A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions

Spatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).     

Geostatistical Analysis of Spatial and Temporal Variations of Groundwater Level

Groundwater and water resources management plays a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying management tools which can reveal the critical and hot conditions seems necessary due to some limitations such as labor and funding. In this study, spatial and temporal analysis of monthly groundwater level fluctuations of 39 piezometric wells monitored during 12 years was carried out. Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial and temporal structure of groundwater level fluctuation. Results showed that a strong spatial and temporal structure existed for groundwater level fluctuations due to very low nugget effects. Spatial analysis showed a strong structure of groundwater level drop across the study area and temporal analysis showed that groundwater level fluctuations have temporal structure. On average, the range of variograms for spatial and temporal analysis was about 9.7 km and 7.2 months, respectively. Ordinary and universal kriging methods with cross-validation were applied to assess the accuracy of the chosen variograms in estimation of the groundwater level drop and groundwater level fluctuations for spatial and temporal scales, respectively. Results of ordinary and universal krigings revealed that groundwater level drop and groundwater level fluctuations were underestimated by 3% and 6% for spatial and temporal analysis, respectively, which are very low and acceptable errors and support the unbiasedness hypothesis of kriging. Although, our results demonstrated that spatial structure was a little bit stronger than temporal structure, however, estimation of groundwater level drop and groundwater level fluctuations could be performed with low uncertainty in both space and time scales. Moreover, the results showed that kriging is a beneficial and capable tool for detecting those critical regions where need more attentions for sustainable use of groundwater. Regions in which were detected as critical areas need to be much more managed for using the current water resources efficiently. Conducting water harvesting systems especially in critical and hot areas in order to recharge the groundwater, and altering the current cropping pattern to another one that need less water requirement and applying modern irrigation techniques are highly recommended; otherwise, it is most likely that in a few years no more crop would be cultivated.     

Mapping Soil Gas Radon Concentration: A Comparative Study of Geostatistical Methods

Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.     

Space-time statistics for environmental and agricultural related phenomena

This paper presents an overview of space-time statistical procedures to analyse agricultural and environmental related phenomena. It starts with an application on root-rot development in cotton. Dependence modelling in space and time is done with the space-time variogram. Various kriging interpolators are presented for making predictions in space and time. Simulated annealing is used to design an optimal monitoring network for estimation of space-time variograms. In the application no clear indication was found for anisotropy, although strong evidence exists that the disease not only proceeds within rows but also jumps between rows. The optimal sampling scheme showed a spatial clustering of observations at the first and the last monitoring day and less observations at intermediate times.     

基于贝叶斯公式的地下水污染源及含水层参数同步反演

针对非均质地下含水层污染源识别及含水层参数反演过程中监测方案优化问题,提出一种基于贝叶斯公式及信息熵最小的累进加井的多井监测方案优化方法.首先,构建假想案例下的二维非均质各向同性潜水含水层水流及溶质运移模型,运用GMS软件进行数值模拟求解.采用最优拉丁超立方抽样方法和Kriging法建立数值模拟模型的替代模型.然后以参数后验分布的信息熵最小为目标函数,采用累进加井的方式进行多井监测方案优化设计.最后根据优化后的监测方案,采用差分进化自适应Metropolis算法进行污染源及含水层参数的同步反演.算例研究表明：在兼顾反演精度及监测成本,并保证每个参数分区内至少有1眼监测井的条件下,5眼井组合监测方案（6,5,1,2,8）为最优监测方案.与信息熵最小的10眼井组合监测方案（1,2,3,4,5,6,7,8,9,10）的参数反演结果相比,5眼井组合监测方案对11个参数α=（X_S,Y_S,T₁,T₂,Q_s,K₁,K₂,K₃,DL₁,DL₂,DL₃）的后验均值偏离率的平均值虽增大1.2%,但监测成本却是10眼井组合监测方案的50%.     

One,two or three dimensions of work engagement? Testing the factorial validity of the Utrecht Work Engagement Scale on a sample of Polish employees

Work engagement, as conceptualized by the Utrecht Work Engagement Scale (UWES), is a work-related positive state of mind that is characterized by vigour, dedication and absorption; however, it still remains unclear how many dimensions work engagement comprises. This study tested the factorial validity of 11 different UWES factorial models that are available in the literature using a confirmatory factor analysis approach on a large sample of multi-occupational Polish employees (N?=?1420). The two-factor UWES-6, comprising vigour and dedication, was found to be reliable and remained invariant across samples drawn from four different organizational positions. It also presented a better fit than the three-factor UWES-9, which is a scale used as a standard in contemporary research on work engagement. The findings suggest that the three-factor UWES-9 might not be an optimal measure of work engagement in Poland.     

Short-term toxicity of pyraclofos used as a blackfly larvicide on non-target aquatic fauna in a tropical environment

Among the many larvicides tested for the control of s.l. larvae, the vector of human onchocerciasis in West Africa, pyraclofos proved to be 100% effective at 100 μg × L⁻¹ for 10 min in river, with a carry of 20 km at 100 m³ × sec⁻¹. Tests were then performed both in laboratory and field conditions to evaluate its toxicity on the non-target aquatic fauna. In experimental short-term gutter tests, the detachment of the total benthic insects was 35% at 100 μg × L⁻¹ for 10 min against 17% for temephos at the same dose and 59% for chlorphoxim at 50μg × L⁻¹ for 10 min. , and were the most affected organisms. The treatment of a river resulted in a considerable detachment of the same taxonomic groups, plus Orthocladiinae. On the other hand, investigations conducted in tanks showed that the 24-hr LC₅₀ for is 150 μg × L⁻¹ and that for 170 μg × L⁻¹, values which are not very different from the operational dose of the larvicide (100 μg × L⁻¹ for 10 min.). Nevertheless, in a river, no fish mortality was recorded. Based on fish LC₅₀ and drift of benthic insects, pyraclofos at 100 μg × L⁻¹ was judged to be less toxic to aquatic fauna in the short term than permethrin and carbosulfan.     

中国1961-2000年月平均气温空间插值方法与空间分布

利用地理信息系统软件ARC/INFO,在考虑海拔高度对气温影响和没有考虑海拔高度对气温影响的两种情况下,分别运用样条插值法、普通克立格法和逆距离权重法对中国623个气象站1961—2000年40 a的逐月平均气温进行了空间插值,并利用交叉检验方法对插值精度进行了评估,结果表明:考虑了海拔高度影响的3种插值方法的精度都有比较明显的提高,对于普通克立格法,平均绝对误差(MAE)从1.44℃降到0.82℃,均方根误差(RMSE)从2.31℃降到1.28℃;对于逆距离权重法,MAE从1.52℃降到0.88℃,RMSE从2.38℃降到1.34℃;对于样条插值法,MAE从1.54℃降到0.87℃,RMSE从2.49℃降到1.35℃。在6种插值方法中,考虑了海拔高度影响的普通克立格法是最优空间插值方法。     

Effects of interpolation and data resolution on methane emission estimates from rice paddies

Rice paddies are an important source of the greenhouse gas methane (CH₄). Global methane emission estimates are highly uncertain and do not account for effects of interpolation or data resolution errors. This paper determines such scaling effects for the influence of soil properties on calculated CH₄ emissions for the island of Java, Indonesia. The effects of different interpolation techniques, variograms and neighbor optimization were tested for soil properties by cross-validation. Interpolated organic carbon values were not significantly different from the original soil samples, in contrast to interpolated soil iron contents. Interpolation of soil properties coupled to a process-based model on CH₄emissions led to a significant change in distribution of calculated CH₄ emissions, i.e., the variance decreased. Effects of data resolution were examined by interpolating soil properties to derive data at different data resolutions and then calculating CH₄ emissions by applying the process-based model at these resolutions. The soil properties did not differ significantly for different data resolutions, in contrast to calculated CH₄ emissions. These scaling effects were caused by the combination of interpolation and a non-linear model. Real scaling effects may even be larger because small-scale variability was not accounted for. Scaling effects, including those caused by small-scale variability, have to be considered to achieve unbiased and less uncertain global CH₄emissions estimates from rice paddies.