Least-squares modification of extended Stokes’ formula and its second-order radial derivative for validation of satellite gravity gradiometry data

The gravity anomalies at sea level can be used to validate the satellite gravity gradiometry data. Validation of such a data is important prior to downward continuation because of amplification of the data errors through this process. In this paper the second-order radial derivative of the extended Stokes’ formula is employed and the emphasis is on least-squares modification of this formula to generate the second-order radial gradient at satellite level. Two methods in this respect are proposed: (a) modifying the second-order radial derivative of extended Stokes’ formula directly, and (b) modifying extended Stokes’ formula prior to taking the second-order radial derivative. Numerical studies show that the former method works well but the latter is very sensitive to the proper choice of the cap size of integration and degree of modification.     

Evaluation of public participation in reconstruction of Bam,Iran, after the 2003 earthquake

In the midst of the ever-increasing natural and human-induced disasters, where many of the preparedness and mitigation measures show inefficiencies, there is narrow margin for decision-makers to make mistakes by misallocating budgets, designing infeasible reconstruction plans, and in other terms, making decisions not in line with the public preferences. In particular, public participation in post-disaster measures seems undoubtedly necessary to reduce the possible economic, social, political, and cultural conflicts around the stressful community after a major disaster. This paper aims at evaluating the role of public participation in increasing the reconstruction phase efficiency through a case study of the reconstruction process in Bam, a southeastern Iranian city, after the 2003 earthquake. It is attempted to identify the major motivators of the public participation through a combination of quantitative and qualitative studies. Statistical data are generated through a set of questionnaires being filled by a number of 200 randomly selected survivors. The numerical results were then discussed through the Focus Group technique sessions to determine the main contributors to the public participation. It is later found that the answers are found among the performance of the reconstruction authorities, financial policies, emotional resiliency of the survivors, public information mechanisms, public satisfaction, the pace of reconstruction, and temporary housing policies.     

An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

Under condition of climate changes as global warming, monitoring and detecting trend of precipitation volume is essential and will be useful for agricultural sections. Considering the fact that there were not enough research related to precipitation volume, this study aimed to determine trends in precipitation volume, monthly and annually in different regions of Fars province for the last three decades (33?years period; 1978–2010). Fars province is located in arid and semi-arid regions of Iran, and it plays an important role in agricultural production. Inverse distance weighting interpolation method was used to provide precipitation data for all regions. To analyze the trends of precipitation volume, Mann–Kendall test, Sen’s slope estimator, and 10-year moving average low-pass filter (within time series) were used. The negative trends were identified by the Sen’s slope estimator as well as Mann–Kendall test. However, all the trends were insignificant at the surveyed confidence level (95%). With regards to the application of 10-year moving average low-pass filter, a considerable decreasing trend was observed after around year 1994. Since one of the most important restrictions in agricultural development of the Fars province is lack of sufficient water resources, any changes onward to lack of sufficient precipitation impose impressive pressure and stress on valuable resources and subsequently agricultural production.     

Constraints on Mercury’s Na exosphere: Combined MESSENGER and ground-based data

We have used observations of sodium emission obtained with the McMath-Pierce solar telescope and MESSENGER’s Mercury Atmospheric and Surface Composition Spectrometer (MASCS) to constrain models of Mercury’s sodium exosphere. The distribution of sodium in Mercury’s exosphere during the period January 12-15, 2008, was mapped using the McMath-Pierce solar telescope with the 5″ × 5″ image slicer to observe the D-line emission. On January 14, 2008, the Ultraviolet and Visible Spectrometer (UVVS) channel on MASCS sampled the sodium in Mercury’s anti-sunward tail region. We find that the bound exosphere has an equivalent temperature of 900-1200 K, and that this temperature can be achieved if the sodium is ejected either by photon-stimulated desorption (PSD) with a 1200 K Maxwellian velocity distribution, or by thermal accommodation of a hotter source. We were not able to discriminate between the two assumed velocity distributions of the ejected particles for the PSD, but the velocity distributions require different values of the thermal accommodation coefficient and result in different upper limits on impact vaporization. We were able to place a strong constraint on the impact vaporization rate that results in the release of neutral Na atoms with an upper limit of 2.1 × 10⁶ cm⁻² s⁻¹. The variability of the week-long ground-based observations can be explained by variations in the sources, including both PSD and ion-enhanced PSD, as well as possible temporal enhancements in meteoroid vaporization. Knowledge of both dayside and anti-sunward tail morphologies and radiances are necessary to correctly deduce the exospheric source rates, processes, velocity distribution, and surface interaction.     

Determination of gravity anomaly at sea level from inversion of satellite gravity gradiometric data

Gravity gradients can be used to determine the local gravity field of the Earth. This paper investigates downward continuation of all elements of the disturbing gravitational tensor at satellite level using the second-order partial derivatives of the extended Stokes formula in the local-north oriented frame to determine the gravity anomaly at sea level. It considers the inversion of each gradient separately as well as their joint inversion. Numerical studies show that the gradients T_zz, T_xx, T_yy and T_xz have similar capability of being continued downward to sea level in the presence of white noise, while the gradient T_yz is considerably worse than the others. The bias-corrected joint inversion process shows the possibility of recovering the gravity anomaly with 1 mGal accuracy. Variance component estimation is also tested to update the observation weights in the joint inversion.     

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.     

Declustering experimental variograms by global estimation with fourth order moments

The variogram is a key parameter for geostatistical estimation and simulation. Preferential sampling may bias the spatial structure and often leads to noisy and unreliable variograms. A novel technique is proposed to weight variogram pairs in order to compensate for preferential or clustered sampling . Weighting the variogram pairs by global kriging of the quadratic differences between the tail and head values gives each pair the appropriate weight, removes noise and minimizes artifacts in the experimental variogram. Moreover, variogram uncertainty could be computed by this technique. The required covariance between the pairs going into variogram calculation, is a fourth order covariance that must be calculated by second order moments. This introduces some circularity in the calculation whereby an initial variogram must be assumed before calculating how the pairs should be weighted for the experimental variogram. The methodology is assessed by synthetic and realistic examples. For synthetic example, a comparison between the traditional and declustered variograms shows that the declustered variograms are better estimates of the true underlying variograms. The realistic example also shows that the declustered sample variogram is closer to the true variogram.     

Measuring the effect of an ongoing urbanization process on biodiversity conservation suitability index: integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS)

The present study adopts an integrative modelling methodology, which combines the strengths of the SLEUTH model and the Conservation Assessment and Prioritization System (CAPS) method. By developing a scenario-based geographic information system simulation environment for Hashtpar City, Iran, the manageability of the landscape under each urban growth scenario is analysed. In addition, the CAPS approach was used for biodiversity conservation suitability mapping. The SLEUTH model was implemented to generate predictive urban layers of the years 2020, 2030, 2040 and 2050 for each scenario (dynamic factors for conservation suitability mapping). Accordingly, conservation suitability surface of the area is updated for each time point and under each urban development storyline. Two-way analysis of variance and Duncan’s new multiple range tests were employed to compare the functionality of the three scenarios. Based on results, the managed urban growth scenario depicted better results for manageability of the landscape and less negative impact on conservation suitability values.