Evolution and spatial characteristics of tourism field strength of cities linked by high-speed rail (HSR) network in China

Traffic is an indispensable prerequisite for a tourism system. The “four vertical and four horizontal” HSR network represents an important milestone of the “traffic revolution” in China. It will affect the spatial pattern of tourism accessibility in Chinese cities, thus substantially increasing their power to attract tourists and their radiation force. This paper examines the evolution and spatial characteristics of the power to attract tourism of cities linked by China’s HSR network by measuring the influence of accessibility of 338 HSR-linked cities using GIS analysis. The results show the following. (1) The accessibility of Chinese cities is optimized by the HSR network, whose spatial pattern of accessibility exhibits an obvious traffic direction and causes a high-speed rail-corridor effect. (2) The spatial pattern of tourism field strength in Chinese cities exhibits the dual characteristics of multi-center annular divergence and dendritic diffusion. Dendritic diffusion is particularly more obvious along the HSR line. The change rate of urban tourism field strength forms a high-value corridor along the HSR line and exhibits a spatial pattern of decreasing area from the center to the outer limit along the HSR line. (3) The influence of the higher and highest tourism field strength areas along the HSR line is most significant, and the number of cities that distribute into these two types of tourism field strengths significantly increases: their area expands by more than 100%. HSR enhances the tourism field strength value of regional central cities, and the radiation range of tourism attraction extends along the HSR line.     

Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province,China

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a^-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a^-1<θ<1.7 d·10a^-1, θ is the change slope of maize phenology). The length of vegetative period (VPL) (from emergence to tasseling) was shortened by 0.9 d·10a^-1, while the length of generative period (GPL) (from tasseling to maturity) was lengthened by 1.7 d·10a^-1. The growing season length (GSL) (from emergence to maturity) was lengthened by 0.4 d·10a^-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days (GDD) (p<0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.     

A proposal for the theoretical analysis of the interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations

Mega-urban agglomerations are strategic core areas for national economic development and the main regions of new urbanization. They also have important roles in shifting the global economic center of gravity to China. However, the development of mega-urban agglomerations has triggered the interactive coercion between resources and the eco-environment. The interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations represent frontier and high-priority research topics in the field of Earth system science over the next decade. In this paper, we carried out systematic theoretical analysis of the interactive coupling mechanisms and coercing effects between urbanization and the eco-environment in mega-urban agglomerations. In detail, we analyzed the nonlinear-coupled relationships and the coupling characteristics between natural and human elements in mega-urban agglomerations. We also investigated the interactive coercion intensities between internal and external elements, and the mechanisms and patterns of local couplings and telecouplings in mega-urban agglomeration systems, which are affected by key internal and external control elements. In addition, we proposed the interactive coupling theory on urbanization and the eco-environment in mega-urban agglomerations. Furthermore, we established a spatiotemporal dynamic coupling model with multi-element, multi-scale, multi-scenario, multi-module and multi-agent integrations, which can be used to develop an intelligent decision support system for sustainable development of mega-urban agglomerations. In general, our research may provide theoretical guidance and method support to solve problems related to mega-urban agglomerations and maintain their sustainable development.     

快速城市化过程中的深圳东部海岸地貌环境与可持续发展

The geomorphological environment is one of the most fundamental variables af-fecting the development of human society.The mission of geomorphological environment research is to explore the most basic environment and features of our Earth’s surface mor-phology.The results can be applied to resource evaluation,environmental protection and reducing and preventing geological disasters.Thus,it can serve to help achieve sustainable development.This paper examines the Shenzhen east coastal zone as a case strongly in-fluenced by urban expansion.We use modern geomorphological theory and methods,along with GIS and RS techniques,to reveal key characteristics of the geomorphological environ-ment and landform classification.Furthermore,coastal ecosystem evaluation and regional resources sustainable utilization should be considered relative to the corresponding geo-morphological environment.Based on this study,we conclude that modern geomorphological theory and methods,supported by "3S" techniques including GIS,RS and GPS,can play an important role in resolving the environment,resources and population problems as well as sustainable development challenges facing humankind at present.     

改革开放以来中国农业政策效果的时空计量分析

Since reform and opening up, how much contribution has China’s implementation of new agricultural policy made to agricultural output? This paper is trying to establish an agricultural policy output econometric model for doing a quantitative analysis of China’s new agricultural policy. The results show that China’s agricultural policies on agricultural output have an average contribution rate of about 7% since 1978, which is consistent with the OECD’s basic forecast. There are obvious temporal and spatial differences. Generally speaking, we can divide the contribution of agricultural policy into three periods, which are the start-up phase from 1978 to 1991 (14 years), the stationary phase from 1992 to 2002 (11 years) and the rising phase from 2003 to 2008 (6 years). In space, the contribution of agricultural policy underwent a process from the all-low in the start-up phase, the gradual increase in the stationary phase to the all-high in the rising phase. Northern and western regions are more sensitive to policies. There are three major factors that can affect the contribution of regional agricultural policies, which are the process of national industrialization strategy, terrain and the level of local finance.     

New evidence for extreme and persistent terminal medieval drought in California’s Sierra Nevada

The level of Cliff Lake, a small, subalpine, moraine-dammed lake in California’s south central Sierra Nevada, was approximately 5 m lower than present for 50 years or more approximately 600 years ago, this determined by radiocarbon dating of wood recovered from a submerged tree stump found in the lake. This finding corresponds to commensurate data from throughout much of western North America, suggesting the duration and magnitude of terminal medieval megadrought was similar throughout the region. Ultimately this datum helps give credence to the perspective that though late Holocene climate in California was indeed variable, the effects of terminal Medieval megadrought was similar across both time and broad geographic expanse.     

A Comparative Analysis of Weights of Evidence,Evidential Belief Functions,and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation

Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, which can be used for exploration targeting. The quality of the mineral potential maps is dependent on the quality of the data used as inputs, with higher quality inputs producing higher quality outputs. In mineral exploration, particularly in regions with little to no exploration history, datasets are often incomplete at the scale of investigation with data missing due to incomplete mapping or the unavailability of data over certain areas. It is not always clear that datasets are incomplete, and this study examines how mineral potential mapping results may differ in this context. Different methods of mineral potential mapping provide different ways of dealing with analyzing and integrating incomplete data. This study examines the weights of evidence (WofE), evidential belief function and fuzzy logic methods of mineral potential mapping using incomplete data from the Carajás mineral province, Brazil to target for orogenic gold mineralization. Results demonstrate that WofE is the best one able to predict the location of known mineralization within the study area when either complete or unacknowledged incomplete data are used. It is suggested that this is due to the use of Bayes’ rule, which can account for “missing data.” The results indicate the effectiveness of WofE for mineral potential mapping with incomplete data.     

Metallic Mineral Resources in the Twenty-First Century. I. Historical Extraction Trends and Expected Demand

Industrial, technological, and economic developments depend on the availability of metallic raw materials. As a greater fraction of the Earth’s population has become part of developed economies and as developed societies have become more affluent, the demand on metallic mineral resources has increased. Yet metallic minerals are non-renewable natural resources, the supply of which, even if unknown and potentially large, is finite. An analysis of historical extraction trends for eighteen metals, going back to the year 1900, demonstrates that demand of metallic raw materials has increased as a result of both increase in world population and increase in per-capita consumption. These eighteen metals can be arranged into four distinct groups, for each of which it is possible to identify a consistent pattern of per-capita demand as a function of time. These patterns can, in turn, be explained in terms of the industrial and technological applications, and in some cases conventional uses as well, of the metals in each group. Under the assumption that these patterns will continue into the future, and that world population will grow by no more than about 50% by the year 2100, one can estimate the amount of metallic raw materials that will be required to sustain the world’s economy throughout the twenty-first century. From the present until the year 2100, the world can be expected to require about one order of magnitude more metal than the total amount of metal that fueled technological and economic growth between the age of steam and the present day. For most of the metals considered here, this corresponds to 5–10 times the amount of metal contained in proven ore reserves. The two chief driving factors of this expected demand are growth in per-capita consumption and present-day absolute population numbers. World population is already so large that additional population growth makes only a small contribution to the expected future demand of metallic raw materials. It is not known whether or not the amount of metal required to sustain the world’s economy throughout this century exists in exploitable mineral resources. In the accompanying paper, I show that it is nevertheless possible to make statistical inferences about the size distribution of the mineral deposits that will need to be discovered and developed in order to satisfy the expected demand. Those results neither prove nor disprove that the needed resources exist but can be used to improve our understanding of the challenges facing future supply of metallic raw materials.     

Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au–Cu deposits in Catanduanes Island, where 17 hydrothermal Au–Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.     

Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.