Representation Of Spatial Variation Research Articles

Towards mapping soil carbon landscapes: Issues of sampling scale and transferability

The conversion of point observations to a geographic field is a necessary step in soil mapping. For pursuing goals of mapping soil carbon at the landscape scale, the relationships between sampling scale, representation of spatial variation, and accuracy of estimated error need to be considered. This study examines the spatial patterns and accuracy of predictions made by different spatial modelling methods on sample sets taken at two different scales. These spatial models are then tested on independent validation sets taken at three different scales. Each spatial modelling method produced similar, but unique, maps of soil organic carbon content (SOC%). Kriging approaches excelled at internal spatial prediction with more densely spaced sample points. Because kriging depends on spatial autocorrelation, kriging performance was naturally poor in areas of spatial extrapolation. In contrast, the spatial regression approaches tested could continue to perform well in spatial extrapolation areas. However, the problem of induction allowed the potential for problems in some areas, which was less predictable. This problem also existed for the kriging approaches. Spatial phenomena occurring between sampling points could also be missed by kriging models. Use of covariates with kriging can help, but the requirement of capturing the full feature space in the map remains. Methods that utilize spatial association, such as spatial regression, can map soil properties for landscape scales at a high resolution, but are highly dependent on the inclusion of the full attribute space in the calibration of the model and the availability of transferable covariates.

Simplified Model for Simulating Basin-Scale Surface Runoff Hydrographs

A simplified model for estimating the hydrologic response to rainfall events at basin scale is developed in this study. It involves an abstraction of the real basin geometry based on networks of planes and channels and three semianalytical components that give the expected areal-average infiltration rate at field scale, the surface runoff hydrograph as lateral inflow into the channel network, and the water flow routing through the channel network. The model was tested by comparison with Monte Carlo simulations that relied on a detailed representation of spatial variation of excess rainfall and numerical solutions of water routing through planes and channels. The peak flow and the shape of the hydrographs were generally well reproduced. The results were less accurate for cases involving low volumes of effective rainfall, but these are of less importance in hydrologic practice. In spite of the complexity of the processes represented, such as the spatial heterogeneity of soil saturated hydraulic conductivity and rainfall rate as random variables over each subwatershed, the model requires a low computational effort that makes it suitable for application at all levels of spatial discretization.

Biological Monitoring in the Amazon: Recent Progress and Future Needs

RESUMENO monitoramento biológico é uma ferramenta fundamental para o manejo ambiental. Ele permite avaliar o estado do ambiente ao longo do tempo, informando sobre a necessidade e sobre as conseqüências das medidas de manejo. Na Amazônia, o monitoramento é uma atividade particularmente difícil devido à variedade das ameaças ambientais, à vastidão da área, e à enorme riqueza de espécies. Para ser eficiente, um programa de monitoramento precisa ser claramente enraizado em uma ameaça ambiental que se pretende resolver – só assim haverá um critério claro para decidir quais variáveis serão medidas e como planejar essa medição. Numa área tão grande quanto a Amazônia, é particularmente importante que os programas de monitoramento definam a priori a sua escala de atuação. Um desenho amostral que serve para a escala local será deficiente na escala regional, e vice‐versa. A idéia de trabalhar simultaneamente em diferentes escalas espaciais é louvável mas altamente arriscada. Finalmente, quando o monitoramento requer identificação de espécies, a riqueza biológica da Amazônia e a escassez de pessoal qualificado limitam o avanço do trabalho. Para garantir a viabilidade futura das atividades de monitoramento é essencial investir com criatividade e determinação no treinamento de observadores. Este comentário sublinha alguns aspetos de progresso recente em monitoramento biológico da Amazônia e identifica três necessidades para o futuro: 1) Garantir a orientação do monitoramento para ameaças claramente identificadas; 2) Trabalhar em uma escala espacial prioritária, definida antes do lançamento do programa; e 3) Investir no treinamento de observadores.El monitoreo biológico es una herramienta fundamental para la gestión ambiental porque permite evaluar el estado del ambiente al largo del tiempo, informando sobre la necesidad e sobre las consecuencias de acciones de gestión. En Amazonia, el monitoreo es una actividad particularmente difícil gracias à la variedad de amenazas, a la extensión de la área, y a la enorme riqueza de especies. Para ser eficiente, un programa de monitoreo necesita ser claramente enraizado en una amenaza ambiental que se pretende resolver – solo así existirá un criterio claro para decidir lo que medir y como medirlo. En una área tan grande como Amazonia, se hace esencial que los programas de monitoreo establezcan a priori su escala de actuación. Un diseño de muestreo que funciona en la escala local será deficiente en la escala regional y vice‐versa. La idea de trabajar simultáneamente en distintas escalas espaciales es muy arriesgada – hay que priorizar. Finalmente, cuando el monitoreo exige identificación de especies, la riqueza de Amazonia y la escasez de personal calificado limitan el progreso del trabajo. Para garantizar la viabilidad del monitoreo, se hace esencial invertir con creatividad y determinación en el entrenamiento de observadores. Este comentario refiere algunos progresos recientes en el monitoreo biológico de Amazonia y identifica tres necesidades para el futuro: 1) Garantizar que cada programa esté claramente orientado para una amenaza ambiental; 2) Trabajar en una escala espacial prioritária; y 3) Invertir en el entrenamiento de observadores.

Digital representation of spatial variation of multivariate landscape data

We propose a method that has general relevance to the digital representation of spatial variation of multivariate landscape data. It is based on the average similarity that operational geographic units (OGU) have with the adjacent ones according to characters relevant understanding landscape patterns and dynamics. The method is flexible and easily executable within the technological framework of geographic information systems (GIS) that today is available even free of charge or at very low cost. An example shows how the method, applied to spatial data of a floristic project for the urban area of Trieste (NE-Italy), can identify floristically homogeneous patches and can quantify the heterogeneity of the transition zones between such patches.

Geological and Petrophysical Characterization of the Ferron Sandstone in Utah, for 3-D Simulation of a Fluvial-Deltaic Reservoir: ABSTRACT

Fluvial-deltaic reservoirs contain the largest developed domestic oil reserves, and due to the high degree of reservoir heterogeneity, the largest amount of unrecovered oil of any type of developed reservoirs. The excellent outcrops of the fluvial-deltaic Ferron Sandstone Member of the Cretaceous Mancos Shale make the Coal Cliffs in east-central Utah a world-class area to study reservoir heterogeneity. With funding from the U.S. Department of Energy, a multidisciplinary team is developing a 3-D reservoir model for the Ferron Sandstone. Our work to date has consisted of: (1) determining geological and petrophysical properties of significant lithofacies, (2) developing new field methods, and (3) interpreting the stratigraphy regionally and within case-study areas. Numerous sections have been measured, described, and correlated to interpret of the sequence stratigraphy and lithofacies. Lithologic and paleocurrent data were entered into a database to construct statistical models, strip logs, and lithofacies maps. Several gamma-ray traverses were undertaken primarily for stratigraphic correlation. Numerous core plugs were obtained from various lithofacies for porosity, permeability, and other types of reservoir analyses. Permeability transects were completed across the proximal, middle, and distal portions of the delta-front sandstones. Six core holes were drilled in the central case-study area in a pattern similar tomore » that drilled in an oil field. The data collected will be integrated into a 3-D representation of spatial variations in porosity, storativity, and tensorial rock permeability at a scale appropriate for inter-well to regional-scale reservoir simulation. Results could improve management of similar reservoirs worldwide through proper infill and extension drilling strategies, reduction of economic risks, increased recovery, and more reliable reserve calculations.« less

Recursive parameter estimation with applications in earth sciences

Parameter estimation has become increasingly interesting the last few decades for a variety of engineering topics. In such situations, one may face problems like (a) how to estimate parameters for which erroneous measurements are available (direct estimation), or (b) how to estimate coefficients of some process model governing a geological phenomenon when these coefficients are inaccessible or difficult to access by direct investigation (inverse estimation or identification). Both these problems are examined in this presentation from a modern stochastic viewpoint, where parameters sought are interpretated mathematically as random functions, generated and estimated in space or time with the aid of recursive models. Advantages of this methodology are remarkable, from both theoretical and physical points of view, as compared to conventional statistics or nonrecursive estimators. Particularly it may offer more accurate estimators, better representation of spatial variation, and a means of overcoming difficulties such as excessive computational time or computer storage. To test effectiveness of this type of estimation, a series of representative case studies from geotechnical practice have been computed in detail.