模型驱动数据空间分辨率对模拟生态水文过程的影响

设定两种独立的调参方案,检验将高/低分辨率下的调参值应用到低/高分辨率中驱动模型模拟的可行性;同时分析驱动数据分辨率的差异对模型模拟生态水文过程的影响;此外,设置9种集水面积阈值,分析驱动数据分辨率与集水面积阈值对模拟结果的影响。结果表明两种调参方案下模拟的水文与生态数据相关性强、差异小,说明调参方案受驱动数据分辨率的影响不明显;分辨率对土地覆被和土壤类型面积影响小,而对高程和坡度影响大;驱动数据分辨率降低,模拟径流的均值减小、峰值增大、生态变量值增大;驱动数据分辨与集水面积阈值之间不存在交互作用;集水面积阈值增大,模拟径流的均值、峰值均减小,生态变量值也减小,但阈值变化对峰现时间无影响。     

Validation of WRF model on simulating forcing data for Heihe River Basin

The research of coupling WRF (Weather Research and Forecasting Model) with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA (China Meteorological Administration) and hourly meteorological observation data from seven sites of WATER (Watershed Airborne Telemetry Experimental Research) are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE (Mean Bias Error) of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were ?0.19 °C, ?4.49 hPa, 4.08% and 0.92 m/s, the average RMSE (Root Mean Square Error) of them were 2.11 °C, 5.37 hPa, 9.55% and 1.73 m/s, and the average R (correlation coefficient) of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were ?0.16 °C, ?6.62 hPa, ?5.14%, 0.26 m/s, 33.0 W/m² and ?6.44 W/m², the average RMSE of them were 2.62 °C, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m² and 53.5 W/m², and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained: (1) regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; (2) the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; (3) both wind speed and rainfall simulated from WRF model did not agree well with observation data.     

A data model for moving regions of fixed shape in databases

Moving object databases are designed to store and process spatial and temporal object data. An especially useful moving object type is a moving region, which consists of one or more moving polygons suitable for modeling the spread of forest fires, the movement of clouds, spread of diseases and many other real-world phenomena. Previous implementations usually allow a changing shape of the region during the movement; however, the necessary restrictions on this model result in an inaccurate interpolation of rotating objects. In this paper, we present an alternative approach for moving and rotating regions of fixed shape, called Fixed Moving Regions, which provide a significantly better model for a wide range of applications like modeling the movement of oil tankers, icebergs and other rigid structures. Furthermore, we describe and implement several useful operations on this new object type to enable a database system to solve many real-world problems, as for example collision tests, projections and intersections, much more accurate than with other models. Based on this research, we also implemented a library for easy integration into moving objects database systems, as for example the DBMS Secondo (1) (2) developed at the FernUniversität in Hagen.     

Providing spatial statistical data analysis functionality for the GIS user: the SAGE project

Geographic representation has become more complex through time as researchers have added new concepts, leading to apparently endless proliferation and creating a need for simplification. We show that many of these concepts can be derived from a single foundation that we term the atomic form of geographic information. The familiar concepts of continuous fields and discrete objects can be derived under suitable rules applied to the properties and values of the atomic form. Fields and objects are further integrated through the concept of phase space, and in the form of field objects. A second atomic concept is introduced, termed the geo‐dipole, and shown to provide a foundation for object fields, metamaps, and the association classes of object‐oriented data modelling. Geographic dynamics are synthesized in a three‐dimensional space defined by static or dynamic object shape, the possibility of movement, and the possibility of dynamic internal structure. The atomic form also provides a tentative argument that discrete objects and continuous fields are the only possible bases for geographic representation.     

遥感分景数据的剖分索引模型

随着空间技术和对地观测技术的飞速发展,海量遥感影像索引成为目前国内外学术界和应用部门面临的一大难题,地球剖分系统的产生为这一难题的解决开辟了新的途径。本文首先研究了遥感分景数据的特征和EMD全球剖分的特征,然后针对现有遥感影像数据索引方法的不足,提出了基于EMD剖分系统的三种索引模型:基于影像—面片映射关系的索引模型、基于EMD数据模型的索引和剖分数据标识索引模型,从三个不同的方面探讨了解决索引问题的方法和思路。并给出了利用遥感分景数据的剖分索引模型对线状对象和面状对象进行索引应用的实例。遥感分景数据的剖分索引模型的建立为遥感影像数据的高效存储和索引提供了一种有益的新思路。     

GIScience for a driverless age

A driverless or autonomous vehicle requires significant support from information technology, both from central databases and from local sensors. The requirements for route guidance are in many ways more demanding than those of current guidance technologies, especially in the ‘last mile’ of a route. Significant extensions are needed for both street-centerline and point-of-interest databases. How these should be captured and structured present significant research challenges for GIScience. The societal and longer term impacts of such extensions are perhaps even more in need of focused research by the GIScience community.     

A GIS data model for landmark-based pedestrian navigation

Landmarks provide the most predominant navigation cue for pedestrian navigation. Very few navigation data models in the geographical information science and transportation communities support modeling of landmarks and use of landmark-based route instructions for pedestrian navigation services. This article proposes a landmark-based pedestrian navigation data model to fill this gap. This data model can model landmarks in several pedestrian navigation scenarios (buildings, open spaces, multimodal transportation systems, and urban streets). This article implements the proposed model in the ArcGIS software environment and demonstrates two typical pedestrian navigation scenarios: (1) a multimodal pedestrian navigation environment involving bus lines, parks, and indoor spaces and (2) a subway system in a metropolitan environment. These two scenarios illustrate the feasibility of the proposed data model in real-world environments. Further improvements of this model could lead to more intuitive and user-friendly landmark-based pedestrian navigation services than the functions supported by current map-based navigation systems.     

A data model and algorithms for a spatial data marketplace

A data marketplace is a platform that facilitates online data trading. It gives sellers the capabilities of publishing data, defining the price function, the authorization rules and the data contract. It gives customers the capabilities to search for data services, to query for their price, to invoke them and to pay for the usage. As data are more and more emphasized as a payable asset, the need for data marketplaces rises. There is a lack of marketplace proposals for spatial data. This paper contributes to fill-in this gap. We propose a data model for representing the different types of data involved. The logical representation of data is a quadtree, and the physical representation fits into a key-value store. The model is thus logically simple and extensible, and physically scalable and highly available. We discuss price queries in detail and propose evaluation algorithms.     

An initial formal model for spatial data infrastructures

The Commission on Spatial Data Standards of the International Cartographic Association is working to define formal models and technical characteristics of Spatial Data Infrastructures (SDI). To date, this work has been restricted to the Enterprise and Information Viewpoints from the ISO Reference Model for Open Distributed Processing standard. The Commission has developed models for these two viewpoints. These models describe how the different parts of an SDI fit together in the viewpoints in question. These models should be seen as a contribution towards the overall model of the SDI and its technical characteristics. During the model development process, the roles of the different Actors in an SDI in the Enterprise and Information Viewpoints have also been identified in Use Case diagrams of an SDI. All the models have been developed using the Unified Modeling Language.     

基于DEM的水文物理过程模拟

基于数字高程模型,考虑流域空间的变异性,建立数字高程流域水系模型。产流子单元的划分、河网水系的生成及其空间拓扑关系的建立,是由计算机自动完成。计算TOPMODEL地形指数ln(a/tgβ)_i的空间累积分布曲线,并对其作无量纲化处理,推求各产流子单元的土壤蓄水容量分布抛物线参数B,构建数字水文模型。全球能量与水循环亚洲季风试验强化观测区—淮河史灌河流域实例研究表明:数字模型不仅可以很好地模拟流域出口断面的径流过程,而且能够模拟土壤水分的变化过程,还可十分方便地输出水文要素和状态变量的空间分布。这对充分利用现有观测信息进行水文数据的深层次挖掘奠定了基础。     

A context-sensitive correlated random walk: a new simulation model for movement

Computational Movement Analysis focuses on the characterization of the trajectory of individuals across space and time. Various analytic techniques, including but not limited to random walks, Brownian motion models, and step selection functions have been used for modeling movement. These fall under the rubric of signal models which are divided into deterministic and stochastic models. The difficulty of applying these models to the movement of dynamic objects (e.g. animals, humans, vehicles) is that the spatiotemporal signal produced by their trajectories a complex composite that is influenced by the Geography through which they move (i.e. the network or the physiography of the terrain), their behavioral state (i.e. hungry, going to work, shopping, tourism, etc.), and their interactions with other individuals. This signal reflects multiple scales of behavior from the local choices to the global objectives that drive movement. In this research, we propose a stochastic simulation model that incorporates contextual factors (i.e. environmental conditions) that affect local choices along its movement trajectory. We show how actual global positioning systems observations can be used to parameterize movement and validate movement models and argue that incorporating context is essential in modeling movement.     

Displacement fields and finite strains in a sandbox model simulating a fold-thrust-belt

A sandbox model consisting of two adjacent mechanically different decollements (frictional and viscous) loosely simulated the southeastern part of the Zagros fold-thrust-belt. Digital images of the model surface are used to coordinate passive markers on the surface and quantify displacement fields and estimate 2-D finite strains. These analyses show that, mapped in a fixed coordinate system, the deformation front propagates at different rates above the two decollements. Strain analysis of the model surface at different stages of deformation also shows that cumulative strain is more heterogeneous above the viscous decollement where strain domains are separated by fault zones. Maps of displacement fields, finite strain ellipses and dilatation also differ in character above the two decollements. Displacements above a viscous decollement decrease gradually towards the foreland, whereas they decrease sharply in front of the frontal thrust above the frictional decollement. Our analyses also show that the estimated finite strain depends not only on the density of the marker points chosen for the analysis, but also their initial distribution relative to the structures. This comparison shows that marker density limits measuring the actual strains in a heterogeneously deforming fold-thrust-belt and marker density and distribution have a strong impact on the strain analysed in nature. The similarity of our model with nature is examined with recent GPS study in the Zagros fold-thrust-belt (SW Iran) and shows, similar to the model results, that a weak salt decollement causes divergent movement in the sedimentary cover in SE Zagros.     

Spatiotemporal data model for network time geographic analysis in the era of big data

There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities.     

Enabling smart data selection based on data completeness measures: a quality-aware approach

Geographic information system (GIS) users rely heavily on the versatile operations of GIS software and the abundant variety of geospatial data from different resources to satisfy their application requirements. However, the convenient use of GIS software has resulted in users easily ignoring the threat of data misuse because of the lack of understanding of data quality. Here we argue that data quality considerations must be coherently assimilated into the GIS operation design to visually present helpful information and ensure the accuracy of data for decision making. Data completeness is selected in this paper to demonstrate how the use of data quality information opens a new dimension to the design of future GIS software. We propose a new model for the representation, analysis, and visualization of data completeness information. With the brand new quantitative measures and informative visual approach, understanding of the data completeness of the illustrated contents in the map interface is enhanced, and inappropriate dataset selection can be effectively prevented. Thus, this paper presents an innovative, integrated and geospatial concept of future GIS operation design, where users are constantly aware of the continuously changing status of data quality based on formalized and quantitative data quality theories.     

The use of surface monitoring data for the interpretation of landslide movement patterns

The Tessina landslide is a large, seasonally active slope failure located on the southern slopes of Mt. Teverone, in the Alpago valley of NE Italy, consisting of a complex system that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, threatens two villages and is hence subject to detailed monitoring, with high quality data being collected using piezometers, inclinometers, extensometers, and through the use of a highly innovative, automated Electronic Distance Measurement (EDM) system, which surveys the location of a large number of reflector targets once every 6 h. These systems form the basis of a warning system that protects the villages, but they also provide a very valuable insight into the patterns of movement of the landslide.In this paper, analysis is presented of the movement of the landslide, concentrating on the EDM dataset, which provides a remarkable record of surface displacement patterns. It is proposed that four distinct movement patterns can be established, which correspond closely to independently defined morphological assessments of the landslide complex. Any given block of material transitions through the four phases of movement as it progresses down the landslide, with the style of movement being controlled primarily by the groundwater conditions. The analysis is augmented with modelling of the landslide, undertaken using the Itasca FLAC code. The modelling suggests that different landslide patterns are observed for different parts of the landslide, primarily as a result of variations in the groundwater conditions. The model suggests that when a movement event occurs, displacements occur initially at the toe of the landslide, then retrogress upslope.     

MODIS雪深反演数学模型验证及分析

在MODIS卫星遥感积雪监测的基础上,利用雪深反演数学模型、积雪指数NDSI和多光谱阈值等相结合的方法,对2004年以来新疆北疆地区的积雪分布状况进行了反演和计算,并利用2004年11月～2005年3月冬季北疆地区气象台站雪深数据和2004年12月～2006年1月加密野外实测雪深数据,对反演雪深数据进行了验证及分析,北疆各地除塔城地区反演精度为83.2%以外,其它地区反演精度达85.2%以上,平均反演精度达86.2%;野外实测数据验证反演精度达92%以上。     

Self-modifying CA model using dual ensemble Kalman filter for simulating urban land-use changes

There are many different methods to calibrate cellular automata (CA) models for better simulation results of urban land-use changes. However, few studies have been reported on combination of parameter update and error control using local data in CA calibration procedures. This paper presents a self-modifying CA model (SM-CA) that uses the dual ensemble Kalman filter (dual EnKF), which enables the CA model to simultaneously update model parameters and simulation results by merging observation data (local data). We applied the proposed model to simulate urban land-use changes in a 13-year period (1993–2005) in Dongguan City, a rapidly urbanizing region in south China. Simulation results indicate that this model yields better simulation results than the conventional logistic-regression CA and decision-tree CA models. For example, the validation is carried out using cross-tabulation matrix. The simulation results of SM-CA have allocation disagreement of 10.18%, 19.64%, and 30.03% in 1997, 2001, and 2005, respectively, which are 2.12%, 2.47%, and 6% lower than conventional logistic-regression CA models.     

A new nutation series for a more realistic model earth

The frequency-dependent correction coefficients with respect to the forced nutations of a rigid earth are computed using the complex scalar gravitational-motion equations for an earth model with an anelastic mantle. Oceanic loads and tidal currents enter the model via outer boundary conditions. The ellipticity of the core-mantle boundary and the dynamical ellipticity are adjusted to observations. This requires the behaviour inside the model earth to be regarded as non-hydrostatic. Some relevant equations for the evaluation of boundary conditions and some terms in the equations of motion are expanded to second order in ellipticity. The computation of the equipotential-surface ellipticity profile is carried to second order as well. These second-order expansions lead to increased accuracy of the results in general. Moreover, one achieves a better reliability for the integration at frequencies close to a resonance. This allows the integration of the equations of motion at any relevant nutation period without the need for a normal-mode expansion. A complete new nutation series for a realistic model earth is presented.