Quantifying uncertainty in remote sensing-based urban land-use mapping

Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at sub-pixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map – indicating absence of bias in the mapping process – it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth.     

数量性状位点的相对选择效率

从理论上采用蒙特卡罗(Monte Carlo)模拟的方法研究了不同遗传力条件下数量性状位点的直接选择(DSQ)和以表型为基础的选择(TBS)在10个不重叠世代中的选择反应以及DSQ相对于TBS的优势。结果表明,在10个世代中DSQ的选择进展在几乎总是大于TBS的选择进展,说明DSQ较TBS具有优越性;但DSQ的相对选择效率(RSE)会随着世代数的增加而呈现较迅速下降的趋势,单个性状情况下RSE则呈直线下降的趋势。随着选择代数的增加,DSQ将失去其优越性,TBS在遗传进展上将超过DSQ。     

Modelling river water temperature using deterministic,empirical, and hybrid formulations in a Mediterranean stream

River water temperature is a common target of water quality models at the watershed scale, owing to its principal role in shaping biogeochemical processes and in stream ecology. Usually, models include physically‐based, deterministic formulations to calculate water temperatures from detailed meteorological information, which usually comes from meteorological stations located far from the river reaches. However, alternative empirical approaches have been proposed, that usually depend on air temperature as master variable. This study explored the performance of a semidistributed water quality application modelling river water temperature in a Mediterranean watershed, using three different approaches. First, a deterministic approach was used accounting for the different heat exchange components usually considered in water temperature models. Second, an empirical approximation was applied using the equilibrium temperature concept, assuming a linear relationship with air temperature. And third, a hybrid approach was constructed, in which the temperature equilibrium concept and the deterministic approach were combined. Results showed that the hybrid approach gave the best results, followed by the empirical approximation. The deterministic formulation gave the worst results. The hybrid approach not only fitted daily river water temperatures, but also adequately modelled the daily temperature range (maximum–minimum daily temperature). Other river water features directly dependent on water temperature, such as river intrusion depth in lentic systems (i.e. the depth at which the river inflow plunges to equilibrate density differences with lake water), were also correctly modelled even at hourly time steps. However, results for the different heat fluxes between river and atmosphere were very unrealistic. Although direct evidence of discrepancies between meteorological drivers measured at the meteorological stations and the actual river microclimate was not found, the use of models including empirical or hybrid formulations depending mainly on air temperature is recommended if only meteorological data from locations far from the river reaches are available. Copyright © 2008 John Wiley & Sons, Ltd.     

Probabilistic modelling of long-term beach evolution near segmented shore-parallel breakwaters

This paper presents a new framework for probabilistic modelling of long-term beach evolution in the vicinity of detached breakwaters. The study focuses on the key physical processes contributing to beach variability over a range of spatial and temporal scales. Based on a one-line model, the framework is enhanced with sophisticated solutions for beach-wave-structure interaction, diffraction together with a treatment of varying tide level. The sediment transport rate is calibrated at regional and local levels using data from bespoke field campaigns and site-specific coefficients are proposed. Monte Carlo simulation is conducted for long-term shoreline simulation under a sequence of time varying sequence of waves, currents and tidal levels. The results of the Monte Carlo simulation give an insight into the statistical characteristics of beach behaviour within the defence system. In particular, regions within the scheme that are relatively stable and those that exhibit greater natural fluctuations are identified.     

地磁匹配导航算法研究

提出一种MonteCarlo方法和均方差算法（MSD）相结合的匹配算法，并将本算法用于地磁匹配导航中。该方法根据惯性导航系统指示的位置从地磁图上提取参考地磁数据，将地磁测量数据进行若干次随机干扰后和参考地磁数据使用MSD算法进行匹配，得到若干个匹配位置，取其均值作为最终匹配位置。仿真结果表明本算法可行。     

考虑优势流作用的降雨入渗边坡可靠度分析

降雨诱发滑坡是世界上最普遍的地质灾害,而关于降雨入渗对边坡的可靠度分析,优势入渗的影响被长期忽视。使用Comsol Multiphysics对降雨条件下优势入渗做数值求解,利用无限边坡模型计算边坡安全系数;并应用改进Cholesky分解法生成空间相关随机场,使用蒙特卡洛方法分析降雨过程中边坡的可靠度。结合确定性与可靠度计算对比均质入渗与优势入渗在降雨过程中边坡安全性变化：（1）降雨强度较低时,优势入渗安全性较好,而降雨强度较高时,均质入渗更稳定;（2）均质入渗中参数空间变异性是边坡失稳破坏的关键因素,而优势入渗的边坡失稳则由湿润峰快速推进所导致;（3）针对优势入渗模型研究,发现基质域与优势域水力交换强度较大时边坡有更大概率失稳,而较小的水力交换强度可能影响边坡底部的失稳破坏。     

Importance sampling based algorithm for efficient reliability analysis of axially loaded piles

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.     

岩质路堑边坡施工监测及稳定性分析

以某高速公路岩质路堑边坡为例,通过施工现场监测及稳定性分析,结果显示初始设计状态下坡体深层位移和坡面位移接近滑动临界值。采取变更设计后,利用现场监测结合蒙特卡洛数值模拟的方法对该路堑边坡的加固效果进行稳定性和可靠性分析。经过加固后的边坡能较好地维持稳定,支护措施可靠。这种现场监测结合蒙特卡洛数值模拟的方法为路堑边坡的动态设计提供了依据,并能及时作出趋势性预测,为路堑岩质边坡的合理支护提供一种新的思路。     

一种生成大周期伪随机数的新算法——改进的混合同余法

为了克服当前所生成的伪随机数周期小、每个随机数仅能出现1次而不能重复的缺点,本文提出了一种生成伪随机数的新方法,称为改进的混合同余法。     

Primary proton spectrum around the knee deduced from the emulsion-chamber data obtained at Mts. Fuji and Kanbala

We have done extensive Monte Carlo simulations using the new simulation codes of CORSIKA and COSMOS to compare with the gamma-family data obtained at Mts. Fuji (3750 m above sea level) and Kanbala (5500 m above sea level). Then, we estimated the primary proton and helium spectra around the knee energy region using a multiple-layered feed-forward neural network as a classifier of primary particle kind. The selection efficiency of proton-induced family events is estimated to be 82%. The flux value of protons at 2×10¹⁵ eV is (5.5±1.5)×10⁻¹⁴ (m⁻² s⁻¹ sr⁻¹ GeV⁻¹). The result suggests heavy-enriched primary composition around the knee region.