970 resultados para Spatial visualization ability
Resumo:
The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.
Resumo:
Most countries of Europe, as well as many countries in other parts of the world, are experiencing an increased impact of natural hazards. It is often speculated, but not yet proven, that climate change might influence the frequency and magnitude of certain hydro-meteorological natural hazards. What has certainly been observed is a sharp increase in financial losses caused by natural hazards worldwide. Eventhough Europe appears to be a space that is not affected by natural hazards to such catastrophic extents as other parts of the world are, the damages experienced here are certainly increasing too. Natural hazards, climate change and, in particular, risks have therefore recently been put high on the political agenda of the EU. In the search for appropriate instruments for mitigating impacts of natural hazards and climate change, as well as risks, the integration of these factors into spatial planning practices is constantly receiving higher attention. The focus of most approaches lies on single hazards and climate change mitigation strategies. The current paradigm shift of climate change mitigation to adaptation is used as a basis to draw conclusions and recommendations on what concepts could be further incorporated into spatial planning practices. Especially multi-hazard approaches are discussed as an important approach that should be developed further. One focal point is the definition and applicability of the terms natural hazard, vulnerability and risk in spatial planning practices. Especially vulnerability and risk concepts are so many-fold and complicated that their application in spatial planning has to be analysed most carefully. The PhD thesis is based on six published articles that describe the results of European research projects, which have elaborated strategies and tools for integrated communication and assessment practices on natural hazards and climate change impacts. The papers describe approaches on local, regional and European level, both from theoretical and practical perspectives. Based on these, passed, current and future potential spatial planning applications are reviewed and discussed. In conclusion it is recommended to shift from single hazard assessments to multi-hazard approaches, integrating potential climate change impacts. Vulnerability concepts should play a stronger role than present, and adaptation to natural hazards and climate change should be more emphasized in relation to mitigation. It is outlined that the integration of risk concepts in planning is rather complicated and would need very careful assessment to ensure applicability. Future spatial planning practices should also consider to be more interdisciplinary, i.e. to integrate as many stakeholders and experts as possible to ensure the sustainability of investments.
Resumo:
Determination of the environmental factors controlling earth surface processes and landform patterns is one of the central themes in physical geography. However, the identification of the main drivers of the geomorphological phenomena is often challenging. Novel spatial analysis and modelling methods could provide new insights into the process-environment relationships. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, field observations and the results of HP analyses. A total of 40 different landform types and subtypes were identified. Topographical, soil property and vegetation variables were the primary correlates for the occurrence and cover of active periglacial landforms on the landscape scale. In the model evaluation, most of the GLMs were shown to be robust although the explanation power, prediction ability as well as the selected explanatory variables varied between the models. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and significances of the environmental variables and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical approach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena.
Resumo:
This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.
Resumo:
Cabomba caroliniana is a submersed macrophyte that has become a serious invader. Cabomba predominantly spreads by stem fragments, in particular through unintentional transport on boat trailers ('hitch hiking'). Desiccation resistance affects the potential dispersal radius. Therefore, knowledge of maximum survival times allows predicting future dispersal. Experiments were conducted to assess desiccation resistance and survival ability of cabomba fragments under various environmental scenarios. Cabomba fragments were highly tolerant of desiccation. However, even relatively low wind speeds resulted in rapid mass loss, indicating a low survival rate of fragments exposed to air currents, such as fragments transported on a boat trailer. The experiments indicated that cabomba could survive at least 3 h of overland transport if exposed to wind. However, even small clumps of cabomba could potentially survive up to 42 h. Thus, targeting the transport of clumps of macrophytes should receive high priority in management. The high resilience of cabomba to desiccation demonstrates the risk of continuing spread. Because of the high probability of fragment viability on arrival, preventing fragment uptake on boat trailers is paramount to reduce the risk of further spread. These findings will assist improving models that predict the spread of aquatic invasive macrophytes.
Resumo:
Individual movement is very versatile and inevitable in ecology. In this thesis, I investigate two kinds of movement body condition dependent dispersal and small-range foraging movements resulting in quasi-local competition and their causes and consequences on the individual, population and metapopulation level. Body condition dependent dispersal is a widely evident but barely understood phenomenon. In nature, diverse relationships between body condition and dispersal are observed. I develop the first models that study the evolution of dispersal strategies that depend on individual body condition. In a patchy environment where patches differ in environmental conditions, individuals born in rich (e.g. nutritious) patches are on average stronger than their conspecifics that are born in poorer patches. Body condition (strength) determines competitive ability such that stronger individuals win competition with higher probability than weak individuals. Individuals compete for patches such that kin competition selects for dispersal. I determine the evolutionarily stable strategy (ESS) for different ecological scenarios. My models offer explanations for both dispersal of strong individuals and dispersal of weak individuals. Moreover, I find that within-family dispersal behaviour is not always reflected on the population level. This supports the fact that no consistent pattern is detected in data on body condition dependent dispersal. It also encourages the refining of empirical investigations. Quasi-local competition defines interactions between adjacent populations where one population negatively affects the growth of the other population. I model a metapopulation in a homogeneous environment where adults of different subpopulations compete for resources by spending part of their foraging time in the neighbouring patches, while their juveniles only feed on the resource in their natal patch. I show that spatial patterns (different population densities in the patches) are stable only if one age class depletes the resource very much but mainly the other age group depends on it.
Resumo:
Cabomba caroliniana is a submersed macrophyte that has become a serious invader. Cabomba predominantly spreads by stem fragments, in particular through unintentional transport on boat trailers (‘hitch hiking’). Desiccation resistance affects the potential dispersal radius. Therefore, knowledge of maximum survival times allows predicting future dispersal. Experiments were conducted to assess desiccation resistance and survival ability of cabomba fragments under various environmental scenarios. Cabomba fragments were highly tolerant of desiccation. However, even relatively low wind speeds resulted in rapid mass loss, indicating a low survival rate of fragments exposed to air currents, such as fragments transported on a boat trailer. The experiments indicated that cabomba could survive at least 3 h of overland transport if exposed to wind. However, even small clumps of cabomba could potentially survive up to 42 h. Thus, targeting the transport of clumps of macrophytes should receive high priority in management. The high resilience of cabomba to desiccation demonstrates the risk of continuing spread. Because of the high probability of fragment viability on arrival, preventing fragment uptake on boat trailers is paramount to reduce the risk of further spread. These findings will assist improving models that predict the spread of aquatic invasive macrophytes.
Resumo:
Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health and other fields, policy or decision makers, health geographers, spatial analysts, public health professionals, and epidemiologists.
Resumo:
Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957–2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20 through (i) reduced frost damage (~10 improvement) and (ii) the ability to use earlier sowing dates (adding a further 10 improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates.
Resumo:
Information visualization is a process of constructing a visual presentation of abstract quantitative data. The characteristics of visual perception enable humans to recognize patterns, trends and anomalies inherent in the data with little effort in a visual display. Such properties of the data are likely to be missed in a purely text-based presentation. Visualizations are therefore widely used in contemporary business decision support systems. Visual user interfaces called dashboards are tools for reporting the status of a company and its business environment to facilitate business intelligence (BI) and performance management activities. In this study, we examine the research on the principles of human visual perception and information visualization as well as the application of visualization in a business decision support system. A review of current BI software products reveals that the visualizations included in them are often quite ineffective in communicating important information. Based on the principles of visual perception and information visualization, we summarize a set of design guidelines for creating effective visual reporting interfaces.
Resumo:
A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.
Resumo:
This paper examines the 2013 Australian federal election to test two competing models of vote choice: spatial politics and valence issues. Using data from the 2013 Australian Election Study, the analysis finds that spatial politics (measured by party identification and self-placement on the left-right spectrum) and valence issues both have significant effects on vote choice. However, spatial measures are more important than valence issues in explaining vote choice, in contrast with recent studies from Britain, Canada and the United States. Explanations for these differences are speculative, but may relate to Australia’s stable party and electoral system, including compulsory voting and the frequency of elections. The consequently high information burden faced by Australian voters may lead to a greater reliance on spatial heuristics than is found elsewhere.