Potential of IRNSS/NavIC L5 signals for ionospheric studies

Indian Space Research Organization (ISRO) has developed an indigenous system named Indian Regional Navigation Satellite System (IRNSS) or NavIC (Navigation with Indian Constellation), that consists of 7 satellites and transmits navigation signal in L and S bands. ISRO, for validation of the system, has installed many IGS (IRNSS/GPS/SBAS) receivers scattered over the Indian region. Using preliminary data from two geographically widely separated stations over India, this paper presents the results on studies on parameters of IRNSS signal quality and discusses how these parameters may be used to study the ionospheric behavior over the Indian region. The results show the importance and advantages of using IRNSS data for such studies.     

ASTER spectral sensitivity of carbonate rocks – Study in Sultanate of Oman

Remote sensing satellite data plays a vital role and capable in detecting minerals and discriminating rock types for explorations of mineral resources and geological studies. Study of spectral absorption characters of remotely sensed data are under consideration by the exploration and mining companies, and demonstrating the spectral absorption characters of carbonates on the cost-effective multispectral image (rather than the hyperspectral, Lidar image) for easy understanding of all geologists and exploration communities of carbonates is very much important. The present work is an integrated study and an outcome of recently published works on the economic important carbonate rocks, includes limestone, marl, listwaenites and carbonatites occurred in parts of the Sultanate of Oman. It demonstrates the spectral sensitivity of such rocks for simple interpretation over satellite data and describes and distinguishes them based on the absorptions of carbonate minerals in the spectral bands of advanced spaceborne thermal emission and reflection radiometer (ASTER) for mapping and exploration studies. The study results that the ASTER spectral band 8 discriminates the carbonate rocks due to the presence of predominantly occurred carbonate minerals; the ASTER band 5 distinguishes the limestones and marls (more hydroxyl clay minerals) from listwaenite (hydrothermally altered rock) due to the presence of altered minerals and the ASTER band 4 detects carbonatites (ultramafic intrusive alkaline rocks) which contain relatively more silicates. The study on the intensity of the total absorptions against the reflections of these rocks shows that the limestones and marls have low intensity in absorptions (and high reflection values) due to the presence of carbonate minerals (calcite and dolomite) occurred in different proportions. The listwaenites and carbonatites have high intensity of absorptions (low reflection values) due to the occurrence of Mn-oxide in listwaenites and carbonates in carbonatites apart the influence of major carbonate minerals that occurred predominantly in these rocks. The study of ASTER thermal infrared (TIR) spectral bands distinguished the marls have low emissivity of energy due to the presence of hydroxyl bearing alumina-silicate minerals from the other rocks such as limestones, listwaenites and carbonatites which have high emissivity due to the absence of hydroxyl bearing alumina-silicate minerals and the presence of carbonate minerals and carbonates.     

机载可见近红外成象光谱仪的设计

本文阐述了一种可行的面阵CCD 成象光谱仪的设计。它具有光谱范围宽(0.4μm～1.1μm)、高光谱分辨率(9.2nm)、密集的光谱波段数(76)、较大的地物扫描视场角(30°)等一系列引人注目的优点。     

Evaluation of thematic mapper data for mapping forest,agricultural and soil resources

Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.     

Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex,south Iran

Spectral transformation methods, including correlation coefficient (CC) and Optimum Index Factor (OIF), band ratio (BR) and principal component analysis (PCA) were applied to ASTER and Landsat TM bands for lithological mapping of Soghan ophiolitic complex in south of Iran. The results indicated that the methods used evidently showed superior outputs for detecting lithological units in ophiolitic complexes. CC and OIF methods were used to establish enhanced Red–Green–Blue (RGB) color combination bands for discriminating lithological units. A specialized band ratio (4/1, 4/5, 4/7 in RGB) was developed using ASTER bands to differentiate lithological units in ophiolitic complexes. The band ratio effectively detected serpentinite dunite as host rock of chromite ore deposits from surrounding lithological units in the study area. Principal component images derived from first three bands of ASTER and Landsat TM produced well results for lithological mapping applications. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinite dunite in ophiolitic complexes. The developed approach used in this study offers great potential for lithological mapping using ASTER and Landsat TM bands, which contributes in economic geology for prospecting chromite ore deposits associated with ophiolitic complexes.     

Detailed choice of the spectral bands

The SPOT satellite is designed so as to provide multispectral observations with 20 m resolution and panchromatic observation with 10 m resolution. The three spectral bands allow a study of the spectral signature of objects; so, the detailed profile of these bands has been optimized so as to select the parts of major interest in the reflectance of various objects and minimize the atmospheric perturbation in the quantitative measurement. The panchromatic band is mainly involved in cartographic application; so the design of the spectral sensitivity is related to the study of the contrast between objects thematically characterized, taking into account the actual resolution.     

Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.     

Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression

This study aimed to investigate the performance of genetic algorithms coupled with partial least squares (GA-PLS) modeling of spectral reflectance in retrieving equivalent water thickness (EWT) at leaf and canopy level. A genetic algorithm was used to identify a subset of spectral bands sensitive to the variation in EWT, and PLS was then applied to relate the identified bands to EWT values. GA-PLS was applied to leaf level reflectance available from LOPEX dataset, and canopy data includes reflectance simulated by a leaf radiative transfer model PROSPECT and a canopy radiative transfer model SAILH and acquired by airborne visible/infrared imaging spectrometer (AVIRIS). The results indicate that GA-PLS has the capability of retrieving EWT from leaf and canopy reflectance, and achieved good estimation accuracy, i.e. low root mean square errors (RMSE) and high squared correlation coefficients (R²). For the retrieval at leaf level, the estimation accuracy can be as good as RMSE = 0.0019 g/cm² and R² = 0.939 or better. For the retrieval at canopy level, the model accuracy is RMSE = 0.0061 g/cm² and R² = 0.966 or better when PROSPECT-SAILH simulated reflectance was used; when AVIRIS image spectra were used, the model accuracy is RMSE = 0.0094 g/cm² and R² = 0.8734 for the calibration, and RMSE = 0.0132 g/cm² and R² = 0.7756 for the validation. These results from GA-PLS modeling support the conclusion that GA-PLS has the potential to be applied to AVIRIS, Hyperion and HyMap imagery for retrieving EWT. The selected bands for the AVIRIS datasets differ from those for the LOPEX and PROSPECT-SAILH simulated datasets, and this inconsistence of the selected bands for different datasets indicates that the GA-PLS method has the advantage of tuning the optimum bands for PLS regression and accommodating the effects of confounding factors.     

A reflectance spectra-based approach to mapping salt fields using PCA-fused Landsat TM data

In this paper a method based on in situ measured reflectance spectra was developed for accurately mapping salt fields in the Taibei Salt Farm in Lianyungang City of East China. After radiometric correction and geometric rectification, six multispectral ETM+ bands were fused with the panchromatic band via principal components analysis (PCA). The fused data were used to map salt fields in the farm. Salt fields were mapped 91.95% correctly in comparison with ground statistics from raw multispectral bands. This accuracy level rose to 96.4% with the use of the panchromatic band (15 m resolution). However, PCA-fused data produced the highest accuracy of 98.8%. At the zone level, coarse resolution data resulted in an accuracy of 98.93% for crystallization ponds, but only 82.68% for condensation ponds. Use of the panchromatic band alone improved the accuracy for condensation ponds but decreased the accuracy for crystallization and evaporation ponds. Results derived from PCA-fused data are highly consistent with the ground statistics at a discrepancy between 0.35% for evaporation zone and 1.80% for condensation zone. It is concluded that a fine spectral resolution is important to separation of ponds of a varying salt content while a fine spatial resolution is important to their mapped area. Ponds of a lower salt content can be mapped more accurately from fused data than from raw spectral bands.     

Detection of hydrothermal alteration zones using ASTER data in Nimu porphyry copper deposit,south Tibet,China

Advanced space-borne thermal emission and reflection radiometer (ASTER) data were evaluated for the hydrothermal alteration mapping of the Nimu porphyry copper deposit, southern Tibet. According to the metallogenic model for porphyry copper, we chose hydrothermal alteration mineral association and then established a remote sensing model. Relative absorption-band depth (RBD) and simple band combination methods in visible near infrared (VNIR) and shortwave infrared (SWIR) bands were used to retrieve information about lithological distributions. Principal component analyses (PCA) were applied to extract the prospecting information based on the spectral information of argillization mineral association, propylitization mineral association, and iron stained (limonite) effects. Results of the study match up well with known copper occurrences and a circular structure in study area, while circular structures usually have close relationship with mineralization. Combined with field validation, ASTER data are proved able to characterise the alteration zone of these porphyry deposits. With VNIR and SWIR bands, argillic, propylitic and ferritization alterations in a single deposit can be effectively discriminated.     

Changes in hyperspectral reflectance signatures of lettuce leaves in response to macronutrient deficiencies

The adaptation of specific remote sensing and hyperspectral analysis techniques for the determination of incipient nutrient stress in plants could allow early detection and precision supplementation for remediation, important considerations for minimizing mass of advanced life support systems on space station and long term missions. This experiment was conducted to determine if hyperspectral reflectance could be used to detect nutrient stress in Lactuca sativa L. cv. Black Seeded Simpson. Lettuce seedlings were grown for 90 days in a greenhouse or growth chamber in vermiculite containing modified Hoagland’s nutrient solution with key macronutrient elements removed in order to induce a range of nutrient stresses, including nitrogen, phosphorus, potassium, calcium, and magnesium. Leaf tissue nutrient concentrations were compared with corresponding spectral reflectances taken at the end of 90 days. Spectral reflectances varied with growing location, position on the leaf, and nutrient deficiency treatment. Spectral responses of lettuce leaves under macronutrient deficiency conditions showed an increase in reflectance in the red, near red, and infrared wavelength ranges. The data obtained suggest that spectral reflectance shows the potential as a diagnostic tool in predicting nutrient deficiencies in general. Overlapping of spectral signatures makes the use of wavelengths of narrow bandwidths or individual bands for the discrimination of specific nutrient stresses difficult without further data processing.     

Optimum spectral bands for land cover discrimination

An experiment was undertaken to select the optimum spectral bands for the discrimination of land use/cover for proposed Indian Remote Sensing Satellite. A feature selection method was used for the discrimination analysis on the multiband data collected by Bendix 11-channel Modular Multiband Scanner over Tirupati test site of Chittoor district, Andhra Pradesh, South India. Of the various combinations of bands analysed, the optimum combination of four bands was defined as that one which provided the greatest divergence distances to discriminate the specific land covers in the test sites. On the basis of the above studies the optimum bands so chosen are 0.49–0.54 μm, 0.62–0.66 μm, 0.66–0.70 μm and 0.77–0.86 μm.     

GRB observed by IBIS/PICsIT in the MeV energy range

We present the preliminary results of a systematic search for GRB and other transients in the publicly available data for the IBIS/PICsIT (0.2–10 MeV) detector on board INTEGRAL. Lightcurves in 2–8 energy bands with time resolution from 1 to 62.5 ms have been collected and an analysis of spectral and temporal characteristics has been performed. This is the nucleus of a forthcoming first catalog of GRB observed by PICsIT.     

A new spectral index to detect Poaceae grass abundance in Mongolian grasslands

The objectives of the present study were to develop a new index based on remotely-sensed data for detecting the abundance of grasses in the family Poaceae, which has a high palatability for livestock in Mongolia, and to map the distribution of these grasses in the semi-arid Mongolian steppes. We measured ground-based spectral reflectance of pure plant leaves – including Poaceae grasses – and soils, as well as in-situ in the Mongolian grasslands. The hyper-spectral data, taken by a spectroradiometer, were converted into four multi-spectral bands (i.e., blue, green, red, and NIR) to simulate satellite-based imagery data. In order to magnify the characteristics of the spectral signal of Poaceae, NGBDI (Normalized Green-Blue Difference Index), NGRDI (Normalized Green-Red Difference Index), NDVI (Normalized Difference Vegetation Index), NNBDI (Normalized NIR-Blue Difference Index) were calculated from the four multi-spectral reflectance values. Poaceae Abundance Index (PAI) was derived by combining these four normalized difference indices. PAI was found out to be a good indicator to discriminate Poaceae grass from the other plant spectral data.     

Bacterial cellulose may provide the microbial-life biosignature in the rock records

Bacterial cellulose (BC) is a matrix for a biofilm formation, which is critical for survival and persistence of microbes in harsh environments. BC could play a significant role in the formation of microbial mats in pristine ecosystems on Earth. The prime objective of this study was to measure to what extent spectral and other characteristics of BC were changed under the performance of BC interaction with the earthly rock – anorthosite – via microorganisms. The spectral analyses (Fourier Transform Infrared FT-IR, spectroscopy, and atomic absorption spectroscopy) showed unprecedented accumulation of chemical elements in the BC-based biofilm. The absorption capacity of IR by BC was shielded a little by mineral crust formed by microorganisms on the BC-based biofilm surface, especially clearly seen in the range of 1200–900 cm⁻¹ in FT-IR spectra. Confocal scanning laser microscopy analysis revealed that elements bioleached from anorthosite created surface coats on the BC nanofibril web. At the same time, the vibrational spectra bands showed the presence of the characteristic region of anomeric carbons (960–730 cm⁻¹), wherein a band at 897 cm⁻¹ confirmed the presence of β-1, 4-linkages, which may serve as the cellulose fingerprint region. Results show that BC may be a biosignature for search signs of living organisms in rock records.     

Extraction of hydrothermal alterations from ASTER SWIR data from east Zanjan,northern Iran

The use of satellite images for mineral exploration has been very successful in pointing out the presence of minerals such as smectite and kaolinite which are important in the identification of hydrothermal alterations. Shortwave infrared (SWIR) bands from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the wavelength of ASTER SWIR bands between 1.65 and 2.43 μm has a good potential for mapping a hydrothermal alteration minerals such as alunite, pyrophyllite, kaolinite, illite–muscovite–sericite, and carbonate. In this range, hydroxide minerals which have been produced by hydrothermal alteration exhibit good absorption compared to shorter or longer wavelengths. In this research which aims to remove atmospheric and topographic effects from ASTER SWIR data, the authors used the log-residual method (LRM) with the minimum noise fraction (MNF) transformation to create a pixel purity index (PPI) which was used to extract the most spectrally pure pixels from multispectral images. Spectral analyses of the clay mineralogy of the study area (east Zanjan, in northern Iran) were obtained by matching the unknown spectra of the purest pixels to the U.S. Geological Survey (USGS) mineral library. Three methods, spectral feature fitting (SFF), spectral angle mapping (SAM), and binary encoding (BE) were used to generate a score between 0 and 1, where a value of 1 indicates a perfect match showing the exact mineral type. In this way, it was possible to identify certain mineral classes, including chlorite, carbonate, calcite–dolomite–magnesite, kaolinite–smectite, alunite, and illite. In this research, two main propylitic and phyllic–argillic zones could be separated using their compositions of these minerals. These two alteration zones are important for porphyry copper deposits and gold mineralization in this part of Iran.     

基于光谱特征的自适应子空间波段选择方法

针对现有波段选择方法无法依据感兴趣地物划分数据子空间及子空间划分容易受背景地物影响等问题,提出一种基于光谱特征的自适应子空间波段选择方法.利用感兴趣地物的光谱曲线,建立光谱自适应因子(SAF,Spectral Adaptive Factor);通过聚类划分子空间,在每个子空间内,利用J-M距离筛选类别可分性最大波段作为子空间最优波段,从而得到整个数据空间的最佳波段组合.利用AOTF (Acousto-Optic Tunable Filter)成像光谱仪数据与波段指数(BI,Band Index)和基于类间可分性最佳波段选择两种方法比较,SAF方法选择的最佳波段组合,包含信息量丰富,地物之间差异较大,且地物平均J-M距离大于另外两种方法.用最大似然法(maximum likelihood)对最佳波段组合进行分类,总体分类精度为96.8%,Kappa系数为0.894.结果验证了SAF方法的有效性和实用性.     

Evaluation of SPOT HRV simulation data for Corps of Engineers applications

During the summer of 1983 three Corps of Engineers project sites were overflown as part of the SPOT (Système Probatoire d'Observation de la Terre) High Resolution Visible (HRV) simulation campaign. The three sites were Chesapeake Bay, Maryland, Berlin Lake, Ohio, and Lac qui Parle, Minnesota. Multispectral imagery data at a 20-m resolution for three spectral bands (0.50–0.59 μm, 0.61–0.68 μm, 0.79–0.89 μm) were obtained for each of the sites. The data were analyzed for use in dredging, recreation resource management, water quality, and wildlife habitat applications.