Bootstrap approaches for spatial data     

Pilar García-Soidán  Raquel Menezes  Óscar Rubiños 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(5):1207-1219

Generation of replicates of the available data enables the researchers to solve different statistical problems, such as the estimation of standard errors, the inference of parameters or even the approximation of distribution functions. With this aim, Bootstrap approaches are suggested in the current work, specifically designed for their application to spatial data, as they take into account the dependence structure of the underlying random process. The key idea is to construct nonparametric distribution estimators, adapted to the spatial setting, which are distribution functions themselves, associated to discrete or continuous random variables. Then, the Bootstrap samples are obtained by drawing at random from the estimated distribution. Consistency of the suggested approaches will be proved by assuming stationarity from the random process or by relaxing the latter hypothesis to admit a deterministic trend. Numerical studies for simulated data and a real data set, obtained from environmental monitoring, are included to illustrate the application of the proposed Bootstrap methods.  相似文献   

Spatial-temporal rainfall modelling for flood risk estimation   总被引：4，自引：6，他引：4  

H. S. Wheater  R. E. Chandler  C. J. Onof  V. S. Isham  E. Bellone  C. Yang  D. Lekkas  G. Lourmas  M.-L. Segond 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(6):403-416

Some recent developments in the stochastic modelling of single site and spatial rainfall are summarised. Alternative single site models based on Poisson cluster processes are introduced, fitting methods are discussed, and performance is compared for representative UK hourly data. The representation of sub-hourly rainfall is discussed, and results from a temporal disaggregation scheme are presented. Extension of the Poisson process methods to spatial-temporal rainfall, using radar data, is reported. Current methods assume spatial and temporal stationarity; work in progress seeks to relax these restrictions. Unlike radar data, long sequences of daily raingauge data are commonly available, and the use of generalized linear models (GLMs) (which can represent both temporal and spatial non-stationarity) to represent the spatial structure of daily rainfall based on raingauge data is illustrated for a network in the North of England. For flood simulation, disaggregation of daily rainfall is required. A relatively simple methodology is described, in which a single site Poisson process model provides hourly sequences, conditioned on the observed or GLM-simulated daily data. As a first step, complete spatial dependence is assumed. Results from the River Lee catchment, near London, are promising. A relatively comprehensive set of methodologies is thus provided for hydrological application.  相似文献   

Use of variograms for field magnetometry analysis in Upper Silesia Industrial Region     

J. Zawadzki  P. Fabijańczyk 《Studia Geophysica et Geodaetica》2007,51(4):535-550

Measurements of topsoil magnetic susceptibility are often used for quick assessment of soil contamination of anthropogenic origin, with heavy metals or other pollutants. However, because of complicated correlations between low-field magnetic susceptibility (shortened to magnetic susceptibility) of topsoil and soil pollution, the outcome of a field magnetometry survey can not be related directly to soil pollution. For each case study, the results should be interpreted on their own taking into account not only the type of pollution but also pedogenic, biogenic and environmental factors. In practice, it is very difficult to measure and consider all these factors. Here we illustrate the merit of geostatistical methods, which are focused on the spatial variability of a phenomenon, in the interpretation of soil magnetometry results. This article presents the analysis of spatial variability of top soil layers magnetic susceptibility-within the Upper Silesia Industrial Region (USIR)-using semivariance analysis. It also explains how to adjust the sampling density of field magnetometry measurements to spatial variability of the soil pollution as well as to the spatial scale of the investigated area. For this purpose, the values of magnetic susceptibility have been measured by using various sampling densities at areas of different size located within USIR. This enabled to determine the main scales of magnetic susceptibility spatial variability of soils within USIR using semivariance. A few distinct scales of variability were found from the site scale to a more regional scale. Variability ranges of 30 km, 12 km, and 5 km refer to the large regional scale, whereas smaller ranges of few hundreds down to a few tens of meters, can be attributed to the local (site) scale. In addition, the precision of the measuring campaigns, performed within USIR with different sampling densities, was compared through the analysis of the spatial variability of the soil magnetic susceptibility signal by using ordinary kriging. jarek97@yahoo.com, piotr.fabijanczyk@is.pw.edu.pl  相似文献   

Scales and uncertainties in using models and GIS for volcano hazard prediction     

《Journal of Volcanology and Geothermal Research》2005,139(1-2):73-87

Practical decision-making in civil protection based on predicting volcano hazards often involves using process models linked with Geographic Information Systems (GIS). Optimum use of these techniques for such decision-support requires careful and coordinated consideration of process, data and model scales and their related uncertainties. To avoid wasting resources and time on inappropriate data collection, improper model use, and resultant poor decision-making, there is a pressing need for a scientific and functional framework within which to examine implementation and use of geo-spatial assessment tools. To be useful for researchers and decision-makers, volcano hazard simulation approaches must consider the spatial and temporal variability in volcano processes and the data collected representing those. The successful application and implementation of a geo-spatial distributed volcano hazard model at variable scales requires explicit or implicit use of some form of scaling theory applied to the tasks of selection and transformation of appropriate data, and use of results. In general, there are five consecutive scaling steps that demonstrate how data and model scale, as well as the methods for information transformation between these, play key roles in controlling whether prediction results have been produced efficiently and are appropriate at the scale of interest for a civil protection manager's decision-making process. This new scaling theory can be used as a framework to construct practical procedures for applying GIS-Model-based volcano models that allow effective model application based on realistic data availability and environmental settings.  相似文献   

A statistical framework of data fusion for spatial prediction of categorical variables   总被引：1，自引：0，他引：1  

Guofeng Cao  Eun-hye Yoo  Shaowen Wang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(7):1785-1799

With rapid advances of geospatial technologies, the amount of spatial data has been increasing exponentially over the past few decades. Usually collected by diverse source providers, the available spatial data tend to be fragmented by a large variety of data heterogeneities, which highlights the need of sound methods capable of efficiently fusing the diverse and incompatible spatial information. Within the context of spatial prediction of categorical variables, this paper describes a statistical framework for integrating and drawing inferences from a collection of spatially correlated variables while accounting for data heterogeneities and complex spatial dependencies. In this framework, we discuss the spatial prediction of categorical variables in the paradigm of latent random fields, and represent each spatial variable via spatial covariance functions, which define two-point similarities or dependencies of spatially correlated variables. The representation of spatial covariance functions derived from different spatial variables is independent of heterogeneous characteristics and can be combined in a straightforward fashion. Therefore it provides a unified and flexible representation of heterogeneous spatial variables in spatial analysis while accounting for complex spatial dependencies. We show that in the spatial prediction of categorical variables, the sought-after class occurrence probability at a target location can be formulated as a multinomial logistic function of spatial covariances of spatial variables between the target and sampled locations. Group least absolute shrinkage and selection operator is adopted for parameter estimation, which prevents the model from over-fitting, and simultaneously selects an optimal subset of important information (variables). Synthetic and real case studies are provided to illustrate the introduced concepts, and showcase the advantages of the proposed statistical framework.  相似文献   

THE USE OF OBSERVATIONAL SPACE IN SEISMIC REFRACTION TECHNIQUES *     

G. M. HABBERJAM 《Geophysical Prospecting》1973,21(1):26-45

Attention is given in this paper to the display of intensive seismic refraction information in a convenient form similar to spatial display techniques being developed for resistivity methods. An observational space for first arrivals is defined and illustrated with respect to some simple structures and the possible use of such a representation in diagnosis is discussed. The spatial display is suitable both for steeply dipping and gently dipping structures. In the latter case, the low relief space may be subjected to further operations to produce apparent velocity distributions and values simply related to plus times. A practical example of the latter process and the subsequent interpretation is given.  相似文献   

Scale-recursive assimilation of precipitation data     

Ida Primus Gorenburg  Dennis McLaughlin  Dara Entekhabi   《Advances in water resources》2001,24(9-10)

This paper presents a new statistical method for assimilating precipitation data from different sensors operating over a range of scales. The technique is based on a scale-recursive estimation algorithm which is computationally efficient and able to account for the nested spatial structure of precipitation fields. The version of the algorithm described here relies on a static multiplicative cascade model which relates rainrates at different scales. Bayesian estimation techniques are used to condition rainrate estimates on measurements. The conditioning process is carried out recursively in two sweeps: first from fine to coarse scales and then from coarse to fine scales. The complete estimation algorithm is similar to a fixed interval smoother although it processes data over scale rather than time. We use this algorithm to assimilate radar and satellite microwave data collected during the tropical ocean–global atmosphere coupled ocean–atmosphere response experiment (TOGA-COARE). The resulting rainrate estimates reproduce withheld radar measurements to within the level of accuracy predicted by the assimilation algorithm.  相似文献   

Temporal change of spatial heterogeneity and its effect on regional trend of annual precipitation heterogeneity indices          下载免费PDF全文

Runrun Zhang  Xi Chen  Huimin Wang  Qinbo Cheng  Zhicai Zhang  Peng Shi 《水文研究》2017,31(18):3178-3190

A statistical test on climate and hydrological series from different spatial resolution could obtain different regional trend due to spatial heterogeneity and its temporal variability. In this study, annual series of the precipitation heterogeneity indices of concentration index (CI) and the number of wet days (NW) along with annual total amount of precipitation were calculated based on at‐site daily precipitation series during 1962–2011 in the headwater basin of the Huaihe River, China. The regional trends of the indices were first detected based on at‐site series by using the aligned and intrablock methods, and field significance tests that consider spatial heterogeneity over sites. The detected trends were then compared with the trends of the regional index series derived from daily areal average precipitation (DAAP), which averages at‐site differences and thus neglects spatial heterogeneity. It was found that the at‐site‐based regional test shows increasing trends of CI and NW in the basin, which follows the test on individual sites that most of sites were characterized by increasing CI and NW. However, the DAAP‐derived regional series of CI and NW were tested to show a decreasing trend. The disparity of the regional trend test on at‐site‐based regional series and the DAAP‐derived regional series arises from a temporal change of the spatial heterogeneity, which was quantified by the generalized additive models for location, scale, and shape. This study highlights that compared with averaging indices, averaging at‐site daily precipitation could lead to an error in the regional trend inference on annual precipitation heterogeneity indices. More attention should be paid to temporal variability in spatial heterogeneity when data at large scales are used for regional trend detection on hydro‐meteorological events associated with intra‐annual heterogeneity.  相似文献   

Estimation of shear wave velocity profiles by the inversion of spatial autocorrelation coefficients     

Argun H. Kocaoğlu  Karolin Fırtana 《Journal of Seismology》2011,15(4):613-624

The subsurface shear-wave velocity (Vs) is considered to be a key parameter for site characterization and assessment of earthquake hazard because of its great influence on local ground-motion amplification. Array microtremor measurements are widely used for the estimation of shear-wave velocities. Compared to other methods such as frequency-wavenumber (f-k) methods, the spatial autocorrelation (SPAC) method requires fewer sensors and thus is relatively easier to implement and gives robust estimations of shear-wave velocity profiles for depths down to a few hundred meters. The quantity derived from observed data is the SPAC coefficient, which is a function of correlation distance, frequency and phase velocity. Generally, estimation of Vs profiles is a two stage process: Estimation of the dispersion data from the SPAC coefficients and inversion of the dispersion data for shear-wave velocity structure. In this study, instead of inverting dispersion curves, a more practical approach is used; that is, observed SPAC coefficients are directly inverted for the S-wave velocities. A synthetic case and a field data application are presented to test the potential of the inversion algorithm. We obtain an iterative damped least-squares solution with differential smoothing. The differential smoothing approach constrains the change in shear-wave velocities of the adjacent layers and thus stabilizes the inversion.  相似文献   

Better models are more effectively connected models   总被引：1，自引：0，他引：1       下载免费PDF全文

Connecteur WG Think‐Tank Team  Jo?o Pedro Nunes  John Wainwright  Charles L. Bielders  Frédéric Darboux  Peter Fiener  David Finger  Laura Turnbull 《地球表面变化过程与地形》2018,43(6):1355-1360

Water‐ and sediment‐transfer models are commonly used to explain or predict patterns in the landscape at scales different from those at which observations are available. These patterns are often the result of emergent properties that occur because processes of water and sediment transfer are connected in different ways. Recent advances in geomorphology suggest that it is important to consider, at a specific spatio‐temporal scale, the structural connectivity of system properties that control processes, and the functional connectivity resulting from the way those processes operate and evolve through time. We argue that a more careful consideration of how structural and functional connectivity are represented in models should lead to more robust models that are appropriate for the scale of application and provide results that can be upscaled. This approach is necessary because, notwithstanding the significant advances in computer power in recent years, many geomorphic models are still unable to represent the landscape in sufficient detail to allow all connectivity to emerge. It is important to go beyond the simple representation of structural connectivity elements and allow the dynamics of processes to be represented, for example by using a connectivity function. This commentary aims to show how a better representation of connectivity in models can be achieved, by considering the sorts of landscape features present, and whether these features can be represented explicitly in the model spatial structure, or must be represented implicitly at the subgrid scale. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

Comparison of Phytoscreening and Direct‐Push‐Based Site Investigation at a Rural Megasite Contaminated with Chlorinated Ethenes          下载免费PDF全文

Arno Rein  Olaf Holm  Stefan Trapp  Steffen Popp‐Hofmann  Martin Bittens  Carsten Leven  Peter Dietrich 《Ground Water Monitoring & Remediation》2015,35(4):45-56

The reliable characterization of subsurface contamination of spatially extended contaminated sites is a challenging task, especially with an unknown history of land use. Conventional technologies often fail due to temporal and financial constraints and thus hinder the redevelopment of abandoned areas in particular. Here we compare two site screening techniques that can be applied quickly at relatively low cost, namely Direct Push (DP)‐based groundwater sampling and tree core sampling. The effectiveness of both methods is compared for a rural megasite contaminated with chlorinated hydrocarbons. Unexpected pollution hot spots could be identified using both of these methods, while tree coring even enabled the delineation of the contaminant plume flowing into an adjacent wetland inaccessible for DP units. Both methods showed a good agreement in revealing the spatial pattern of the contamination. The correlation between groundwater concentrations and equivalent concentrations in wood was linear and highly significant for trichloroethene. Correlation was less obvious for its metabolite cis‐dichloroethene, but still significant. As outcome of our study we recommend tree coring and for initial screening in combination with a DP sampling to retrieve quantitative data on groundwater pollutants in order to assess the contamination situation of a non‐ or only partly investigated site. The subsequent placement of monitoring wells for long‐term monitoring of contamination levels is recommended. A combination of methods would achieve more relevant information at comparable or possibly even lower efforts in comparison to a conventional site investigation.  相似文献   

On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins     

Daniel Andres Rodriguez  Javier Tomasella 《水文科学杂志》2013,58(10):1831-1846

ABSTRACT

The MHD-INPE model was applied in the Ji-Parana Basin, a 30 000 km² catchment located in the southwest of the Amazon Basin which has lost more than 50% of its forest since the 1980s, to simulate land use and land cover change impacts on runoff generation process and how they are related to basin topography. Simulation results agree with observational studies in the sense that fast response processes are significant in sub-basins with steep slopes while in basins with gentle topography, the impacts are most visible in slow-response hydrological processes. On the other hand, the model is not able to capture the dependence of LUCC impacts on spatial scales. These discrepancies are probably associated with limitations in the spatial representation of heterogeneities within the model, which become more relevant at larger scales. We also tested the hypothesis that secondary forest growth should be able to compensate the decrease in evapotranspiration due to forest–cropland or forest–grassland conversion at a regional scale. Results showed that despite the small fraction of secondary forest estimated on the basin, the higher evapotranspiration efficiency of this type of forest counterbalances a large fraction of the LUCC impacts on evapotranspiration. This result suggests that enhanced transpiration due to secondary forest could explain, at least in part, the lack of clear LUCC signals in discharge series at larger scales.