空间尺度转换数据精度评价的准则和方法

空间尺度问题是地理学、生态学和水文学等多个学科的基础科学问题之一。空间数据尺度转换是将数据从一个空间尺度转换到另一个空间尺度的过程, 它是尺度科学研究的重要内容之一。对尺度转换后的成果数据深入分析, 提炼尺度转换成果数据精度评价的原则、指标以及模型方法, 这对正确选择和应用尺度转换成果数据具有重要意义。在详细评述尺度和尺度转换研究概念、内容和主要进展的基础上, 本文主要从数据处理、地图学角度出发, 提出了空间数据尺度转换精度评价的3 项基本准则, 即保持构成信息守恒、保持面积信息守恒、保持区域空间格局和形态信息守恒。继而据此将当前常见的指标进行了梳理和归并;根据上述准则和指标, 结合GIS 方法、常规统计方法、地统计方法等, 给出了上述评价指标的计算模型及其应用方法和典型案例。最后指出, 在实际应用中需结合研究目标, 针对性选择尺度转换效应函数, 通过开展模型模拟和对比分析, 最终确定合适的尺度转换方法。     

A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules

Cellular automata (CA) have emerged as a primary tool for urban growth modeling due to its simplicity, transparency, and ease of implementation. Sensitivity analysis is an important component in CA modeling for a better understanding of errors or uncertainties and their propagation. Most studies on sensitivity analyses in urban CA modeling focus on specific component such as neighborhood configuration or stochastic perturbation. However, sensitivity analysis of transition rules, which is one of the core components in CA models, has not been systematically done. This article proposes a systematic sensitivity analysis of major operational components in urban CA modeling using a stepwise comparison approach. After obtaining transition rules, three stages (i.e. static calibration of transition rules, dynamic evolution with varied time steps, and incorporation with stochastic perturbation) are designed to facilitate a comprehensive analysis. This scheme implemented with a case study in Guangzhou City (China) reveals that gaps in performance from static calibration with different transition rules can be reduced when dynamic evolution is considered. Moreover, the degree of stochastic perturbation is closely related to obtain urban morphology. However, a more realistic (i.e. fragmented) urban landscape is achieved at the cost of decreasing pixel-based accuracy in this study. Thus, a trade-off between pixel-based and pattern-based comparisons should be balanced in practical urban modeling. Finally, experimental results illustrate that models for transition rules extraction with good quality can do an assistance for urban modeling through reducing errors and uncertainty range. Additionally, ensemble methods can feasibly improve the performance of CA models when coupled with nonparametric models (i.e. classification and regression tree).     

Comparing models of debris-flow susceptibility in the alpine environment

Debris-flows are widespread in Val di Fassa (Trento Province, Eastern Italian Alps) where they constitute one of the most dangerous gravity-induced surface processes. From a large set of environmental characteristics and a detailed inventory of debris flows, we developed five models to predict location of debris-flow source areas. The models differ in approach (statistical vs. physically-based) and type of terrain unit of reference (slope unit vs. grid cell). In the statistical models, a mix of several environmental factors classified areas with different debris-flow susceptibility; however, the factors that exert a strong discriminant power reduce to conditions of high slope-gradient, pasture or no vegetation cover, availability of detrital material, and active erosional processes. Since slope and land use are also used in the physically-based approach, all model results are largely controlled by the same leading variables.Overlaying susceptibility maps produced by the different methods (statistical vs. physically-based) for the same terrain unit of reference (grid cell) reveals a large difference, nearly 25% spatial mismatch. The spatial discrepancy exceeds 30% for susceptibility maps generated by the same method (discriminant analysis) but different terrain units (slope unit vs. grid cell). The size of the terrain unit also led to different susceptibility maps (almost 20% spatial mismatch). Maps based on different statistical tools (discriminant analysis vs. logistic regression) differed least (less than 10%). Hence, method and terrain unit proved to be equally important in mapping susceptibility.Model performance was evaluated from the percentages of terrain units that each model correctly classifies, the number of debris-flow falling within the area classified as unstable by each model, and through the metric of ROC curves. Although all techniques implemented yielded results essentially comparable; the discriminant model based on the partition of the study area into small slope units may constitute the most suitable approach to regional debris-flow assessment in the Alpine environment.     

基于Voronoi模型的海南岛旅游资源集合体空间边界提取

旅游资源是旅游业发展的物质条件,是开展各项旅游活动的载体和基础。旅游资源分类方法和评价理论研究已取得了较大的进展,但在旅游资源调查与规划实践中,以有研究通常将一个景区或大规模地理实体与小规模实体在同一个标准下衡量与对比,未考虑旅游资源的地理空间尺度特征。不同尺度的旅游地域空间,旅游资源评价、规划方法及其开发方向都不同。本文目的是通过梳理不同尺度旅游资源空间单元概念,对最难界定的集合体进行空间识别。基于集合体的概念认知,利用空间语义关系构建本体概念模型,提出了不同类型旅游资源集合体的空间边界提取方法。鉴于此,以海南岛为例进行实证研究,运用空间语义关系构建3种不同类型的旅游资源本体概念模型,在此基础上对不同类型旅游资源集合体进行条件约束判断,并利用泰森多边形与缓冲区分析方法对其进行空间识别。与规划范围结果对比发现,该方法可较好地近似表达旅游资源集合体空间边界及空间关系。每种类型的集合体空间语义关系存在树状层次结构,包含2个层次,空间形态呈多边形和带状分布。研究方法具有可操作性,能够为旅游规划与管理提供科学参考。     

Robust inferences of travel paths from GPS trajectories

Monitoring and predicting traffic conditions are of utmost importance in reacting to emergency events in time and for computing the real-time shortest travel-time path. Mobile sensors, such as GPS devices and smartphones, are useful for monitoring urban traffic due to their large coverage area and ease of deployment. Many researchers have employed such sensed data to model and predict traffic conditions. To do so, we first have to address the problem of associating GPS trajectories with the road network in a robust manner. Existing methods rely on point-by-point matching to map individual GPS points to a road segment. However, GPS data is imprecise due to noise in GPS signals. GPS coordinates can have errors of several meters and, therefore, direct mapping of individual points is error prone. Acknowledging that every GPS point is potentially noisy, we propose a radically different approach to overcome inaccuracy in GPS data. Instead of focusing on a point-by-point approach, our proposed method considers the set of relevant GPS points in a trajectory that can be mapped together to a road segment. This clustering approach gives us a macroscopic view of the GPS trajectories even under very noisy conditions. Our method clusters points based on the direction of movement as a spatial-linear cluster, ranks the possible route segments in the graph for each group, and searches for the best combination of segments as the overall path for the given set of GPS points. Through extensive experiments on both synthetic and real datasets, we demonstrate that, even with highly noisy GPS measurements, our proposed algorithm outperforms state-of-the-art methods in terms of both accuracy and computational cost.     

Analysis of Difference Between Direct and Geodetic Mass Balance Measurements at South Cascade Glacier, Washington

Net mass balance has been measured since 1958 at South Cascade Glacier using the 'direct method,' e.g. area averages of snow gain and firn and ice loss at stakes. Analysis of cartographic vertical photography has allowed measurement of mass balance using the 'geodetic method' in 1970, 1975, 1977, 1979–80, and 1985–97. Water equivalent change as measured by these nearly independent methods should give similar results. During 1970–97, the direct method shows a cumulative balance of about −15 m, and the geodetic method shows a cumulative balance of about −22 m. The deviation between the two methods is fairly consistent, suggesting no gross errors in either, but rather a cumulative systematic error. It is suspected that the cumulative error is in the direct method because the geodetic method is based on a non-changing reference, the bedrock control, whereas the direct method is measured with reference to only the previous year's summer surface. Possible sources of mass loss that are missing from the direct method are basal melt, internal melt, and ablation on crevasse walls. Possible systematic measurement errors include under-estimation of the density of lost material, sinking stakes, or poorly represented areas.     

适应自然灾害的研究方法进展

自然灾害损失虽然不可避免, 但可通过调整人类活动规避或减轻风险, 实现人类社会与自然灾害共存的协调适应。本文基于适应自然灾害研究发展的历程, 综述了现有适应性研究中的定性和定量研究方法。前者主要集中在对多尺度的适应主体综合分析、底层家庭或群体适应以及顶层的政策适应等方面;而后者主要集中在生态系统适应、民众或区域适应对策优选及适应能力评估等方面。基于数理模型或者实地观测实验的定量评估以及多指标、多标准的综合评估方法是适应自然灾害定量研究的主流。研究表明:①适应自然灾害研究有向综合性和精细化方向发展的趋势, 一些系统综合分析方法以及本地乡土的适应自然灾害逐渐引起重视。②目前适应自然灾害研究方法上存在自上而下与自下而上两种研究途径, 而探索这两种途径有效结合的多尺度综合研究方法是适应自然灾害研究的关键。     

A continuous deployment-based approach for the collaborative creation,maintenance, testing and deployment of CityGML models

Georeferenced 3D models are an increasingly common choice to store and display urban data in many application areas. CityGML is an open and standardized data model, and exchange format that provides common semantics for 3D city entities and their relations and one of the most common options for this kind of information. Currently, creating and maintaining CityGML models is costly and difficult. This is in part because both the creation of the geometries and the semantic annotation can be complex processes that require at least some manual work. In fact, many publicly available CityGML models have errors. This paper proposes a method to facilitate the regular maintenance of correct city models in CityGML. This method is based on the continuous deployment strategy and tools used in software development, but adapted to the problem of creating, maintaining and deploying CityGML models, even when several people are working on them at the same time. The method requires designing and implementing CityGML deployment pipelines. These pipelines are automatic implementations of the process of building, testing and deploying CityGML models. These pipelines must be run by the maintainers of the models when they make changes that are intended to be shared with others. The pipelines execute increasingly complex automatic tests in order to detect errors as soon as possible, and can even automate the deployment step, where the CityGML models are made available to their end users. In order to demonstrate the feasibility of this method, and as an example of its application, a CityGML deployment pipeline has been developed for an example scenario where three actors maintain the same city model. This scenario is representative of the kind of problems that this method intends to solve, and it is based on real work in progress. The main benefits of this method are the automation of model testing, every change to the model is tested in a repeatable way; the automation of the model deployment, every change to the model can reach its end users as fast as possible; the systematic approach to integrating changes made by different people working together on the models, including the possibility of keeping parallel versions with a common core; an automatic record of every change made to the models (who did what and when) and the possibility of undoing some of those changes at any time.     

Sensitivity analysis of a decision tree classification to input data errors using a general Monte Carlo error sensitivity model

We analysed the sensitivity of a decision tree derived forest type mapping to simulated data errors in input digital elevation model (DEM), geology and remotely sensed (Landsat Thematic Mapper) variables. We used a stochastic Monte Carlo simulation model coupled with a one‐at‐a‐time approach. The DEM error was assumed to be spatially autocorrelated with its magnitude being a percentage of the elevation value. The error of categorical geology data was assumed to be positional and limited to boundary areas. The Landsat data error was assumed to be spatially random following a Gaussian distribution. Each layer was perturbed using its error model with increasing levels of error, and the effect on the forest type mapping was assessed. The results of the three sensitivity analyses were markedly different, with the classification being most sensitive to the DEM error, than to the Landsat data errors, but with only a limited sensitivity to the geology data error used. A linear increase in error resulted in non‐linear increases in effect for the DEM and Landsat errors, while it was linear for geology. As an example, a DEM error of as small as ±2% reduced the overall test accuracy by more than 2%. More importantly, the same uncertainty level has caused nearly 10% of the study area to change its initial class assignment at each perturbation, on average. A spatial assessment of the sensitivities indicates that most of the pixel changes occurred within those forest classes expected to be more sensitive to data error. In addition to characterising the effect of errors on forest type mapping using decision trees, this study has demonstrated the generality of employing Monte Carlo analysis for the sensitivity and uncertainty analysis of categorical outputs that have distinctive characteristics from that of numerical outputs.     

Evaluation of the SNOWPACK model’s metamorphism and microstructure in Canada: a case study

The snow thermodynamic multi-layer model SNOWPACK was developed to address the risk of avalanches by simulating the vertical properties of snow. Risk and stability assessments are based on the simulation of the vertical variability of snow microstructure, as well as on snow cohesion parameters. Previous research has shown systematic error in grain size simulations (equivalent optical grain size) over several areas in northern Canada. To quantify the simulated errors in snow grain size and uncertainties in stability, the snow specific surface area (SSA) was measured with a laser-based instrument. Optical grain size was retrieved to validate the optical equivalent grain radius from SNOWPACK. The two study plots are located in Glacier National Park, BC, and Jasper National Park, AB, Canada. Profiles for density and stratigraphic analysis were obtained as well as grain size profiles, combined with snow micropenetrometer (SMP) measurements. Density analysis showed good agreement with the simulated values (R² = 0.76). Optical grain size analysis showed systematic overestimation of the modeled values, in agreement with the current literature. The error in SSA evolution for a rounding environment was mostly constant, whereas error for conditions driven by a temperature gradient was linked to the size of the facetted grains.     

基于互补相关原理的区域蒸散量估算模型比较

利用黄河流域1981~2000年期间的气象、水文资料,结合卫星遥感信息和数字高程模型,检验了平流-干旱、CRAE (Complementary Relationship Areal Evapotranspiration)、Granger等互补相关模型在不同时间尺度、不同气候类型区域上的计算精度,讨论了不同气候因子对计算误差的影响,并分析了模型参数的变化规律。结果表明：平流-干旱模型、CRAE和Granger模型估算的年蒸散量除了干旱年份外,误差都在10%以下。平流-干旱模型估算的月蒸散量比较合理,而CRAE模型与Granger模型都存在冬季月蒸散量估算过高的问题。平流-干旱模型与Granger模型的水量平衡闭合误差空间分布比较一致,计算效果是比较理想的,而CRAE模型的水量平衡闭合误差比较大。互补相关模型在湿润和干旱的条件下以及在可利用能量比较高和比较低的条件下,计算效果比较差。互补相关模型的经验参数在不同年型、不同气候类型区域有不同的最优值。     

基于混合光谱理论的太湖水体叶绿素a浓度提取

TM图象多波段数据作为遥感监测水体叶绿素a浓度的数据源,已有多种遥感定量模型与之对应,但主要还是以经验模型为主。利用TM数据首先采用特征波段比值方法,建立太湖水体合适的叶绿素a浓度反演的遥感定量模型。由于经验模型的缺陷性,还提出了基于TM数据的水体混合光谱分析模型,同时分析了端元光谱提取方法对模型求解的影响。通过计算叶绿素a浓度模型估算结果与实地测量数据的相关系数和均方根误差(RMSE),可以发现混合光谱分析模型也是水体叶绿素a浓度遥感估算的另一条佳径。     

Fidelity and time resolution of the magnetostratigraphic record in Siwalik sediments: high-resolution study of a complete polarity transition and evidence for cryptochrons in a Miocene fluviatile section

The Surai Khola section in southwest Nepal, a 5000 m continuously exposed record of fluvial sedimentation since Middle Miocene, was revisited for high-resolution magnetostratigraphy in sequences with expected cryptochrons and reversals of the geomagnetic field. Polarity intervals with durations of a few tens of thousands of years are recorded as zones of stable palaeomagnetic directions. Polarity transitions are recorded as zones with complex demagnetization behaviour of specimens in the sedimentary column. Almost antiparallel palaeoremanence directions, residing in different haematite phases in the same specimens, could generally not be separated properly by thermal demagnetization. Differing demagnetization paths for neighbouring specimens during a reversal suggest that measured transitional directions are not true geomagnetic field directions, but rather are generated by the superposition of variable amounts of at least two almost antiparallel components of magnetization. Accompanying studies of recent river sand deposits demonstrate that these sediments acquire a true depositional remanent magnetization (DRM) with considerable inclination errors and scattered directions for individual specimens.     

水文模型参数敏感性分析—优化—区域化方法研究进展

水文模型是认识水文科学规律、分析水文过程及研究水文循环机理的重要科学工具。水文模型模拟结果的不确定分析是提高模型可靠性、进行有效水情预报的一个重要研究内容。参数不确定性是影响水文模型模拟结果不确定性的关键因素之一,开展模型参数不确定性及其影响因素分析对水文预报具有重要现实意义。目前的参数不确定性分析方法大致可分为3类：参数敏感性分析、参数优化以及考虑无资料流域参数值估计的参数区域化方法。论文归纳总结了近年来国内外水文模型参数不确定性分析工作的主要研究进展,分析了不同方法的优点与不足,提出了未来水文模型不确定性分析方法研究的潜在发展方向。借助多学科理论和技术方法,加强水文模型不确定性分析系统性方法的研究,是水文学科当前的迫切需求及发展趋势。     

Evaluating Volumetric Glacier Change Methods Using Airborne Laser Scanning Data

Assessments of geodetic volume change are widely used in glaciology and have a long tradition dating back to the nineteenth century. Over time, the geodetic method and corresponding data storage have been developed further, but the resulting methodological heterogeneity can lead to errors that are difficult to separate from other survey uncertainties. In this study we used high‐resolution airborne laser scanning data from the Findelengletscher in the Swiss Alps to evaluate state‐of‐the‐art volumetric glacier change methods. For the first time we have been able to simulate errors arising from different geodetic methods and spatial resolutions. The evaluation showed that, although the digital elevation models were perfectly co‐registered, systematic and random method‐ and scale‐dependent errors still occurred. These errors have an impact on the resulting volume changes at lower spatial resolutions and may lead to exponentially larger uncertainties. Volume changes from contour methods provided reasonably accurate results, while volumetric change assessments from central profile lines were especially prone to biases at any scale.     

快速城镇化背景下建设用地扩展驱动力研究述评与展望

 快速城镇化及经济发展背景下,我国建设用地扩展特征明显,建设用地扩展驱动力研究可为政府制定土地利用管控策略提供依据。采用文献分析法、归纳法,对已有研究成果进行了综述,综合分析表明：已有研究存在理论体系不健全;驱动因子遴选缺乏科学性;尺度界定不清晰;数据获取口径不一,遥感数据与统计数据不匹配;研究方法存在一定缺陷等不足与弊端。从人类与环境相互作用的系统观视角出发,加强学科交流,构建完整理论体系框架;注重驱动因子遴选的整体性、层次性、动态性、差异性;构建揭示空间异质差异的非线性模型,创建对模型可靠性和科学性进行检验方法;将数学模型方法、数据库技术和3S技术结合起来,创新研究方法;规范数据获取口径;加强时空尺度的敏感性研究;建设用地扩展对自然、社会经济反馈机制等方面进行了展望,以期为建设用地扩展驱动力进一步研究提供借鉴。     

东莞地区土地利用变化预测的CBR和CA方法对比研究(英文)

Many studies on land use change(LUC),using different approaches and models,have yielded good results.Applications of these methods have revealed both advantages and limitations.However,LUC is a complex problem due to influences of many factors,and variations in policy and natural conditions.Hence,the characteristics and regional suitability of different methods require further research,and comparison of typical approaches is re-quired.Since the late 1980s,CA has been used to simulate urban growth,urban sprawl and land use evolution successfully.Nowadays it is very popular in resolving the LUC estimating problem.Case-based reasoning(CBR),as an artificial intelligence technology,has also been employed to study LUC by some researchers since the 2000s.More and more researchers used the CBR method in the study of LUC.The CA approach is a mathematical system con-structed from many typical simple components,which together are capable of simulating complex behavior,while CBR is a problem-oriented analysis method to solve geographic problems,particularly when the driving mechanisms of geographic processes are not yet understood fully.These two methods were completely different in the LUC research.Thus,in this paper,based on the enhanced CBR model,which is proposed in our previous research(Du et al.2009),a comparison between the CBR and CA approaches to assessing LUC is presented.LUC in Dongguan coastal region,China is investigated.Applications of the im-proved CBR and the cellular automata(CA) to the study area,produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR,and 70.7% accuracy from the CA.From the results,we can see that the accuracies of the CA and CBR approaches are both >70%.Although CA method has the distinct advantage in predicting the urban type,CBR method has the obvious tendency in predicting non-urban type.Considering the entire ana-lytical process,the preprocessing workload in CBR is less than that of the CA approach.As such,it could be concluded that the CBR approach is more flexible and practically useful than the CA approach for estimating land use change.     

Comparison of Methods Used to Estimate Conventional Undiscovered Petroleum Resources: World Examples

Various methods for assessing undiscovered oil, natural gas, and natural gas liquid resources were compared in support of the USGS World Petroleum Assessment 2000. Discovery process, linear fractal, parabolic fractal, engineering estimates, PETRIMES, Delphi, and the USGS 2000 methods were compared. Three comparisons of these methods were made in: (1) the Neuquen Basin province, Argentina (different assessors, same input data); (2) provinces in North Africa, Oman, and Yemen (same assessors, different methods); and (3) the Arabian Peninsula, Arabian (Persian) Gulf, and North Sea (different assessors, different methods). A fourth comparison (same assessors, same assessment methods but different geologic models), between results from structural and stratigraphic assessment units in the North Sea used only the USGS 2000 method, and hence compared the type of assessment unit rather than the method. In comparing methods, differences arise from inherent differences in assumptions regarding: (1) the underlying distribution of the parent field population (all fields, discovered and undiscovered), (2) the population of fields being estimated; that is, the entire parent distribution or the undiscovered resource distribution, (3) inclusion or exclusion of large outlier fields; (4) inclusion or exclusion of field (reserve) growth, (5) deterministic or probabilistic models, (6) data requirements, and (7) scale and time frame of the assessment. Discovery process, Delphi subjective consensus, and the USGS 2000 method yield comparable results because similar procedures are employed. In mature areas such as the Neuquen Basin province in Argentina, the linear and parabolic fractal and engineering methods were conservative compared to the other five methods and relative to new reserve additions there since 1995. The PETRIMES method gave the most optimistic estimates in the Neuquen Basin. In less mature areas, the linear fractal method yielded larger estimates relative to other methods. A geologically based model, such as one using the total petroleum system approach, is preferred in that it combines the elements of petroleum source, reservoir, trap and seal with the tectono-stratigraphic history of basin evolution with petroleum resource potential. Care must be taken to demonstrate that homogeneous populations in terms of geology, geologic risk, exploration, and discovery processes are used in the assessment process. The USGS 2000 method (7th Approximation Model, EMC computational program) is robust; that is, it can be used in both mature and immature areas, and provides comparable results when using different geologic models (e.g. stratigraphic or structural) with differing amounts of subdivisions, assessment units, within the total petroleum system.     

用非饱和土壤物理参数模拟坡面产流过程研究

采用人工模拟降雨方法，在用蒸发法测定非饱和土壤物理参数和基础上，运用修正的Green—Ampt入渗模型，结合退水曲线法和坡面运动波模型．研究了9场不同雨强和不同历时模拟降雨的产流过程。结果表明模拟误差在11．0％-30．7％间变化，80％的模：似误差可控制在18％以内，说明用非饱和土壤物理参数可以进行一般精度要求的坡面径流过程模拟。     

Extended hybrid meshing algorithm for multiresolution terrain models

Hybrid terrains are a convenient approach for the representation of digital terrain models, integrating heterogeneous data from different sources. In this article, we present a general, efficient scheme for achieving interactive level-of-detail rendering of hybrid terrain models, without the need for a costly preprocessing or resampling of the original data. The presented method works with hybrid digital terrains combining regular grid data and local high-resolution triangulated irregular networks. Since grid and triangulated irregular network data may belong to different datasets, a straightforward combination of both geometries would lead to meshes with holes and overlapping triangles. Our method generates a single multiresolution model integrating the different parts in a coherent way, by performing an adaptive tessellation of the region between their boundaries. Hence, our solution is one of the few existing approaches for integrating different multiresolution algorithms within the same terrain model, achieving a simple interactive rendering of complex hybrid terrains.