Sparse Data Division Using Data Segmentation and Kohonen Network for Neural Network and Geostatistical Ore Grade Modeling in Nome Offshore Placer Deposit

In this paper, sparse data problem in neural network and geostatistical modeling for ore-grade estimation was addressed in the Nome offshore placer gold deposit. The problem of sparse data arises because of the random data division into training, validation, and test subsets during ore-grade modeling. In this regard, the possibility of generating statistically dissimilar data subsets by random data division was also explored through a simulation exercise. A combined approach of data segmentation and application of a Kohonen network then was used to solve the data division problem. Two neural networks and five kriging models were applied for grade modeling. The neural network was trained using an early stopping method. Performance evaluation of the models was carried out on the test data set. The study results indicated that all the models that were investigated in this study performed almost equally. It was also revealed that by using the secondary variable watertable depth the neural network and the kriging models slightly improved their prediction precision. Further, the overall R ² of the models was poor as a result of high nugget (noisy) component in ore-grade variation.     

中国高铁网络结构特征及其组织模式

基于2018年高铁网络OD数据,运用社会网络分析方法从高铁网络、城市节点等方面探讨中国城市高铁网络结构特征及其地域组织模式,结果表明:①中国高铁网络整体较为松散,东北地区网络密度最高,东部和中部地区作为整体网络的中介作用明显;②重要高铁线路的"廊道效应"突出,中心度呈现出以京广、京沪和沪昆高铁组成的"三角旗状"空间格局并向两侧城市呈不规则递减的态势;③多层级网络识别出紧密关联高铁线路和四横四纵向八横八纵格局的转变;④高铁网络的地域组织形式表现为点-轴串珠模式、双核组团模式和极核模式,高铁网络的完善使组织模式由单核趋向于网络化转变。     

Use a Spatial Analysis Model to Assess Habitat Quality in Lashihai Watershed

Habitat quality assessments are of great significance for protecting biodiversity. This study analyzes the changing habitat quality of Lashihai watershed based on SPOT satellite images. We extracted the land use data for Lashihai watershed in Yunnan province for the years 2000 and 2015, and then used an InVEST model to evaluate habitat degradation, habitat quality and habitat scarcity in the study area from 2000 to 2015. Spatial statistical methods were used to determine changes to spatial dynamics. Results indicate that the number of areas with habitat degradation was generally small, and that both the number of areas with habitat degradation and the degree of degradation had fallen noticeably during the fifteen-year study period. In general, the quality of habitats was maintained or improved, while the quality of habitats decreased in only a few areas. The scarcity of habitats for cultivated land had increased, the tension between people and land use was relatively prominent. The reason habitat quality in Lashihai watershed has improved can be attributed to three factors: 1) The policy of returning farmland to forests since 2000 has been well implemented and has achieved remarkable results. Loss of forests from logging and deforestation has basically been eliminated, and great progress has been made restoring the ecological environment. 2) High background value of quality habitat suitability benefits from the research area’s high vegetation coverage. 3) The development of the local tourism economy has transformed the area’s ecological advantages into an economic bonus, greatly increasing the income level and living standards of residents. At the same time, the ecological resource bonus has increased the enthusiasm of residents for ecological protection and has helped to promote the protection of local eco-systems, both reducing ecological degradation and improving habitat quality. At the same time, increasing conflicts between land and people should be addressed. Support is needed to promote development of the ecological economy while continuously reducing ecological degradation and further increasing residents’ income. There must be less reliance on industry and less pressure on both land and people, all the while ensuring that the local economy and ecology can more forward together in a sustainable way.     

Bayesian and Neural Network Approaches to Estimate Deep Temperature Distribution for Assessing a Supercritical Geothermal System: Evaluation Using a Numerical Model

The temperature distribution at depth is a key variable when assessing the potential of a supercritical geothermal resource as well as a conventional geothermal resource. Data-driven estimation by a machine-learning approach is a promising way to estimate temperature distributions at depth in geothermal fields. In this study, we developed two methodologies—one based on Bayesian estimation and the other on neural networks—to estimate temperature distributions in geothermal fields. These methodologies can be used to supplement existing temperature logs, by estimating temperature distributions in unexplored regions of the subsurface, based on electrical resistivity data, observed geological/mineralogical boundaries, and microseismic observations. We evaluated the accuracy and characteristics of these methodologies using a numerical model of the Kakkonda geothermal field, Japan, where a temperature above 500 °C was observed below a depth of about 3.7 km. When using geological and geophysical knowledge as prior information for the machine learning methods, the results demonstrate that the approaches can provide subsurface temperature estimates that are consistent with the temperature distribution given by the numerical model. Using a numerical model as a benchmark helps to understand the characteristics of the machine learning approaches and may help to identify ways of improving these methods.

     

Reservoir Characterization Using Multi-component Seismic Data in a Novel Hybrid Model Based on Clustering and Deep Neural Network

Natural Resources Research - Effective use of the difference between longitudinal and converted shear waves in reservoir sensitivity analysis is a key component to reduce the multi-solution problem...     

基于网络K函数法的地理对象分布模式分析——以香港岛餐饮业空间格局为例

很多地理对象的空间分布与空间上呈现网状结构的地理现象高度相关,分析这些地理对象的分布模式,在地理研究中有重要意义.该文采用由平面空间扩展到网状结构空间的网络K函数法,以香港岛餐饮业地理空间格局为例开展研究.应用单变量K函数法分析餐饮店在网状结构空间中的分布模式,应用双变量交叉K函数法分析餐饮店分布是否受交通站点及旅游景点影响,并对不同尺度下餐饮店地理选址和空间分布规律进行探索与分析.     

Multi-parameter Analysis of Local Singularity Mapping and Its Application to Identify Geochemical Anomalies in the Xishan Gold Deposit,North China

Natural Resources Research - Identification of geochemical anomalies from geological background is of great significance in the exploration of complex mineralization systems. For a 2D problem, the...     

Structural Analysis for Gold Mineralization Using Remote Sensing and Geochemical Techniques in a GIS Environment: Island of Lesvos,Hellas

Exploration for epithermal Au has been active lately in the Aegean Sea of the eastern Mediterranean Basin, both in the islands of the Quaternary arc and in those of the back-arc region. The purpose of this study was the structural mapping and analysis for a preliminary investigation of possible epithermal gold mineralization, using remotely sensed data and techniques, structural and field data, and geochemical information, for a specific area on the Island of Lesvos. Therefore, Landsat-TM and SPOT-Pan satellite images and the Digital Elevation Model (DEM) of the study area were processed digitally using spatial filtering techniques for the enhancement and recognition of the geologically significant lineaments, as well as algebraic operations with band ratios and Principal Component Analysis (PCA), for the identification of alteration zones. Statistical rose diagrams and a SCHMIDT projection Stereo Net were generated from the lineament maps and the collected field data (dip and strike measurements of faults, joints, and veins), respectively. The derived lineament map and the band ratio images were manipulated in a GIS environment, in order to study the relation of the tectonic pattern to both the alteration zoning and the geomorphology of the volcanic field of the study area. Target areas of high interest for possible mineralization also were specified using geochemical techniques, such as X-Ray Diffraction (XRD) analysis, trace-element, and fluid-inclusion analysis. Finally, preliminary conclusions were derived about possible mineralization, the type (high or low sulfidation), and the extent of mineralization, by combining the structural information with geochemical information.     

基于IBIS模型的1955~2006年中国土壤温度模拟及时空演变分析

基于IBIS模型对中国1955~2006年的土壤上层1m的年平均与月平均土壤温度进行模拟,并利用全国气象站点土壤温度观测数据对模拟结果进行验证,结果显示中国南方区的模拟效果优于北方及青藏高原区,春、夏、秋三季模拟效果优于冬季,总体而言取得了较满意的效果。基于模拟结果,利用Mann-Kendall方法对中国1955~2006年年平均和月平均土壤温度进行趋势分析的结果表明,年平均土壤温度,中国北方呈显著上升趋势,南方呈非显著上升趋势,四川盆地、贵州中部、藏东南及天山地区等小部分区域呈现显著或非显著下降趋势;月平均土壤温度,北方基本保持显著上升趋势,南方地区7~9月份总体呈现出下降的趋势,8月份最为显著。     

南昌地区建设用地空间扩展的广义转移概率模型建设与应用研究

对南昌地区城市发育约束因素的分析的基础上,基于非城市像元所处的城市化梯度、距离最近建成区斑块的距离、最近建成区斑块的规模、边缘像元的邻域水平等4个城市景观格局因子和道路及地形等两个社会经济和自然影响因子,构建了广义转移概率模型,并开展了相关的动态模拟研究。表明,与传统模拟方法相比,该模型具有比较理想的精度水平,模拟结果能够很好地反映南昌地区今后城市建设用地发展趋势,提出的模型手段改进设计获得了令人满意的效果,是对现行城市景观动态模拟研究工作的一个重要的方法论补充和完善。     

基于互联网数据的城市社区租金评估及 空间格局制图——以深圳市为例

准确刻画精细化尺度下的城市房租空间格局,对于研究城市居住行为、提高城市规划合理性十分重要。文章提出了一种基于互联网房租数据作为可靠数据源的城市房租空间格局制图方法。以深圳市作为研究区,通过广泛采集开放平台中用户发布的租房信息,绘制社区行政区尺度的房租空间分布图。房租空间制图涉及到对于没有样本数据区域平均房租的评估,因此,选取一系列与房租相关的房产属性、房屋区位及配套设施的评价指标,采用前馈神经网络技术构建评估模型。以2015年深圳市的住宅租赁市场作为研究对象,通过对结果的分析,以及与权威部门发布的统计数据进行比较,表明此方法能够有效地绘制社区尺度下城市房租的空间分布,模型预测结果的误差（%RMSE）为13.87%。所使用的互联网房租数据、POIs数据及前馈神经网络的建模工具均是开源的,而且所提出的方法论具有普适性,能够应用于其他研究区的房租空间格局制图,具有实践意义。     

Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network

Natural Resources Research - Ground vibration (PPV) is one of the hazard effects induced by blasting operations in open-pit mines, which can affect the surrounding structures, particularly the...     

空间正义视角下乡村权的概念框架与比较研究

“乡村权”概念是近年空间正义研究在乡村地域进行理论延伸与实践检验的新领域,其通过揭示以土地为空间媒介的乡村权利剥夺现象,批判性分析乡村空间资源分配和空间生产过程中出现的非正义问题。延续激进地理学视角,文章聚焦“乡村土地”与“村民身份”两大问题,基于突尼斯、印度、黎巴嫩等南方国家,以及英国、法国、意大利等北方国家的案例,揭示村民在生产、生活及意识层面所处的非正义境况（即“被迫非农化”）,并探寻村民为寻求空间正义所采取的个人或集体抗争方式（即“自发再农化”）。通过案例比较发现：1）南方国家与北方国家的乡村案例表现出的被迫非农化现象具有共性,其本质都是资本剥削导致的乡村土地和村民身份被剥夺;2）南方和北方国家的自发再农化手段存在差异,南方国家的村民主要采取法律途径或极端方式,北方国家则依托自上而下的国家政策保障与自下而上的地方能力建设。进而,归纳出乡村权三大内涵,即“占有权（拥有农地并进行农业生产）”“定居权（以村民的生活方式生活在乡村）”“参与权（自主决定是否非农化）”。最后,建议在中国乡村振兴中,通过科学知识共享、社区学习与合作等方式提升村民自身能力,实现村民在乡村空间占有、定居、参与的...     

Using a migration systems approach to understand the link between climate change and urbanisation in Malawi

Most scholarship on rural–urban migration in Sub-Saharan Africa demonstrates that migrants tend to move in a “circular” fashion and only spend short periods of time in cities before returning home to rural villages. However, some scholars working on the impacts of climate change on migration suggest that deteriorating environmental conditions may undermine rural livelihoods and lead people to move to cities for longer periods of time. If this is true, then climate change threatens to accelerate urbanisation and lead to renewed stress on urban infrastructure. The purpose of this paper is to explore these positions and we do so by collecting survey [n = 241], in-depth interview [n = 75] and focus group [n = 123 participants] data from rural and urban Malawi. Two key results stand out as significant. The first is that migrants in Malawi's capital city tend to stay in the urban environment for longer periods of time than conventional understandings of migration would predict. The second key result is that climate change may actually lead, in the case of Malawi, to reverse (i.e urban–rural) migration. This is because many of the people in Malawi's cities depend on products produced in rural environments (e.g. food and fuelwood). If climate change undermines rural livelihoods, then many urban residents will find the basis of their livelihoods removed and will likely respond by moving back to rural villages. Overall, our results, therefore, suggest that in at least one case the effect of climate change on migration may not be to increase migration towards cities but to stimulate an exodus from cities and back to the rural countryside.     

坡向和微地形对大型土壤动物空间分布格局的影响

尽管在景观和区域尺度上对土壤动物空间分布格局的研究已较多,但在小尺度上对局部微生境条件如何影响土壤动物多样性及其空间分布格局的研究还很少。以典型温带次生林为研究对象,采用样方法系统调查了林地阴坡和阳坡4个不同地形部位大型土壤动物群落的密度,并测定了不同地形部位的生境条件。采用三因子方差分析和对应分析等方法定量研究了坡向和地形部位对大型土壤动物群落密度的空间分布格局的影响。主要表现在：①在采集到的160个土壤样品中共检测到动物个体4 148个,分别隶属于26个不同的土壤动物类群;②坡向和地形部位对土壤动物的空间分布格局有显著的影响,但不同土壤动物类群对坡向和地形部位的响应模式存在一定的差异,这种差异的形成可能与不同土壤动物类群的生活习性和生物学特征密切相关。其结论是：在小尺度上,林地的坡向和微地形条件主要通过影响局部小生境的生物和非生物因子组合特征而对土壤动物的空间分布格局产生重要影响。     

Using a Bayesian estimator to combine information from a cluster analysis and remote sensing data to estimate high-resolution data for agricultural production in Germany

In Germany, a county-resolution data set that consists of 35 land-use and animal-stock categories has been used extensively to assess the impact of agriculture on the environment. However, because such environmental effects as emission or nutrient surplus depend on the location, even a county resolution might produce misleading results. The aim of this article is to propose a Bayesian approach which combines two sorts of information, with one being treated as defining the prior and the other the data to form a posterior, used to estimate a data set at a municipality resolution. We define the joint prior density function based on (i) remote sensing data, thus accounting for differences in county data and missing data at the municipality level, and (ii) the results of a cluster analysis that was previously applied to the micro-census, whereas the data are defined by official statistics at the county level. This approach results in a fairly accurate data set at the municipality level. The results, using the proposed method, are validated by the national research data centre by comparing the estimates to actual observations. The test statistics presented here demonstrate that the proposed approach adequately estimates the production activities.     

Using unsupported lead-210 measurements to investigate soil erosion and sediment delivery in a small Zambian catchment

Traditional techniques used to assemble information on rates of erosion and soil redistribution possess many important limitations. As a result, the use of environmental radionuclides, and more particularly ¹³⁷Cs measurements, has attracted increasing attention in recent years as a means of obtaining spatially distributed information on rates of erosion and deposition. The application of the ¹³⁷Cs approach is, however, hampered in some areas of the world where ¹³⁷Cs inventories are low and the low concentrations of ¹³⁷Cs found in soils and sediments cause problems for laboratory analysis. These problems will increase as time progresses due to the radioactive decay of the existing inventory, most of which was deposited as fallout ca. 40 years ago. This contribution explores the potential for using another fallout radionuclide, namely unsupported ²¹⁰Pb, as an alternative to ¹³⁷Cs, in the small (63 km²) Upper Kaleya catchment in southern Zambia where ¹³⁷Cs inventories are already very low. The approach employed with unsupported ²¹⁰Pb is similar to that used for ¹³⁷Cs, although the essentially constant fallout of unsupported ²¹⁰Pb through time means that the resulting estimates of erosion and soil redistribution rates reflect a longer period of time (ca. 100 years rather than ca. 40 years). The estimates of erosion and deposition rates derived from the unsupported ²¹⁰Pb measurements are used to construct typical sediment budgets for the three main land-use types in the Upper Kaleya catchment, namely, commercial cultivation, communal cultivation and bush grazing. The results obtained from the unsupported ²¹⁰Pb are compared with equivalent results based on ¹³⁷Cs measurements provided by a previous investigation undertaken in the study catchment. The two sets of results are highly consistent. The study reported confirms the viability of using unsupported ²¹⁰Pb as an alternative to ¹³⁷Cs in this environment and demonstrates that conjunctive use of both radionuclides can provide additional information on the erosional history of a study area.