Applications of multivariate statistical analysis in remote sensing of agriculture

Rasmussen, Kjeld & Olesen, Henrik Hagen: Applications of multivariate statistical analysis in remote sensing of agriculture. Geografisk Tidsskrift 88:100–107. Copenhagen 1988.

Applications of satellite remote sensing to agriculture involve two main objectives, the identification and mapping of crops, including estimation of acreages, and monitoring of plant growth or production factors, aiming at estimation/prediction of yields.

Deterministic models of the interaction of electromagnetic radiation and plant canopies are used to relate the measured reflected or emitted radiation to crop type and agronomically relevant parameters. The great natural variation of reflectance properties of crops does, however, call for use of a statistical approach. The high dimensionality of the data-sets involved, very often more than ten, requires the use of multivariate techniques.

This paper will deal with the use of multivariate statistical techniques for both crop identification and crop monitoring based on high-resolution satellite remote sensing data, such as those produced by Landsat MSS and -TM and SPOT. Emphasis will be placed upon use of statistical methods in classification and on removal of redundancy in multi-dimensional data-sets. The relative merits of deterministic and statistical methods will be discussed as will the possibilities of incorporating spatial information into statistical methods.     

高阶统计量及AIC方法在区域地震事件和直达P波初动识别中的应用

利用高阶统计量（偏斜度和峰度）与赤池信息量准则（简称AIC）相结合,进行区域地震事件实时检测和P波初至精细识别的新方法研究,通过处理山东地震台网记录的地震波资料,结果表明：应用高阶统计量（偏斜度和峰度,尤其是峰度）能够有效识别地震事件,降低地震事件的错误报警率和漏报率;与人工识别震相到时结果相比,根据Ske-AIC、Kur-AIC震相自动识别方法得到的震相到时的平均绝对值误差小.     

数学形态滤波法在GPS基线分析中的应用

通过GAMIT软件得到福建省连续观测GPS基准站基线时间序列,并引人数学形态滤波法,过滤基线中的白噪音和脉冲扰动.以福建省主要断裂带为研究背景,研究GPS基线时间序列、跨断层短水准观测资料与福建主要断层的相关性,分析了影响基线变化的因素,以及地壳水平运动与应力积累的关系.     

光释光测年单个黄土样品测片个数选取问题的统计学研究

光释光测年多颗粒实验中单个样品的测片个数选取没有一定标准,从几十到一百多个不等。通过分析7个黄土中颗粒(38~63 μm)样品,分别进行了不同测片个数的等效剂量的实验及统计分析研究。每个样品的等效剂量由SAR法和SGC法得到,每个样品不同测片数的等效剂量结果进行了多种统计分析和检验。认为在风成沉积物的光释光测年实验中,当一个样品进行实验的测片数达到20~30个测片时,样品的等效剂量分布形态就趋于稳定;即此测片数较合理——既能较准确反映统计意义上的样品的古剂量,又不至于进行大量重复性工作;这对于水成沉积物光释光测年中单个样品的测片个数选取也有一定的参考价值。     

Spatiotemporal analysis of rural–urban land conversion

Understanding the complexity of urban expansion requires an analysis of the factors influencing the spatial and temporal processes of rural–urban land conversion. This study aims at building a statistical land conversion model to assist in understanding land use change patterns. Specifically, GIS coupled with a logistic regression model and exponential smoothing techniques is used for exploring the effects of various factors on land use change. These factors include population density, slope, proximity to roads, and surrounding land use, and their influence on land use change is studied for generating a predictive model. Methods to reduce spatial autocorrelation in a logistic regression framework are also discussed. Primarily, an optimal sampling scheme that can eliminate spatial autocorrelation while maintaining adequate samples to allow the model to achieve the comparable accuracy as the spatial autoregressive model is developed. Since many of the previous studies on modeling the spatial complexity of urban growth ignored temporal complexity, a modified exponential smoothing technique is employed to produce a smoothed model from a series of bi‐temporal models obtained from different time periods. The proposed model is validated using the multi‐temporal land use data in New Castle County, DE, USA. It is demonstrated that our approach provides an effective option for multi‐temporal land use change modeling and the modeling results help interpret the land use change patterns.     

RIPARIAN VEGETATION AND SANDBAR MORPHOLOGY ALONG THE LOWER LITTLE COLORADO RIVER,ARIZONA

The distribution of riparian vegetation in relation to channel morphology is poorly understood in canyon rivers, which are characterized by in-channel fluvial sediment deposits rather than flood plains. This study focuses on vegetation and sandbar characteristics in two reaches of the lower Little Colorado River canyon in Arizona–one reach with ephemeral flow from the watershed, and another with perennial baseflow from a spring. Both reaches have been colonized by the exotic Tamarix chinensis, a riparian species known for its geomorphic influence on river channels. On the basis of a sampling of 18 bars, results show that vegetation frequency and density is significantly greater in the perennial study reach. However, sandbar morphology variables do not differ between reaches, despite a significantly narrower and deeper ephemeral channel. Hydraulic calculations of flood depths and Pearson correlations between bar and vegetation variables indicate reach-specific biogeomorphic relationships. In the ephemeral reach, higher bars are less affected by flood inundation, support older vegetation, and may be more stable habitat for vegetation. In the wider perennial reach where bars are lower and more expansive, vegetation patterns relate to bar size, Tamarix being most common on the largest bars. Overall results suggest that (1) vegetation variation relates to baseflow hydrology, (2) bar formation relates to high discharge events, and (3) vegetation patterns respond to, rather than influence, sandbar form in this canyon riparian system.     

Radioactive high level waste insight modelling for geological disposal facilities

Within this paper we present a simplified analytical model to provide insight into the key performance measures of a generic disposal system for high level waste within a geological disposal facility. The model assumes a low solubility waste matrix within a corrosion resistant disposal container surrounded by a low permeability buffer. Radionuclides migrate from the disposal area through a porous geosphere to the biosphere and give a radiological dose to a receptor. The system of equations describing the migration is transformed into Laplace space and an approximation used to determine peak values for the radionuclide mass transfer rate entering the biosphere. Results from the model are compared with those from more detailed numerical models for key radionuclides in the UK high level waste inventory. Such an insight model can provide a valuable second line of argument to assist in confirming the results of more detailed models and build confidence in the safety case for a geological disposal facility.     

Using geovisual analytics to compare the performance of geographically weighted discriminant analysis versus its global counterpart,linear discriminant analysis

Geographically weighted spatial statistical methods are a family of spatial statistical methods developed to address the presence of non-stationarity in geographical processes, the so-called spatial heterogeneity. While these methods have recently become popular for analysis of spatial data, one of their characteristics is that they produce outputs that in themselves form complex multi-dimensional spatial data sets. Interpretation of these outputs is therefore not easy, but is of high importance, since spatial and non-spatial patterns in the results of these methods contain clues to causes of underlying non-stationarity. In this article, we focus on one of the geographically weighted methods, the geographically weighted discriminant analysis (GWDA), which is a method for prediction and analysis of categorical spatial data. It is an extension of linear discriminant analysis (LDA) that allows the relationship between the predictor variables and the categories to vary spatially. This produces a very complex data set of GWDA results, which include on top of the already complex discriminant analysis outputs (e.g. classifications and posterior probabilities) also spatially varying outputs (e.g. classification function parameters). In this article, we suggest using geovisual analytics to visualise results from LDA and GWDA to facilitate comparison between the global and local method results. For this, we develop a bespoke visual methodology that allows us to examine the performance of global and local classification method in terms of quality of classification. Furthermore, we are also interested in identifying the presence (or absence) of non-stationarity through comparison of the outputs of both methods. We do this in two ways. First, we visually explore spatial autocorrelation in both LDA and GWDA misclassifications. Second, we focus on relationships between the classification result and the independent variables and how they vary over space. We describe our visual analytic system for exploration of LDA and GWDA outputs and demonstrate our approach on a case study using a data set linking election results with a selection of socio-economic variables.     

星系翘曲盘及其统计研究

河外旋涡星系外区普遍存在翘曲结构,其特征可用干翘曲参数来描述,包括翘曲角、翘曲半径、不对称度等。一些翘曲星系表已相继发表,并用于相关的统计分析。关于翘曲盘的形成已提出多种理论机制,如星系间的潮汐相互作用、星系际介质的吸积、盘与暗晕的角动量错向以及星系际磁场的作用等。     

Quantification of particle crushing in consideration of grading evolution of granular soils in biaxial shearing: A probability‐based model

A probability‐based model is presented to estimate particle crushing and the associated grading evolution in granular soils during isotropic compression and prepeak shearing in biaxial tests. The model is based on probability density functions of interparticle and intraparticle stress (ie, particle normalized maximum shear stress and particle average maximum shear stress) derived from discrete element method simulations of biaxial tests. We find that the probability density functions of normalized maximum shear stress are dependent on the current sample grading, implying coupling effects between particle crushing and sample grading such that the particle crushing is affected by the current sample grading, and the grading change is also dependent on the current particle crushing extent. To incorporate these coupling effects into the model, particle crushing and grading change are calculated for each load increment, in which the crushing probability of a particle during any loading increment is denoted as the corresponding increment of probability of the internal maximum shear stress exceeding its maximum shear strength. The model shows qualitative agreement with published experimental data. The effects of the model parameters, including initial porosity, particle strength, initial grading, and crushing mode, on the calculated results are discussed and compared with previous studies. Finally, the strengths and limitations of the model are discussed.