Perceptions of climate change in China: The research and policy connection

Global climate change has evolved from a scientific problem into an economic and political problem oI worlOwloe rater- est. National perspectives play a crucial role in addressing climate change. Mutual understanding of perspectives is nec- essary to result in rational policies and a consensus among stakeholders with divergent interests. Conceptual frameworks for understanding the problem of climate change in China, the largest developing country and the largest greenhouse gas emitter, are of great significance to national and international efforts to address the problems of climate change. Chinese perceptions of climate change as a sustainable development problem have recently been in tension with an emerging Western perspective that frames climate change as a security issue. This paper explores Chinese perceptions of climate change as expressed in recent governmental policy statements, public opinion surveys, and academic scholarship with a focus on publications in Chinese-language journals, often unfamiliar in the West. It looks at the relationship between Chinese research and policy and finds that the Chinese policy frame of climate change as a sustainable development problem draws from the body of domestic research and is reflective of the perspectives and multidisciplinary approach of Chinese researchers in areas of climate change.     

施肥对新垦绿洲风沙土肥力及碳积累的影响

利用2005年安排在临泽边缘绿洲沙地农田的长期施肥定位试验,研究不同用量有机肥、化肥、有机肥和化肥配施对绿洲沙地土壤肥力及有机碳积累的影响。试验包括高量有机肥单施(M3),氮磷化肥单施(NP3),低、中、高量氮磷钾化肥单施(NPK1,NPK2,NPK3),及低、中、高量氮磷钾化肥配施高、中、低量有机肥9个处理(NPK1M3,NPK2M2,NPK3M1),测定分析10年后不同施肥处理耕层(0~20 cm)土壤物理化学性状特征及有机碳动态。结果表明:施有机肥及有机无机配施处理较单施化肥处理容重下降0.13 g·cm^-3,田间持水量提高6.7%,单施有机肥、有机无机配施较单施化肥,土壤有机碳(SOC)和全氮含量分别提高64.8%、36.3%和64.9%、49.5%。高量施用氮磷化肥和氮磷钾化肥处理全磷含量最高,有机肥及有机无机配施较单施化肥有效氮含量显著增加,有机无机配施及高量施用磷肥土壤有效磷积累明显,高量施用有机肥能显著提升有效钾含量。连续施肥处理10年后,SOC含量提高了1.68~2.84倍,土壤全氮、全磷、碱解氮及有效磷均有一定程度的提高,但单施化肥及有机肥与氮磷化肥配施有效钾含量下降。SOC的积累速率单施化肥、有机无机配施、单施有机肥处理分别为0.27、0.59,0.87 g·kg^-1·a^-1。增施有机肥、适量减少化肥投入、氮磷钾化肥的平衡施用是绿洲沙地农田土壤肥力持续提升的施肥管理对策。     

The application and comparison of several flux profile relations in CoLM

This paper discusses the important role that flux profile relations play in momentum flux, sensible heat flux, and latent heat flux simulations in CoLM （Common Land Model） and compares the application of three flux profile relation schemes in CoLM by means of the Loess Plateau Land-Atmosphere Interaction Pilot Experiment （LOPEX） of 2005. It reveals that the results simulated by the model barely changed in the original flux profile schemes of the models a~er eliminating the very stable condition and the very unstable condition, and there were only tiny changes in numerical values. This indicates that the corrected terms added to fm（ξm）,fh（ξh） were very tiny and can be ignored under very stable and very unstable circumstances. According to a comparison of the three flux profile relations, the simulation results were basically coherent by using any CoLM： the correlation coefficient of the simulation value and the observed value was 0.89, and this bears on the coherence with the numerical procedures for the flux pro- file relations under unstable circumstances. The simulation results were improved considerably by utilizing the Lobocki flux pro- file schemes, which numerical procedures under unstable circumstances differed significantly fi＇om other three flux profile schemes; in this case the correlation coefficient of the value of simulation and the observed value became 0.95. In the next itera- tion of this study, it will be of great importance for the development of the land surface process model to continue experimenting with the application of some novel flux profile schemes in the land surface process models in typical regions.     

A density-based approach for detecting network-constrained clusters in spatial point events

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.     

An enhanced approach for surface flow routing over drainage‐constrained triangulated irregular networks

The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model.     

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.     

Sea-Level Change Over the China Sea and Its Vicinity Derived from 25-Year T/P Series Altimeter Data

The characteristics of sea-level change in the China Sea and its vicinity are studied by combining TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 altimeter data. First, the sea-surface height is computed by using monthly data via collinear adjustment, regional selection, and crossover adjustment. The sea-level anomaly (SLA) from October 1992 to July 2017 is calculated based on the difference that is obtained by the value derived from the inverse distance weighting method to interpolate the CNES_CLS15 model value at a normal point. By analyzing the satellite data at the same time in orbit, three mean bias groups over the China Sea and its vicinity are obtained: the difference between T/P and Jason-1 is ??11.76 cm, the difference between Jason-1 and Jason-2 is 9.6 cm, and the difference between Jason-2 and Jason-3 is 2.42 cm. To establish an SLA series for 25 years in the study area, the SLAs are corrected. Mean rate of sea-level rise of the Bohai Sea, Yellow Sea, East China Sea, and South China Sea of 4.87 mm/a, 2.68 mm/a, 2.88 mm/a, and 4.67 mm/a, respectively, is found by analyzing the series of SLAs.     

Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

Autonomous orbit determination is the ability of navigation satellites to estimate the orbit parameters on-board using inter-satellite link (ISL) measurements. This study mainly focuses on data processing of the ISL measurements as a new measurement type and its application on the centralized autonomous orbit determination of the new-generation Beidou navigation satellite system satellites for the first time. The ISL measurements are dual one-way measurements that follow a time division multiple access (TDMA) structure. The ranging error of the ISL measurements is less than 0.25 ns. This paper proposes a derivation approach to the satellite clock offsets and the geometric distances from TDMA dual one-way measurements without a loss of accuracy. The derived clock offsets are used for time synchronization, and the derived geometry distances are used for autonomous orbit determination. The clock offsets from the ISL measurements are consistent with the L-band two-way satellite, and time–frequency transfer clock measurements and the detrended residuals vary within 0.5 ns. The centralized autonomous orbit determination is conducted in a batch mode on a ground-capable server for the feasibility study. Constant hardware delays are present in the geometric distances and become the largest source of error in the autonomous orbit determination. Therefore, the hardware delays are estimated simultaneously with the satellite orbits. To avoid uncertainties in the constellation orientation, a ground anchor station that “observes” the satellites with on-board ISL payloads is introduced into the orbit determination. The root-mean-square values of orbit determination residuals are within 10.0 cm, and the standard deviation of the estimated ISL hardware delays is within 0.2 ns. The accuracy of the autonomous orbits is evaluated by analysis of overlap comparison and the satellite laser ranging (SLR) residuals and is compared with the accuracy of the L-band orbits. The results indicate that the radial overlap differences between the autonomous orbits are less than 15.0 cm for the inclined geosynchronous orbit (IGSO) satellites and less than 10.0 cm for the MEO satellites. The SLR residuals are approximately 15.0 cm for the IGSO satellites and approximately 10.0 cm for the MEO satellites, representing an improvement over the L-band orbits.     

Geographical impacts on social networks from perspectives of space and place: an empirical study using mobile phone data

Space and place are two fundamental concepts in geography. Geographical factors have long been known as drivers of many aspects of people’s social networks. But whether and how space and place affect social networks differently are still unclear. The widespread use of location-aware devices provides a novel source for distinguishing the mechanisms of their impacts on social networks. Using mobile phone data, this paper explores the effects of space and place on social networks. From the perspective of space, we confirm the distance decay effect in social networks, based on a comparison between synthetic social ties generated by a null model and actual social ties derived from real-world data. From the perspective of place, we introduce several measures to evaluate interactions between individuals and inspect the trio relationship including distance, spatio-temporal co-occurrence, and social ties. We found that people’s interaction is a more important factor than spatial proximity, indicating that the spatial factor has a stronger impact on social networks in place compared to that in space. Furthermore, we verify the hypothesis that interactions play an important role in strengthening friendships.     

Weak GPS signal tracking using FFT discriminator in open loop receiver

An open loop tracking architecture, which tracks GPS signals under weak and challenging conditions, is analyzed. The in-phase and quadrature-phase integration pair is regarded as a single tone complex signal. An FFT-based method is used as a frequency discriminator to estimate the Doppler frequency residual of the single tone signal. Another FFT-based method applies complex squaring to eliminate the effect of the navigation data bits polarities. The performance of the FFT-based discriminators is assessed in three criteria. Those criteria are the signal strength and dynamic range that can be tracked and the accuracy of the estimated Doppler frequency. In addition, the performance of the discriminators is analyzed to provide the theoretical and simulated peak detection probability. The results indicate that the FFT discriminator can track signals about 5 dB weaker than the signals that can be tracked by the complex squared FFT discriminator. In a quasi-static environment, the Doppler frequency residual can be assumed to be around zero, which can enable the FFT-based discriminators to track signals with approximately 2 dB less power. Moreover, the performance of the FFT-based discriminators is compared with the performance of two other frequency discriminators, namely the fast–slow and power-based. The comparison results indicate that these two frequency discriminators give higher frequency estimation accuracy, but they have a narrower dynamic range.