Accessibility for High Asia： Comparative Perspectives on Northern Pakistan＇s Traffic Infrastructure and Linkages with Its Neighbours in the Hindukush-Karakoram- Himalaya

Starting with a discussion of development concepts which were applied in practice and which followed the developmentalist paradigm the expansion of traffic infrastructure in colonial and post-colonial periods is presented for the High Asian mountain rim. Selective railways and roads are the major feature of this development, which aimed first on serving the convenience of hill station visitors and followed strategic considerations later on. This bias between regional planning and implementation remains a characteristic feature. At the same time traffic infrastructure without asphalt roads is important for the mountain areas, thus breaking up the strong correlation between development and asphalt roads.     

A light subsystem inside a gravitating triaxial ellipsoid

We obtain the possible ellipsoidal and hyperboloidal equilibrium figures of the light subsystem with internal fluxes of matter of constant vorticity inside a gravitating homogeneous triaxial ellipsoid. We obtain the domains of stability of these equilibrium figures with respect to second-form oscillations.Translated fromAstrofizika, Vol. 38, No. 2, 1995.     

Reliable estimation of orbit errors in spaceborne SAR interferometry

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.     

Estimation of parameters in a split functional model of geodetic observations (<Emphasis Type="Italic">M</Emphasis><Subscript>split</Subscript> estimation)

The paper presents a method of estimating parameters in two competitive functional models. The models considered here are concerned with the same observation set and are based on the assumption that an observation may result from a realization of either of two different random variables. These variables differ from one another at least in the main characteristic (for example, outliers can be realizations of one variable). A quantity that describes the opportunity of identifying a single observation with one random variable is assumed to be known. That quantity, called the elementary split potential, is strictly referred to the amount of information that an observation can provide about two competitive assumptions concerning the observation distribution. Parameter assessments that maximize the global elementary split potential (concerning all observations), are called M _split estimators. A generalization of M _split estimation presented in the paper refers to the theoretical foundation of M-estimation. An erratum to this article can be found at     

基于SAR干涉点目标分析技术的城市地表形变监测

通过深入研究干涉点目标的相位模型,提出基于空间搜索的邻近点目标干涉相位差解缠方法,用以计算点目标的地形残差和线性形变,以及分离点目标大气延迟相位和非线性形变相位的时空域滤波方法,解决干涉点目标分析中的关键问题.最后,以苏州地区地表沉降监测为应用试验,利用形成的SAR干涉点目标形变信息提取技术,获取苏州市区1992-2002年间的地表沉降信息.研究结果与已有文献记录保持比较好的一致性,证明SAR干涉点目标技术完全可以发展成为应用于城市地表形变监测的实用化技术.

Abstract：

Interferometric point target analysis (IPTA) is one of the latest developments in radar interferometric processing. It is achieved by analysis of the interferometric phases of some individual point targets, which are discrete and present temporarily stable backscattering characteristics, in long temporal series of interferometric SAR images. This paper analyzes the interferometric phase model of point targets, and then addresses two key issues within IPTA process. Firstly, a spatial searching method is proposed to unwrap the interferometric phase difference between two neighboring point targets. The height residual error and linear deformation rate of each point target can then be calculated, when a global reference point with known height correction and deformation history is chosen. Secondly, a spatial-temporal filtering scheme is proposed to further separate the atmosphere phase and nonlinear deformation phase from the residual interferometric phase. Finally, an experiment of the developed IPTA methodology is conducted over Suzhou urban area. Totally 38 ERS-1/2 SAR scenes are analyzed, and the deformation information over 3 546 point targets in the time span of 1992-2002 are generated. The IPTA-derivecl deformation shows very good agreement with the published result, which demonstrates that the IPTA technique can be developed into an operational tool to map the ground subsidence over urban area.     

Variation in tree mortality and regeneration affect forest carbon recovery following fuel treatments and wildfire in the Lake Tahoe Basin, California, USA

Background

Forest fuel treatments have been proposed as tools to stabilize carbon stocks in fire-prone forests in the Western U.S.A. Although fuel treatments such as thinning and burning are known to immediately reduce forest carbon stocks, there are suggestions that these losses may be paid back over the long-term if treatments sufficiently reduce future wildfire severity, or prevent deforestation. Although fire severity and post-fire tree regeneration have been indicated as important influences on long-term carbon dynamics, it remains unclear how natural variability in these processes might affect the ability of fuel treatments to protect forest carbon resources. We surveyed a wildfire where fuel treatments were put in place before fire and estimated the short-term impact of treatment and wildfire on aboveground carbon stocks at our study site. We then used a common vegetation growth simulator in conjunction with sensitivity analysis techniques to assess how predicted timescales of carbon recovery after fire are sensitive to variation in rates of fire-related tree mortality, and post-fire tree regeneration.

Results

We found that fuel reduction treatments were successful at ameliorating fire severity at our study site by removing an estimated 36% of aboveground biomass. Treated and untreated stands stored similar amounts of carbon three years after wildfire, but differences in fire severity were such that untreated stands maintained only 7% of aboveground carbon as live trees, versus 51% in treated stands. Over the long-term, our simulations suggest that treated stands in our study area will recover baseline carbon storage 10?C35?years more quickly than untreated stands. Our sensitivity analysis found that rates of fire-related tree mortality strongly influence estimates of post-fire carbon recovery. Rates of regeneration were less influential on recovery timing, except when fire severity was high.

Conclusions

Our ability to predict the response of forest carbon resources to anthropogenic and natural disturbances requires models that incorporate uncertainty in processes important to long-term forest carbon dynamics. To the extent that fuel treatments are able to ameliorate tree mortality rates or prevent deforestation resulting from wildfire, our results suggest that treatments may be a viable strategy to stabilize existing forest carbon stocks.     

Modelling and Remote Sensing of Land Surface Temperature in Turkey

This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26?C45°E and 36?C42°N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, Eski?ehir, ?stanbul, ?zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LST_ANN) and Becker and Li temperature(LST_B-L) method values have been found as 0.077?K and 0.091?K (training stations), 0.045?K and 0.003?K (testing stations), respectively.     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

In-flight performance analysis of the CHAMP BlackJack GPS Receiver

JPL's BlackJack receiver currently represents the most widely used geodetic grade GPS receiver for space applications. Using data from the CHAMP science mission, the in-flight performance of the BlackJack receiver has been assessed and the impact of various software updates performed during the 2.5 years since launch is described. Key aspects of the study comprise the channel allocation, anomalous data points, and the noise level of the code and carrier data. In addition, it has been demonstrated that the code measurements collected onboard the CHAMP satellite are notably affected by multipath errors in the aft-looking hemisphere, which can be attributed to cross-talk between the occultation antenna string and the primary precise orbit determination antenna. For carrier smoothed 10 s normal points, the code noise itself varies between a minimum of 5 cm at high elevations and 0.5 m (C/A) to 1.0 m (P₁, P₂) at 10° elevation. Carrier-phase data exhibit representative errors of 0.2 to 2.5 mm. The results of the CHAMP GPS data analysis contribute to a better understanding and possible improvement of the BlackJack receiver and support the design of optimal data editing and weighting strategies in precise orbit determination applications.