Showing papers on "VNIR published in 2013"

Mineral Mapping Using Simulated Worldview-3 Short-Wave-Infrared Imagery

Abstract: WorldView commercial imaging satellites comprise a constellation developed by DigitalGlobe Inc. (Longmont, CO, USA). Worldview-3 (WV-3), currently planned for launch in 2014, will have 8 spectral bands in the Visible and Near-Infrared (VNIR), and an additional 8 bands in the Short-Wave-Infrared (SWIR); the approximately 1.0–2.5 μm spectral range. WV-3 will be the first commercial system with both high spatial resolution and multispectral SWIR capability. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data collected at 3 m spatial resolution with 86 SWIR bands having 10 nm spectral resolution were used to simulate the new WV-3 SWIR data. AVIRIS data were converted to reflectance, geographically registered, and resized to the proposed 3.7 and 7.5 m spatial resolutions. WV-3 SWIR band pass functions were used to spectrally resample the data to the proposed 8 SWIR bands. Characteristic reflectance signatures extracted from the data for known mineral locations (endmembers) were used to map spatial locations of specific minerals. The WV-3 results, when compared to spectral mapping using the full AVIRIS SWIR dataset, illustrate that the WV-3 spectral bands should permit identification and mapping of some key minerals, however, minerals with similar spectral features may be confused and will not be mapped with the same detail as using hyperspectral systems. The high spatial resolution should provide detailed mapping of complex alteration mineral patterns not achievable by current multispectral systems. The WV-3 simulation results are promising and indicate that this sensor will be a significant tool for geologic remote sensing.

Prediction of Soil Texture Distributions Using VNIR-SWIR Reflectance Spectroscopy

Abstract: Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regression (PLSR) method, which is a classical statistical multivariate technique, that uses the full-spectrum data. At this aim, the surface reflectance of 100 soil samples collected from different sites in Sicily and covering a wide range of textures were measured in laboratory using an ASD FieldSpec Pro spectroradiometer (350-2500 nm). The results of our work indicated that the PLSR technique performed better than the CR approach. Particularly, the assessment of soil texture accuracy performed using root mean squared error (RMSE) and coefficient of determination (R2) showed that the CR approach allowed to obtain a moderate prediction only for the clay texture fraction. Differently, using PLSR technique, the levels of accuracy resulted high for the clay fraction (RMSE=5.8%, R2=0.87) and satisfactory for the sand (RMSE=7.7%, R2=0.80) and silt fractions (RMSE=7.2%, R2=0.60). Moreover the use of PLSR technique allowed to establish the “key wavelengths” of the investigated spectrum range that should be considered “essential” for the prediction of soil textures, suggesting the optimal settings for airborne or satellite sensors usable in the future for accurate mapping of soil textures.

Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites

Abstract: This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called “crop mark”, the second component “vegetation” and the third component “soil”. For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed.

An Automated Method for Global Urban Area Mapping by Integrating ASTER Satellite Images and GIS Data

Abstract: We present an automated classification method for global urban area mapping by integrating satellite images taken by Visible and Near-Infrared Radiometer of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER/VNIR) and GIS data derived from existing urban area maps. The method consists of two steps. First, we extracted urban areas from ASTER/VNIR satellite images by using an iterative machine-learning classification method known as Learning with Local and Global Consistency (LLGC). This method is capable of automatically performing classification with a noisy training dataset, in our case, low-resolution urban maps. Therefore, we were able to perform supervised classification of ASTER/VNIR images without using labor-intensive visual interpretation. Second, we integrated the LLGC confidence map with other maps by logistic regression. The logistic regression complemented misclassifications in the LLGC map and provided useful information for further improvement of the model. In an experiment including 194 scenes of ASTER/VNIR images, the integrated maps were developed at a resolution of 15 m resolution, which is much finer than existing maps with resolutions of 300 to 1000 m. The maps achieved an overall accuracy of 90.0% and a kappa coefficient of 0.565, both of which are higher than or almost equal to the values for major existing global urban area maps.

ASTER spectral analysis of ultramafic lamprophyres carbonatites and aillikites within the Batain Nappe, northeastern margin of Oman: a proposal developed for spectral absorption

Abstract: We developed a scientific proposal on spectral absorption in remote sensing and a new image-processing method that is purely based on multispectral satellite image spectra to map ultramafic lamprophyre and carbonatite occurrences. The proposed method provides a simple, yet efficient, tool that will help exploration geologists. In this proposal, in which the spectral absorption is applicable to all satellite images obtained in visible, reflected infrared, and thermal infrared spectral wavelength regions, we found that the carbonatites appear white in colour on a greyscale or RGB thermal infrared image obtained in the thermal infrared wavelength region 3–15 μm due to molecular emission of thermal energy by such carbonate content, particularly the wavelength recorded by the sensor and that the variation of absorption in spectral bands of an outcrop is due to the differences in percentage of carbonate content or the spectral, spatial, radiometric, or temporal resolution of satellite data or the occurrences of carbonatites to incident energy. The results were confirmed by studying the spectral absorption characteristics of carbonatites in selected world occurrences including parts of Batain Nappe, Oman; Fuerteventura Canary Islands, Spain; Mount Homa, Kenya; Ol Doinyo Lengai, Tanzania; Mount Weld region, Laverton, Australia, and Phalaborwa region, South Africa, using Advanced Spaceborne Thermal Emission and Reflection Radiometer ASTER and Landsat Thematic Mapper TM satellite data. A subsequent study of visible near-infrared VNIR and shortwave infrared SWIR ASTER spectral bands of Early Cretaceous alkaline ultramafic rocks of Batain Nappe, along the northeastern margin of Oman to map for the occurrences of carbonatite and aillikite ultramafic lamprophyres dikes and plugs, showed their detection mainly by the diagnostic CO3 absorption 2.31–2.33 μm in ASTER SWIR band 8. The results of image interpretations were verified and confirmed in the field and were validated through the study of laboratory analyses. A few more carbonatite dike occurrences were interpreted directly over the greyscale image of ASTER bands and true-colour interpretations of a Google Earth image along this margin. The carbonatites and aillikite occurrences of the area are rich in apatite, iron oxide, phlogopite, and REE-rich minerals and warrant new exploration projects.

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

Abstract: 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 (R2 = 0.97, RMSE = 0.17 mg g−1), RWC (R2 = 0.88, RMSE = 1.41 mg g−1), Car (R2 = 0.66, RMSE = 0.08 mg g−1), phenolics (R2 = 0.64, RMSE = 23.01 mg g−1) and lignin (R2 = 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.

Development of an image-based method for the detection of archaeological buried relics using multi-temporal satellite imagery

Abstract: Remote sensing has been successfully used for the exposure of shallow buried relics such as archaeological remains The detection is mainly based on photointerpretation of high-resolution satellite or aerial images Photointerpretation for archaeological purposes is focused on the identification of crop marks using visible and near infrared VNIR spectrum eg vegetation indices response, which is sensitive to vegetation stress Detection of such marks is always performed through images of adequate spatial resolution, and therefore this procedure might be problematic in cases when there is a lack of accessibility to such kinds of data This paper addresses this problem and illustrates an image-based method intended for the detection of crop marks using satellite data of inadequate spatial resolution The overall methodology consists of seven separate steps The method needs two areas of interest to be selected in the image, preferably in close proximity to one another The first area is characterized as the ‘archaeological area under investigation'while the second is a vegetated non-archaeological area These two areas are simultaneously examined in detail using spectral signatures, soil lines, and their phenological cycle characteristics The proposed methodology has been successfully applied in three different areas in Cyprus and Greece, where the authors have already used the technique for validation purposes

Thermal Infrared Spectroscopy in the Laboratory and Field in Support of Land Surface Remote Sensing

Abstract: Thermal infrared (TIR) spectra of Earth surface materials are used in a wide variety of applications. These applications can fall into either of two groups: (a) where the TIR emissivity spectra themselves are the primary interest, and are used to determine the chemical/physical parameters of minerals and rocks, soil, vegetation and man-made materials, or (b) where the primary interest is in the temperature of the objects under study, and where emissivity spectra are required inorder to best determine kinetic from radiant temperature. Unlike visible-near infrared (VNIR) and shortwave infrared (SWIR) instruments, TIR spectroscopy instrumentation often requires customization in order to acquire reliable and reproducible data, making thermal spectroscopy a potentially complex process. Within this chapter we intend to provide a simple starting point for the new user of thermal infrared spectroscopy, and a synoptic overview of the technique for the more experienced practitioner. We discuss the theoretical background, give examples of instrument setups and provide typical measurement scenarios for a number of land applications.

Remote Sensing of Snow Cover

Abstract: Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

Simultaneous retrieval of CO2 and aerosols in a plume from hyperspectral imagery: application to the characterization of forest fire smoke using AVIRIS data

Abstract: Hyperspectral imagery is a widely used technique to study atmospheric composition. For several years, many methods have been developed to estimate the abundance of gases. However, existing methods do not simultaneously retrieve the properties of aerosols and often use standard aerosol models to describe the radiative impact of particles. This approach is not suited to the characterization of plumes, because plume particles may have a very different composition and size distribution from aerosols described by the standard models given by radiative transfer codes. This article presents a new method to simultaneously retrieve carbon dioxide CO2 and aerosols inside a plume, combining an aerosol retrieval algorithm using visible and near-infrared VNIR wavelengths and a CO2 estimation algorithm using shortwave infrared SWIR wavelengths. The microphysical properties of the plume particles, obtained after aerosol retrieval, are used to calculate their optical properties in the SWIR. Then, a database of atmospheric terms is generated with the radiative transfer code, Moderate Resolution Atmospheric Transmission MODTRAN. Finally, pixel radiances around the 2.0 μm absorption feature are used to retrieve the CO2 abundances. After conducting a signal sensitivity analysis, the method was applied to two airborne visible/infrared imaging spectrometer AVIRIS images acquired over areas of biomass burning. For the first image, in situ measurements were available. The results show that including the aerosol retrieval step before the CO2 estimation: 1 induces a better agreement between in situ measurements and retrieved CO2 abundances the CO2 overestimation of about 15%, induced by neglecting aerosols has been corrected, especially for pixels where the plume is not very thick; 2 reduces the standard deviation of estimated CO2 abundance by a factor of four; and 3 causes the spatial distribution of retrieved concentrations to be coherent.

Analysing the effects of applying agricultural lime to soils by VNIR spectral sensing: a quantitative and quick method

Abstract: The potential of visible and near-infrared VNIR diffuse reflectance spectra to predict the chemical properties of Ferralsols and Arenosols cultivated with maize during four crop cycles were evaluated. The study was carried out in a greenhouse and aimed to i evaluate soil chemistry variation induced by plants and the application of lime with different degrees of reactivity using conventional methods and proximal soil-sensing techniques, ii identify the wavelength ranges related to soil chemistry changes, and iii construct models that predict soil chemistry attributes using soil VNIR spectra. Treatments used were three lime rates applied to raise the base saturation to 40%, 60% and 80% and one control. Partial least squares regression with cross-validation was used to establish relationships between the VNIR spectra and the reference data from chemical analyses. The predicted results were evaluated based on the values of coefficient of determination R2, the ratio of the standard deviation of the validation set to the root mean square error of cross-validation RPD, and the root mean square of prediction. The predicted results were excellent R2 > 0.90 and RPD > 3 for potassium and for the lime requirement calculation. Good predictions 0.81 < R2 < 0.90 and 2.5 < RPD < 3 were also obtained for pH and sum of bases. The resulting models for exchangeable calcium, cation exchangeable capacity, and base saturation had moderate predictive power 0.66 < R2 < 0.80 and 2.0 < RPD < 2.5. Our findings suggest that VNIR reflectance spectroscopy could be used as a rapid, inexpensive, and non-destructive technique to predict some soil chemistry properties for these soil types. As this methodology evolves, it may eventually permit real-time analyses of soil variability and real-time management responses via sensors installed on tractors.

Four Decades of Progress in Monitoring and Modeling of Processes in the Soil-Plant- Atmosphere System: Applications and Challenges Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy

Abstract: Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regression (PLSR) method, which is a classical statistical multivariate technique, that uses the full-spectrum data. At this aim, the surface reflectance of 100 soil samples collected from different sites in Sicily and covering a wide range of textures were measured in laboratory using an ASD FieldSpec Pro spectroradiometer (350-2500 nm). The results of our work indicated that the PLSR technique performed better than the CR approach. Particularly, the assessment of soil texture accuracy performed using root mean squared error (RMSE) and coefficient of determination (R 2 ) showed that the CR approach allowed to obtain a moderate prediction only for the clay texture fraction. Differently, using PLSR technique, the levels of accuracy resulted high for the clay fraction (RMSE=5.8%, R 2 =0.87) and satisfactory for the sand (RMSE=7.7%, R 2 =0.80) and silt fractions (RMSE=7.2%, R 2 =0.60). Moreover the use of PLSR technique allowed to establish the “key wavelengths” of the investigated spectrum range that should be considered “essential” for the prediction of soil textures, suggesting the optimal settings for airborne or satellite sensors usable in the future for accurate mapping of soil textures.

ASTER VNIR & SWIR Band Enhancement for Lithological Mapping - A case study of the Azegour Area (Western High Atlas, Morocco)

Abstract: The purpose of this study is to emphasize on the ASTER images effectiveness and capabilities in the field of lithological mapping. An ASTER image (L1b) covering the study area has been used. Visible, near-infrared and short wave infrared reflectance data (9 ASTER bands) have been processed and interpreted. Preprocessing included geometric correction; crossTalk correction; orthorectification. Then the VNIR and SWIR bands have been normalized using the Flat Field Calibration method. Digital processing focused on image enhancement by applying principal component analysis (PCA) and a minimum noise fraction (MNF) transformation. This was achieved by using ENVI 4.7®. Results showed that there are dissimilarities with the published geological map. Offset between lithological boundaries and the obtained results, textures and/or contrast detected inside homogeneously mapped layers have been observed. The existing geological map contains relevant lithological information, however these results provide a new layer of information that can be used to upgrade it. Thus the image enhancement of ASTER remote sensing data can be used as a powerful tool for lithological mapping. Keywords: ASTER, Lithological Mapping, Band enhancement, Western High Atlas,

Dual-band infrared remote sensing system with combined long-wave infrared imaging and mid-wave infrared spectral analysis

Abstract: We present a new optical system for infrared (IR) image-spectrum integration remote sensing. The purpose to develop this instrument is to find the key spectral characteristics of typical hot target and to explore a new intelligence fusion method for the recognition. When mounted on a two-dimensional rotation stage, it can track the suspected target by image processing, and then get its spectrum to do recognition. It is a dual-band system with long-wave infrared (LWIR) imaging and mid-wave infrared (MWIR) spectrum. An IR dichroic beamsplitter is used to divide wideband incident infrared into LWIR and MWIR. Compared to traditional infrared combined imaging and spectral-analysis instruments, it yields higher sensitivity for measuring the IR spectrum. The sensors for imaging and spectrum detection are separate, so high spatial resolution, frame rate, and spectrum resolution can all be obtained simultaneously.

Visible-Near Infrared (VNIR) and Shortwave Infrared (SWIR) Spectral Variability of Urban Materials

Abstract: : The advent of relatively high spatial resolution hyperspectral imagery (HSI) provides a different perspective of the urban environment than lower spatial resolution hyperspectral data and either multispectral or panchromatic images. The objective of this thesis was to build and analyze a spectral library of urban materials and to understand how spectral variability affects the ability of classification algorithms to identify and discriminate various materials. The scope of the project was limited to non-vegetative impervious materials located on the Naval Postgraduate School campus. An airborne hyperspectral image, acquired September 30th 2011 was used for image-derived endmembers and a portable spectroradiometer was used to collect field spectra. Visual analysis of spectra was performed to assess intra- and inter-class variability and to identify spectral features and their causes. The spectral angle mapper (SAM) algorithm was used on the HSI data as a method to quantify intra-class spectral variability using a standard spectral angle. Classification maps were created with both SAM and mixture tuned matched filtering (MTMF) algorithms to determine how intra- and inter-class spectral variability affect the algorithm s ability to classify urban materials. The spatially complex nature of the urban environment negatively affected the performance of the SAM algorithm, but the ability to increase the spectral angle to account for materials with high spectral variability allowed improved interclass discrimination. The MTMF algorithm was better suited for intra-class discrimination of materials.

Concept and integration of an on-line quasi-operational airborne hyperspectral remote sensing system

Abstract: Modern mission characteristics require the use of advanced imaging sensors in reconnaissance. In particular, high spatial and high spectral resolution imaging provides promising data for many tasks such as classification and detecting objects of military relevance, such as camouflaged units or improvised explosive devices (IEDs). Especially in asymmetric warfare with highly mobile forces, intelligence, surveillance and reconnaissance (ISR) needs to be available close to real-time. This demands the use of unmanned aerial vehicles (UAVs) in combination with downlink capability. The system described in this contribution is integrated in a wing pod for ease of installation and calibration. It is designed for the real-time acquisition and analysis of hyperspectral data. The main component is a Specim AISA Eagle II hyperspectral sensor, covering the visible and near-infrared (VNIR) spectral range with a spectral resolution up to 1.2 nm and 1024 pixel across track, leading to a ground sampling distance below 1 m at typical altitudes. The push broom characteristic of the hyperspectral sensor demands an inertial navigation system (INS) for rectification and georeferencing of the image data. Additional sensors are a high resolution RGB (HR-RGB) frame camera and a thermal imaging camera. For on-line application, the data is preselected, compressed and transmitted to the ground control station (GCS) by an existing system in a second wing pod. The final result after data processing in the GCS is a hyperspectral orthorectified GeoTIFF, which is filed in the ERDAS APOLLO geographical information system. APOLLO allows remote access to the data and offers web-based analysis tools. The system is quasi-operational and was successfully tested in May 2013 in Bremerhaven, Germany.

Validation of the Radiometric Characteristics of Landsat 8 (LDCM) OLI Sensor using Band Aggregation Technique of EO-1 Hyperion Hyperspectral Imagery

Abstract: The quality of satellite imagery should be improved and stabilized to satisfy numerous users. The radiometric characteristics of an optical sensor can be a measure of data quality. In this study, a band aggregation technique and spectral response function of hyperspectral images are used to simulate multispectral images. EO-1 Hyperion and Landsat-8 OLI images acquired with about 30 minutes difference in overpass time were exploited to evaluate radiometric coefficients of OLI. Radiance values of the OLI and the simulated OLI were compared over three subsets covered by different land types. As a result, the index of agreement shows over 0.99 for all VNIR bands although there are errors caused by space/time and sensors.

Sentinel-2 diffuser on-ground calibration

Abstract: The Sentinel-2 multi-spectral instrument (MSI) will provide Earth imagery in the frame of the Global Monitoring for Environment and Security (GMES) initiative which is a joint undertaking of the European Commission and the Agency. MSI instrument, under Astrium SAS responsibility, is a push-broom spectro imager in 13 spectral channels in VNIR and SWIR. The instrument radiometric calibration is based on in-flight calibration with sunlight through a quasi Lambertian diffuser. The diffuser covers the full pupil and the full field of view of the instrument. The on-ground calibration of the diffuser BRDF is mandatory to fulfil the in-flight performances. The diffuser is a 779 x 278 mm2 rectangular flat area in Zenith-A material. It is mounted on a motorised door in front of the instrument optical system entrance. The diffuser manufacturing and calibration is under the Centre Spatial of Liege (CSL) responsibility. The CSL has designed and built a completely remote controlled BRDF test bench able to handle large diffusers in their mount. As the diffuser is calibrated directly in its mount with respect to a reference cube, the error budget is significantly improved. The BRDF calibration is performed directly in MSI instrument spectral bands by using dedicated band-pass filters (VNIR and SWIR up to 2200 nm). Absolute accuracy is better than 0.5% in VNIR spectral bands and 1% in SWIR spectral bands. Performances were cross checked with other laboratories. The first MSI diffuser for flight model was calibrated mid 2013 on CSL BRDF measurement bench. The calibration of the diffuser consists mainly in thermal vacuum cycles, BRDF uniformity characterisation and BRDF angular characterisation. The total amount of measurement for the first flight model diffuser corresponds to more than 17500 BRDF acquisitions. Performance results are discussed in comparison with requirements.

Lithology Identification of the North Qilian Belt by Surface Temperature and Spectral Emissivity Information Derived from ASTER TIR Data

Abstract: Lithology units have been identified in northern Qilian belt by using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared (TIR)L1B data which contains both surface temperature and spectral emissivity information. As mafic-to-untramafic units have higher surface temperature than other geologic units, surface temperature images were generated to identify the dolerite and peridotite etc. Reference to analysis of thermal spectra characteristics of geological units from JHU spectral library, a new ASTER colored composite band ratio combination band 11/12: band 12/10: band 12/14 as R:G:B was applied successfully to distinguish quartz-rich felsic units and feldspathic rocks from the large meadow in the study area , with the band ratio and de-correlation techniques. To clarify the geological boundaries and remove the vegetation effect more effective, NDVI image and false color composite image composed of band 3: band 2 : band 1 visible to near infrared bands were also generated. The result indicated that combination of TIR FCC image, VNIR FCC image, temperature image and NDVI image for the study lithology mapping works well and matches the field geological

Mapping of manganese potential areas using ASTER satellite data in parts of Sultanate of Oman

Abstract: Economically viable stratiform manganese occurrences are found within the radiolarian cherts belongs to the Late Jurassic-Cretaceous age of Wahrah Formation near Ras Al Hadd region, northern east margin of Oman. In this study, their occurrence and distribution are discriminated in visible near infrared (VNIR) and short wave infrared (SWIR) multispectral bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) using band ratio and Principal Component Analysis (PCA) image processing methods. The processed ASTER band ratio ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) image discriminated clearly the occurrence and spatial distribution of Wahrah formation in cyan colour. The RGB image of principal components PC3, PC2 and PC1 identified well the occurrences of manganese bodies in dark blue colour within the Wahrah formation of the study area. The results of image interpretations are verified in the field. The samples collected from field were studied in the laboratory using thin and polished sections under microscope and X-Ray Diffraction (XRD) analyses. This work demonstrates the sensor capability of ASTER in the mapping of manganese potential areas and the preliminary remote sensing study proposes for a large scale detailed exploration work on manganese in this region. The familiar image processing methods used in this study have great potential in the mapping of manganese bodies and associated lithology and as such are recommended for discriminating similar manganese mineralization in other arid geographic regions of the world.

Onboard electrical calibration of the ASTER VNIR

Abstract: The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) is one of the five sensors on the NASA’s Terra satellite on orbit since December 1999. ASTER consists of three radiometers, the Visible and Near InfraRed (VNIR), the Short-Wave InfraRed (SWIR) and Thermal InfraRed (TIR) whose spatial resolutions are 15 m, 30 m and 90 m, respectively. Unfortunately the SWIR image data are saturated since April 2008 due to the offset rise caused by the cooler temperature rise, but the VNIR and the TIR are taking Earth images of good quality. The VNIR and the TIR experienced responsivity degradation while the SWIR showed little change. From the lamp calibration, Band 1 decreased the most among three VNIR bands and 31% in thirteen years. The VNIR has the electrical calibration mode to check the healthiness of the electrical circuits through the charge coupled device (CCD). Four voltage levels from Line 1 to Line 4, which are from 2.78 V to 3.10 V, are input to the CCD in the onboard calibration sequence and the output digital numbers (DNs) are detected in the images. These input voltages are monitored as telemetry data and have been stable up to now. From the electrical calibration we can check stabilities of the offset, gain ratio and gain stability of the electric circuit. The output level of the Line1 input is close to the offset level which is measured while observing the earth at night. The trend of the Line 1 output is compared to the offset level. They are similar but are not exactly the same. The trend of the even pixel and odd pixel is the same so the saturated offset levels of the odd pixel is corrected by using the even pixel trend. The gain ratio trend shows that the ratio is stable. But the ratio values are different from those measured before launch. The difference comes up to 10% for the Band 2. The correct gain ratio should be applied to the vicarious calibration result because the onboard calibration is measured with the Normal gain whereas the vicarious calibration often measures with the High gain. The cause of the VNIR responsivity degradation is not known but one of the causes might be the change of the electric circuit. The band 3 gain shows 16 % decrease whereas the gain changes of the band 1 and band 2 are 5% to 8%. The responsivity decrease after 1000 days since launch might be controlled by the electric circuit change.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

Abstract: Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the “Urban” class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the “Dirt Path” class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Spectral Library for Various Rocks and Minerals of Salem District: A Comparative Study and Validation with ASTER Data

Abstract: Documentation of hyperspectral data of selected rocks and minerals and validation of the measured spectral values with ASTER data are presented in this chapter. Spectral data were generated by using the instrument SVC HR 1024 Spectroradiometer with a wavelength range of 350–2,500 nm. The spectra were compared with USGS and JHU spectral library. Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data acquired in the Visible Near Infra Red (VNIR) and Short Wave Infra Red (SWIR) regions were used to evaluate the spectral discrimination of rocks and minerals. The SAM technique was used to detect the presence of minerals (e.g. Magnesite and Bauxite) in the study area and then the spectral library was validated with the SAM results.