基于辅助变量的森林半腐层厚度空间插值精度

基于地统计学方法,利用3种以海拔作为辅助变量的空间插值算法[局部平均的简单kriging法(simple kriging with locally varying mean,SKlm)、带有外部漂移的kriging法(krig-ing with an external drift,KED)和协kriging法(cokrging,COK)]计算了森林半腐层厚度的空间插值精度,并进行了交叉验证.结果表明:KED法既考虑了变量之间的空间变异,又考虑到影响局部空间变化的因素,与其他插值方法相比,其精度有很大提高;由于海拔与半腐层厚度之间的相关关系较弱,导致SKlm法的插值精度没有达到预期效果;COK法直接将海拔用于估计半腐层厚度,由于在边界地区缺乏采样点数据,因此边界地区的插值出现了多处突变区域.对比地统计学方法与距离反比权重法(inverse distance weighting,IDW)在本研究中的插值精度,除了KED方法的插值精度较高外,其余方法的插值精度均不及IDW,原因可能是利用辅助变量辅助地统计学插值时,主、辅助变量之间的相关关系在插值中起着重要作用.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.

Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Modeling of atmospheric effects on InSAR measurements by incorporating terrain elevation information

We propose an elevation-dependent calibratory method to correct for the water vapour-induced delays over Mt. Etna that affect the interferometric syntheric aperture radar (InSAR) results. Water vapour delay fields are modelled from individual zenith delay estimates on a network of continuous GPS receivers. These are interpolated using simple kriging with varying local means over two domains, above and below 2 km in altitude. Test results with data from a meteorological station and 14 continuous GPS stations over Mt. Etna show that a reduction of the mean phase delay field of about 27% is achieved after the model is applied to a 35-day interferogram. (C) 2006 Elsevier Ltd. All rights reserved.

An investigation into the impact of using various techniques to estimate Arctic surface air temperature anomalies

Time series of global and regional mean Surface Air Temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies and Simple Kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, Root Mean Square Errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Non-interpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979-2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

Estudo integrado de análogo a reservatórios petrolíferos fluviais: caracterização, parametrização e modelagem tridimensional de depósitos recentes do Rio Assu (Rio Grande do Norte/Brasil)

This work shows a integrated study of modern analog to fluvial reservoirs of Açu Formation (Unit 3). The modern analog studied has been Assu River located in the same named city, Rio Grande do Norte State, Northeast of Brazil. It has been developed a new methodology to parameterizating the fluvial geological bodies by GPR profile (by central frequency antennas of 50, 100 and 200 MHz). The main parameters obtained were width and thickness. Still in the parameterization, orthophotomaps have been used to calculate the canal sinuosity and braided parameters of Assu River. These information are integrated in a database to supply input data in 3D geological models of fluvial reservoirs. It was made an architectural characterization of the deposit by trench description, GPR profile interpretation and natural expositions study to recognize and describe the facies and its associations, external and internal geometries, boundary surfaces and archtetural elements. Finally, a three-dimensional modeling has been built using all the acquired data already in association with real well data of a reservoir which Rio Assu is considered as analogous. Facies simulations have been used simple kriging (deterministic algorithm), SIS and Boolean (object-based, both stochastics). And, for modeling porosities have used the stochastic algorithm SGS

Comparação entre as redes neurais artificiais e o método de interpolação krigagem aplicados à pesquisa agronômica

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Suscetibilidade magnética e análise de incertezas em mapeamento de solos

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).

Estimating total cross sections from neutron-nucleus collisions using a simple functional form

Total cross sections for neutron scattering from nuclei, with energies ranging from 10 to 600 MeV and from many nuclei spanning the mass range 6Li to 238U, have been analyzed using a simple, three-parameter, functional form. The calculated cross sections are compared with results obtained by using microscopic (g-folding) optical potentials as well as with experimental data. The functional form reproduces those total cross sections very well. When allowance is made for Ramsauer-like effects in the scattering, the parameters of the functional form required vary smoothly with energy and target mass. They too can be represented by functions of energy and mass.