Developing a multi-scale visualisation framework for use in climate change response

Climate change is predicted to impact countries, regions and localities differently. However, common to the predicted impacts is a global trend toward increased levels of carbon dioxide and rising sea levels. Governments and communities need to take into account the likely impacts of climate on the landscape, both built and natural. There is a growing and significant body of climate change research. Much of this information produced by domain experts for a range of disciplines is complex and difficult for planners, decision makers and communities to act upon. The need to communicate often complex scientific information which can be used to assist in the planning cycle is a key challenge. This paper draws from a range of international examples of the use of visualisation in the context of landscape planning to communicate climate change impact and adaptation options within the context of the planning cycle. Missing from the literature, however, is a multi-scalar approach which allows decision makers, planners and communities to seamlessly explore scenarios at their special level of interest, as well as to collectively understand what is driving these at a larger scale, and what the implications are at ever more local levels. Visualisation tools such as digital globes provide one way to bring together multi-scaled spatial–temporal datasets. We present an initial development with this goal in mind. Future research is required to determine the best tools for communicating particular complex scientific data and also to better understand how visualisation can be used to improve the landscape planning process.

Assessing the ability of rural agrarian areas to provide Cultural Ecosystem Services (CES): a Multi Scale Social Indicator Framework (MSIF)

Assessing the ways in which rural agrarian areas provide Cultural Ecosystem Services (CES) is proving difficult to achieve. This research has developed an innovative methodological approach named as Multi Scale Indicator Framework (MSIF) for capturing the CES embedded into the rural agrarian areas. This framework reconciles a literature review with a trans-disciplinary participatory workshop. Both of these sources reveal that societal preferences diverge upon judgemental criteria which in turn relate to different visual concepts that can be drawn from analysing attributes, elements, features and characteristics of rural areas. We contend that it is now possible to list a group of possible multi scale indicators for stewardship, diversity and aesthetics. These results might also be of use for improving any existing European indicators frameworks by also including CES. This research carries major implications for policy at different levels of governance, as it makes possible to target and monitor policy instruments to the physical rural settings so that cultural dimensions are adequately considered. There is still work to be developed on regional specific values and thresholds for each criteria and its indicator set. In practical terms, by developing the conceptual design within a common framework as described in this paper, a considerable step forward towards the inclusion of the cultural dimension in European wide assessments can be made.

Assessing the ability of rural agrarian areas to provide cultural ecosystem services (CES): A multi scale social indicator framework (MSIF)

Assessing the ways in which rural agrarian areas provide Cultural Ecosystem Services (CES) is proving difficult to achieve. This research has developed an innovative methodological approach named as Multi Scale Indicator Framework (MSIF) for capturing the CES embedded into the rural agrarian areas. This framework reconciles a literature review with a transdisciplinary participatory workshop. Both of these sources reveal that societal preferences diverge upon judgemental criteria which in turn relate to different visual concepts that can be drawn from analyzing attributes, elements, features and characteristics of rural areas. We contend that it is now possible to list a group of possible multi scale indicators for stewardship, diversity and aesthetics. These results might also be of use for improving any existing European indicators frameworks by also including CES. This research carries major implications for policy at different levels of governance, as it makes possible to target and monitor policy instruments to the physical rural settings so that cultural dimensions are adequately considered. There is still work to be developed on regional specific values and thresholds for each criteria and its indicator set. In practical terms, by developing the conceptual design within a common framework as described in this paper, a considerable step forward toward the inclusion of the cultural dimension in European wide assessments can be made

内蒙古锡林河流域空间生态学研究

本文从物种和景观两个组织水平上研究了气候、土壤、地形等自然环境因子和人类活动因子对生物空间分布格局的影响。基于锡林河流域地理信息系统各环境因子的专题数据，利用空间异质性分析方法研究了锡林河流域环境因子的空间分布格局;基于锡林河流域野外调查数据，运用空间异质性分析方法研究了重要物种的空间分布格局，并采用典范对应分析(Canomc Correspondence Analvsis，CCA)方法分析了物种分布与环境因子的关系：基于锡林河流域地理信息系统各环境因子的专题数据，研究了锡林河流域植被斑块的空间格局特征及其与环境因子的关系，并采用典范对应分析方法分析了植被类型组成与环境因子的关系：基于内蒙古草原生态系统定位研究站放牧样地的样方调查数据．采用空间异质性分析方法，研究了放牧压力对物种空间分布格局的影响：基于多年的卫星遥感数据，采用建模和对比等方法，研究了定居放牧方式下植被状况空间变化规律及植被状况时空变化与人类活动、社会经济发展的关系。通过上述分析，得到的主要结论如下： 1、锡林河流域各个环境因子都具有自己的空间特征尺度，共同形成多尺度等级体系，按特征尺度的大小可以分为如下3个组： ·小尺度组(15km左右)：有机暖、全N的较小的特征尺度 ·中尺度组(30～50km)：T1，碳酸钙含量．PER、全N和海拔高度的较小的特征尺度 ·大尺度组(100km左右)：ANNR，PER、全N和海拔高度的较大的特征尺度多尺度等级的生态学意义是它反映生态变量异质斑块的镶嵌和包含特征，环境因子多尺度等级体系反映共性，具有普遍性：反映生态关系，具有生态学意义。 2、对物种空间异质性的Mantel检验和半方差分析得到了一致的结果产即羊草、糙隐子草和星毛萎菱菜在锡林河流域的空间分布呈现随机特征，而大针茅和冷蒿则表现为十分显著的格局特征。按分布格局的显著程度从大到小排列为冷蒿>大针茅>星毛萎菱菜>糙隐子草>羊草。理论半方差图显示大针茅和冷蒿的空间自相关域分别为30．447公里和30公里。物种空间分布格局是受自然条件、人类活动以及它们自身的生理生态特征综合决定的，物种自身的生理生态特征决定了它们对外界环境变化的适应性反应机制，而自然与人类活动这两种因素在空间的交错配置决定了物种适应性反应的方向和程度，从而综合导致物种空间分布格局的形成。 3、对锡林河流域物种分布与环境因子关系的CCA分析和交叉半方差方法分析显示：1)气候因子(11个指标)、土壤性状因子(3个指标)和地形因子(3个指标)对物种分布的贡献率分别为11．2％、9．5％和11％，三者总和为31．7％。2)各个环境因子对物种分布空间作用方向具有一致性，物种分布与环境因子几乎都在135。和157．5。两个方向上具有相对明显的相关性，从锡林河流域来看，这两个方向反映了气候、土壤以及地形从东南往西北的变化梯度方向。 4、对锡林河流域14个植被景观指数进行的PCA分析表明，锡林河流域植被斑块空间分布的物理特征主要表现在斑块的数目和大小方面，其次是在斑块的多样性方面，并可将它们分为4个组，分别反映锡林河流域植被斑块的不同特征： ·第一组：NP、PRD、LPI、MPS、PSSD和TE，主要反映景观斑块在数量和大小方面的特征; ·第二组：SHDI、SIDI、SHEI和SIEI，主要反映景观斑块的多样性特征; ·第三组：PSCV和[J]．主要反映景观斑块之间的相互邻接程度; ·第四组：MSI和AWMSI，主要反映景观斑块的形状特征。 MPS和PSSD两个指数与环境因子无论是在相关系数的性质还是显著程度上都保持了很好的一致性，它们与纬度(LAT)及可能蒸散率(PER)呈极显著的正相关关系，而与经度(LNG)、海拔高度(ALT)、年平均降水量(ANNR)及土壤有机质含量(0RG)呈极显著的负相关关系：平均形状指数(MSI)只与LAT呈显著的正相关关系;多样性指数和扩散毗连指数与任何一个环境因子都没有表现出显著的相关性。 5、锡林河流域植被分布与环境因子的关系CCA排序方法分析表明，气候因子(11个指标)、土壤性状因子(3个指标)和地形因子(3个指标)对植被分布的贡献率分别为19.8%、11.1%和14.5%，三者总和为45.4％。环境因子在植被和物种两个水平上的贡献率表现了相似的特点，自然环境因子不能完全解释植被的空间分布，人类活动的影响应该受到重视。 6、放牧压力对物种空间分布格局的研究表明： ·牧压对温带典型草原物种的空间分布格局有明显的影响。随着牧云的增大，属于原生群落物种的羊草与大针茅空间分布的随机性减小，空间自相关尺度逐渐增大;而对于退化过程中的入侵物种冷蒿和星毛萎菱菜，其空间分布的随机性逐渐增大．空间自相关尺度也呈增大趋势。在牧压胁迫超过一定水平时，冷蒿空间分布的自相关尺度开始下降，而星毛萎菱菜的空间分布格局则表现出强烈的随机性。 ·物种空间格局的变化是反映群落演替过程较为稳定的特征，适用于不同放牧条件下 群落之间的比较。 7、利用遥感数据对人类活动对植被影响的研究表明： ·定居放牧方式下，NDVI随定居点距离的变化格局经历了3个阶段。第一阶段，草场处于原生阶段，NDVI不随距离变化;第二阶段，定居点附近开始局部退化，NDVI随距离增加而增大：第三阶段，退化区域扩大，NDVI不随距离变化。 ·在草场局部退化阶段，NDVI随距离的变化呈对数函数规律，定居点的放牧区具有放牧半径、原生NDVI值、NDVI变化率等特征。根据这些特征、NDVI对数规律以及NDVI与地上生物量的关系可以推测定居点的总载畜量。 ·锡林河流域从87年到85年NDVI值降低最大的区域为流域的中部和南部，这与这一区域人类活动强度以及社会经济发展具有密切关系。

A new perspective on service quality: A multi-dimensional, hierarchical scale

This study offers a new perspective on the nature, content and structure of perceived service quality. The Nordic and Gap schools of quality assessment are integrated with recent advances in the literature to develop and test a multidimensional, hierarchical scale. The scale provides a framework for assessing service quality within a high involvement, high contact, ongoing service environment. Empirical results indicated that service quality conforms to a multidimensional, hierarchical structure consisting of four primary dimensions, which in turn comprise nine sub-dimensions. The results obtained extend our understanding of service evaluation and have important implications for service providers seeking to improve the quality of the services they provide.

Multi-scale bio-inspired place recognition

This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

Multi-scale cortical keypoints for realtime hand tracking and gesture recognition

Human-robot interaction is an interdisciplinary research area which aims at integrating human factors, cognitive psychology and robot technology. The ultimate goal is the development of social robots. These robots are expected to work in human environments, and to understand behavior of persons through gestures and body movements. In this paper we present a biological and realtime framework for detecting and tracking hands. This framework is based on keypoints extracted from cortical V1 end-stopped cells. Detected keypoints and the cells’ responses are used to classify the junction type. By combining annotated keypoints in a hierarchical, multi-scale tree structure, moving and deformable hands can be segregated, their movements can be obtained, and they can be tracked over time. By using hand templates with keypoints at only two scales, a hand’s gestures can be recognized.

A multi-scale framework for strategic management of diffuse pollution

A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.

Hydrangea-like multi-scale carbon hollow submicron spheres with hierarchical pores for high performance supercapacitor electrodes

Uniform hydrangea-like multi-scale carbon hollow submicron spheres (HCSSg) are fabricated by a simple hydrothermal method using glucose as carbon source and fibrous silicon dioxides spheres as shape guide. Structure characterization suggests that petal-like partially graphitized carbon nanosheets with the thickness of about 10 nm arranged in three dimensions (3D) to form the hydrangea-like hollow spheres (size ranging from 250 to 500 nm) with mesoporous channels, which can be conducive to be a high specific surface area (934 m2 g-1) and bulk density (0.87 cm g-3), hierarchical pores structure with good conductivity. As a result, the HCSSg has been demonstrated to be a supercapacitor electrode material with high gravimetric (386 F g-1 at 0.2 A g-1) and outstanding volumetric (335 F cm-3) capacitance, good rate capability and cycling stability with 94% capacitance retention after 5000 cycles in aqueous electrolytes, thus suggesting its application potential.

First steps towards modeling a multi-scale Earth system

Recent advances in computational geodynamics are applied to explore the link between Earth’s heat, its chemistry and its mechanical behavior. Computational thermal-mechanical solutions are now allowing us to understand Earth patterns by solving the basic physics of heat transfer. This approach is currently used to solve basic convection patterns of terrestrial planets. Applying the same methodology to smaller scales delivers promising similarities between observed and predicted structures which are often the site of mineral deposits. The new approach involves a fully coupled solution to the energy, momentum and continuity equations of the system at all scales, allowing the prediction of fractures, shear zones and other typical geological patterns out of a randomly perturbed initial state. The results of this approach are linking a global geodynamic mechanical framework over regional-scale mineral deposits down to the underlying micro-scale processes. Ongoing work includes the challenge of incorporating chemistry into the formulation.

Entropic bounds for multi-scale and multi-physics coupling in earth sciences

The ability to understand and predict how thermal, hydrological,mechanical and chemical (THMC) processes interact is fundamental to many research initiatives and industrial applications. We present (1) a new Thermal– Hydrological–Mechanical–Chemical (THMC) coupling formulation, based on non-equilibrium thermodynamics; (2) show how THMC feedback is incorporated in the thermodynamic approach; (3) suggest a unifying thermodynamic framework for multi-scaling; and (4) formulate a new rationale for assessing upper and lower bounds of dissipation for THMC processes. The technique is based on deducing time and length scales suitable for separating processes using a macroscopic finite time thermodynamic approach. We show that if the time and length scales are suitably chosen, the calculation of entropic bounds can be used to describe three different types of material and process uncertainties: geometric uncertainties,stemming from the microstructure; process uncertainty, stemming from the correct derivation of the constitutive behavior; and uncertainties in time evolution, stemming from the path dependence of the time integration of the irreversible entropy production. Although the approach is specifically formulated here for THMC coupling we suggest that it has a much broader applicability. In a general sense it consists of finding the entropic bounds of the dissipation defined by the product of thermodynamic force times thermodynamic flux which in material sciences corresponds to generalized stress and generalized strain rates, respectively.

Management of multi-scale forest resource data over time

During the last decades there has been a global shift in forest management from a focus solely on timber management to ecosystem management that endorses all aspects of forest functions: ecological, economic and social. This has resulted in a shift in paradigm from sustained yield to sustained diversity of values, goods and benefits obtained at the same time, introducing new temporal and spatial scales into forest resource management. The purpose of the present dissertation was to develop methods that would enable spatial and temporal scales to be introduced into the storage, processing, access and utilization of forest resource data. The methods developed are based on a conceptual view of a forest as a hierarchically nested collection of objects that can have a dynamically changing set of attributes. The temporal aspect of the methods consists of lifetime management for the objects and their attributes and of a temporal succession linking the objects together. Development of the forest resource data processing method concentrated on the extensibility and configurability of the data content and model calculations, allowing for a diverse set of processing operations to be executed using the same framework. The contribution of this dissertation to the utilisation of multi-scale forest resource data lies in the development of a reference data generation method to support forest inventory methods in approaching single-tree resolution.