadic data) and to its simple and easy implementation. Data merge based on multiresolution analysis, however, requires the definition of a model establishing how the missing spatial details to be injected into the multispectral bands are extracted from the panchromatic image. The model can be global over the whole image or depend on the local space-spectral context. This paper reports results on the fusion of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Each of the five thermal infrared (TIR) images (90m) is merged with the most correlated visible-near infrared (VNIR) image (15m). Due to the 6:1 scale ratio, the GLP has been utilized. The injection of spatial details has been ruled by means of the Spectral Distortion Minimizing (SDM) model that minimises the spectral distortion between the resampled and fused images. Notwithstanding the lack of a spectral overlap between the VNIR and the TIR bands, experimental results show that the fused images keep their spectral characteristics while the spatial resolution is enhanced.

Improvement in absolute calibration accuracy of Landsat-5 TM with Landsat-7 ETM+ data

Abstract: The ability to detect and quantify changes in the Earth's environment depends on satellites sensors that can provide calibrated, consistent measurements of Earth's surface features through time. A critical step in this process is to put image data from subsequent generations of sensors onto a common radiometric scale. To evaluate Landsat-5 (L5) Thematic Mapper's (TM) utility in this role, image pairs from the L5 TM and Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors were compared. This approach involves comparison of surface observations based on image statistics from large common areas observed eight days apart by the two sensors. The results indicate a significant improvement in the consistency of L5 TM data with respect to L7 ETM+ data, achieved using a revised Look-Up-Table (LUT) procedure as opposed to the historical Internal Calibrator (IC) procedure previously used in the L5 TM product generation system. The average percent difference in reflectance estimates obtained from the L5 TM agree with those from the L7 ETM+ in the Visible and Near Infrared (VNIR) bands to within four percent and in the Short Wave Infrared (SWIR) bands to within six percent.

Multi-spectral thermal image analysis of natural backgrounds and targets

Abstract: This paper describes the visual, spatial and thermal characteristics, and analysis of dynamic landscape conditions critical to mine detection sensors. The characterization data will be used to develop a geospatial, all-season high fidelity data set to support the modeling of synthetic battlefield environments. Surface and subsurface targets of various materials and sizes were added to natural backgrounds to measure the spectral and thermal changes due to different environmental conditions. The imagery was collected with a four-camera system, each representing the visible near infrared (VNIR), 0.4-1.0 micron spectrum, the near infrared (NIR), 0.9 to 1.7 micron spectrum, the mid-wave infrared (MWIR), 3 to 5 micron spectrum, and the long-wave (LWIR), 8 to 14 micron spectrum. The four imaging systems are mounted on a rotating boom that is raised to approximately 12- meters above ground level to match the nadir aspect airborne imaging systems. Multiple areas within the rotational footprint are selected and measured every 10-minutes through a diurnal cycle. Concurrent meteorological measurements are recorded to identify wind speed and direction, air temperature, surface conditions and relative humidity profiles. The background and target analysis procedure is a process of several steps. First, the regions of interest (ROI's) are selected that identify the target or area to be characterized. Second, the area and statistical values will be calculated for each region of interest. Third, the ROI values are compared to the onsite meteorological station.

Hyperspectral imaging of an inter-coastal waterway

Abstract: This paper demonstrates the characterization of the water properties, bathymetry, and bottom type of the Indian River Lagoon (IRL) on the eastern coast of Florida using hyperspectral imagery. Images of this region were collected from an aircraft in July 2004 using the Portable Hyperspectral Imager for Low Light Spectroscopy (PHILLS). PHILLS is a Visible Near InfraRed (VNIR) spectrometer that was operated at an altitude of 3000 m providing 4 m resolution with 128 bands from 400 to 1000 nm. The IRL is a well studied water body that receives fresh water drainage from the Florida Everglades and also tidal driven flushing of ocean water through several outlets in the barrier islands. Ground truth measurements of the bathymetry of IRL were acquired from recent sonar and LIDAR bathymetry maps as well as water quality studies concurrent to the hyperspectral data collections. From these measurements, bottom types are known to include sea grass, various algae, and a gray mud with water depths less than 6 m over most of the lagoon. Suspended sediments are significant (~35 mg/m 3 ) with chlorophyll levels less than 10 mg/m 3 while the absorption due to Colored Dissolved Organic Matter (CDOM) is less than 1 m -1 at 440 nm. Hyperspectral data were atmospherically corrected using an NRL software package called Tafkaa and then subjected to a Look-Up Table (LUT) approach which matches hyperspectral data to calculated spectra with known values for bathymetry, suspended sediments, chlorophyll, CDOM, and bottom type.

The prediction of nitrogen concentration in soil by VNIR reflectance spectrum

Abstract: In this paper, the study on predicting nitrogen concentration in soil by VNIR (visible near infrared) spectrum is introduced. First, we analyzed the relationships between absorption features and nitrogen concentration to select the absorption features significantly correlated with nitrogen. Then several parameters of spectra in the selected absorption features were calculated, including first derivative reflectance spectra (FDR), inverse-log spectra (log (1/R)) and Band Depth. All of the soil samples were split into a calibration dataset and a validation dataset. Using stepwise multiple linear regression method, we established the statistical relationships between these parameters and nitrogen concentration. The regression models were calibrated using the calibration dataset, and validated using the validation dataset. The good results indicate that soil spectrum in the VNIR range has the potential for the rapid simultaneous prediction of nitrogen concentration. Keywords-nitrogen; soil; VNIR spectrum; SMLR

Development of the WAMS-VNIR instrument for SPF-II

Abstract: Wide-Angle Multi-Band Sensor-Visible and Near Infrared (WAMS-VNIR) has been developed as an Earth-observation mission instrument for SPF-II. SPF-II is a step toward the realization of Stratospheric Platform (SPF) using airships; it is capable of station-keeping flight at an altitude of 4km. WAMS-VNIR is a STARING multi-spectral imaging radiometer and polarimeter with five bands in wavelengths of 500 to 1000nm. WAMS-VNIR has optics of a 110° FOV, two rotating filter wheels, and a 1280 × 1024 pixel Si-CCD FPA. The wide field-of-view optics enable observing an 8km area even from an altitude of 4km. Five narrow-band spectral filters are installed on a rotating wheel, and two polarizers are installed on another rotating wheel. The polarizers rotate around the optical axis separately from the rotation of the wheel, providing several advantages in polarization measurement. The sensor system was completed and performance checks are being conducted. This paper introduces the sensor system and its performance.

Comparison between ETM + and ASTER Data for Extraction of Alteration Information: A Case Study of Fenghuangshan Orefield, Tongling, Anhui Province

Abstract: With the advent of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a 14 band multispectral sensor operating onboard the Earth Observation System (EOS) Terra satellite, the availability of spectral features in the shortwave infrared (SWIR) portion of the electromagnetic spectrum has been greatly increased This allows us to reveal the detailed spectral characterization of surface targets, particularly of minerals with diagnostic spectral features in this wavelength range, such as clay minerals In this study, Landsat ETM + and ASTER remote sensing data were used to map the alteration of rocks and minerals in Fenghuangshan Orefield based on the spectral feature analysis Principal component analysis (PCA) was done using four ETM + bands as input bands to extract clay alteration information, based on the relationship between the wavelengths of the ETM + bands and absorption features of the clay minerals PCA was also applied to the subsets of four and six ASTER bands to discriminate two kinds of clay minerals in the study area: kaolinite+sericite and chlorite, using the Crosta technique proposed by Loughlin The subsets were selected according to the bands with characteristic spectral features of key alteration mineral end members in the VNIR and SWIR of the spectrum The information of clay mineral distribution was extracted by each data set Comparison between ETM + and ASTER data for extraction of alteration information in this study shows that ASTER data has better capability for recognition of alteration minerals