GNSS satellite transmit power and its impact on orbit determination

Antenna thrust is a small acceleration acting on Global Navigation Satellite System satellites caused by the transmission of radio navigation signals. Knowledge about the transmit power and the mass of the satellites is required for the computation of this effect. The actual transmit power can be obtained from measurements with a high-gain antenna and knowledge about the properties of the transmit and receive antennas as well as losses along the propagation path. Transmit power measurements for different types of GPS, GLONASS, Galileo, and BeiDou-2 satellites were taken with a 30-m dish antenna of the German Aerospace Center (DLR) located at its ground station in Weilheim. For GPS, total L-band transmit power levels of 50–240 W were obtained, 20–135 W for GLONASS, 95–265 W for Galileo, and 130–185 W for BeiDou-2. The transmit power differs usually only slightly for individual spacecraft within one satellite block. An exception are the GLONASS-M satellites where six subgroups with different transmit power levels could be identified. Considering the antenna thrust in precise orbit determination of GNSS satellites decreases the orbital radius by 1–27 mm depending on the transmit power, the satellite mass, and the orbital period.     

Estimation of Above Ground Biomass for Central Indian Deciduous Forests Using ALOS PALSAR L-Band Data

Reliable and accurate estimates of tropical forest above ground biomass (AGB) are important to reduce uncertainties in carbon budgeting. In the present study we estimated AGB of central Indian deciduous forests of Madhya Pradesh (M.P.) state, India, using Advanced Land Observing Satellite – Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR) L-band data of year 2010 in conjunction with field based AGB estimates using empirical models. Digital numbers of gridded 1?×?1° dual polarization (HH & HV) PALSAR mosaics for the study area were converted to normalized radar cross section (sigma naught - σ⁰). A total of 415 sampling plots (0.1 ha) data collected over the study area during 2009–10 was used in the present study. Plot-level AGB estimates using volume equations representative to the study area were computed using field inventory data. The plot-level AGB estimates were empirically modeled with the PALSAR backscatter information in HH, HV and their ratios from different forest types of the study area. The HV backscatter information showed better relation with field based AGB estimates with a coefficient of determination (R²) of 0.509 which was used to estimate spatial AGB of the study area. Results suggested a total AGB of 367.4 Mt for forests of M.P. state. Further, validation of the model was carried out using observed vs. predicted AGB estimates, which suggested a root mean square error (RMSE) of ±19.32 t/ha. The model reported robust and defensible relation for observed vs. predicted AGB values of the study area.     

Evaluating the Long-term Urban Expansion of Ranchi Urban Agglomeration,India Using Geospatial Technology

The present study analyzes the built-up expansion of Ranchi urban agglomeration over a period of about 8 decades from 1927–2005. Satellite images and topographical maps were used to evaluate land use dynamics during these periods. Built-up growth of 473.7% during 1927–2005 was primarily at the expense of agricultural land along with reduction of natural water bodies reflects negative impacts of built-up expansion, which increased many folds in recent decades. The built-up growth is also analyzed with reference to population growth, land consumption rate and land transformation. The land loss due to increasing built-up growth of Ranchi were compared with other capital regions and cities along with population increase to provide insight into the possible scenario of built-up expansion in Ranchi urban area.     

Dimensionality Reduction and Classification of Hyperspectral Images Using Object-Based Image Analysis

Object-based image analysis (OBIA) has attained great importance for the delineation of landscape features, particularly with the accessibility to satellite images with high spatial resolution acquired by recent sensors. Statistical parametric classifiers have become ineffective mainly due to their assumption of normal distribution, vast increase in the dimensions of the data and availability of limited ground sample data. Despite pixel-based approaches, OBIA takes semantic information of extracted image objects into consideration, and thus provides more comprehensive image analysis. In this study, Indian Pines hyperspectral data set, which was recorded by the AVIRIS hyperspectral sensor, was used to analyse the effects of high dimensional data with limited ground reference data. To avoid the dimensionality curse, principal component analysis (PCA) and feature selection based on Jeffries–Matusita (JM) distance were utilized. First 19 principal components representing 98.5% of the image were selected using the PCA technique whilst 30 spectral bands of the image were determined using JM distance. Nearest neighbour (NN) and random forest (RF) classifiers were employed to test the performances of pixel- and object-based classification using conventional accuracy metrics. It was found that object-based approach outperformed the traditional pixel-based approach for all cases (up to 18% improvement). Also, the RF classifier produced significantly more accurate results (up to 10%) than the NN classifier.     

Evaluation of gravitational curvatures of a tesseroid in spherical integral kernels

Proper understanding of how the Earth’s mass distributions and redistributions influence the Earth’s gravity field-related functionals is crucial for numerous applications in geodesy, geophysics and related geosciences. Calculations of the gravitational curvatures (GC) have been proposed in geodesy in recent years. In view of future satellite missions, the sixth-order developments of the gradients are becoming requisite. In this paper, a set of 3D integral GC formulas of a tesseroid mass body have been provided by spherical integral kernels in the spatial domain. Based on the Taylor series expansion approach, the numerical expressions of the 3D GC formulas are provided up to sixth order. Moreover, numerical experiments demonstrate the correctness of the 3D Taylor series approach for the GC formulas with order as high as sixth order. Analogous to other gravitational effects (e.g., gravitational potential, gravity vector, gravity gradient tensor), numerically it is found that there exist the very-near-area problem and polar singularity problem in the GC east–east–radial, north–north–radial and radial–radial–radial components in spatial domain, and compared to the other gravitational effects, the relative approximation errors of the GC components are larger due to not only the influence of the geocentric distance but also the influence of the latitude. This study shows that the magnitude of each term for the nonzero GC functionals by a grid resolution 15\(^{{\prime } }\,\times \) 15\(^{{\prime }}\) at GOCE satellite height can reach of about 10\(^{-16}\) m\(^{-1}\) s\(^{2}\) for zero order, 10\(^{-24 }\) or 10\(^{-23}\) m\(^{-1}\) s\(^{2}\) for second order, 10\(^{-29}\) m\(^{-1}\) s\(^{2}\) for fourth order and 10\(^{-35}\) or 10\(^{-34}\) m\(^{-1}\) s\(^{2}\) for sixth order, respectively.     

The IFFT-based SQM method against digital distortion in GNSS signals

Global navigation satellite systems (GNSS) signal deformations could threaten the position accuracy and integrity of GNSS, especially for safety critical applications. Digital distortion is an important kind of deformations caused by failures inside the baseband generation unit onboard the GNSS satellites. Multi-correlator technique, as a prevalent signal quality monitoring (SQM) method, was developed to reliably detect the signal anomaly and therefore protect airborne users from this integrity threat. However, the conventional multi-correlator technique is unable to estimate the degree of distortion quantitatively, while another SQM method, the chip domain observable, has a poor real-time capability so that it could not meet the stringent time to alarm requirements. To solve the above problem, we derived the spectrum form of the conventional Threat Model A first and proposed a IFFT-based SQM algorithm. This new method can perform SQM easily by analyzing the impulses after PSD division and IFFT: Detect the presence of digital distortion by judging whether there is an impulse after IFFT and estimate the degree of distortion by computing the offset of the impulse. The results show that the IFFT-based method can not only detect digital distortion real-timely but also estimate the digital distortion degree quantitatively.     

衡水地区地裂缝空间发育特征与地下水位降深关系

通过浅层地震法及高密度电阻率法物探对河北衡水地区最近发现的3条地裂缝调查,探明了地裂缝地下发育深度、宽度、倾向等,发现地裂缝在地表与地下发育特征有明显不同：地表以一条地裂缝存在,在地下深处则以裂缝带发育,裂缝带两侧裂缝埋深不同,地下裂缝形态表现为上窄下宽。对该地区深层钻探、水文地质和多年地下水开采等资料分析表明,该地区的地裂缝是地质历史时期地质构造活动产物,开采深层地下水等资源则是促使地裂缝发展的主要原因。通过对不同地点地裂缝发育深度与近36年以来地下水水位降深的关系分析,结果显示：不同地区地裂缝发育深度与相应深层地下水水位降深呈线性关系。研究成果对地裂缝机理研究及预防开采深层地下水对地质环境的影响具有指导作用。     

Wave data assimilation using a hybrid approach in the Persian Gulf

The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.     

Diagnosing vertical motion in the Equatorial Atlantic

Estimating the vertical velocity (w) in the oceanic upper-layers is a key issue for understanding the cold tongue development in the Eastern Equatorial Atlantic. In this methodological paper, we develop an expanded and general formulation of the vertical velocity equation based on the primitive equation (PE) system, in order to gain new insight into the physical processes responsible for the Equatorial and Angola upwellings. This approach is more accurate for describing the real ocean than simpler considerations based on just the wind-driven patterns of surface layer divergence. The w-sources/forcings are derived from the PE w-equation and diagnosed from a realistic ocean simulation of the Equatorial Atlantic. Sources of w are numerous and express the high complexity of terms related to the turbulent momentum flux, to the circulation and to the mass fields, some of them depending explicitly on w and others not. The equatorial upwelling is found to be mainly induced by the (i) the zonal turbulent momentum flux, (ii) the curl of turbulent momentum flux and (iii) the imbalance between the circulation and the pressure fields. The Angola upwelling in the eastern part of the basin is controlled by strong curl of turbulent momentum flux. A strong cross-regulation is evidenced between the w-forcings independent of w and dependent on w, which suggests an equatorial balanced-dynamics. The w-forcing depending on w represents the negative feedback of the ocean to the w-forcing independent of w: in the equatorial band, this adjustment is led by non-linear processes and by vortex stretching outside.