基于变异函数的云南县域经济空间变异研究

从云南省县域经济的人均国内生产总值人手,在云南省129个县2000～2007年人均GDP及人均纯收入数据与空间地理位置坐标的基础上,运用变异函数的理论和方法,计算县域经济相关指标的变异函数,并根据相关方法拟合成球状模型的变异函数,最后结合云南县域的情况和变异函数图进行分析,为云南县域经济的发展提供支持.     

Spatial Dependence of Check Plot Yield and Local Control

For maximizing genetic gains, with given resources, plant breeders generally conduct large but un- or inadequately-replicated field trials especially during early generation evaluations and population improvement programmes. Checks arc often used to improve the precision of test plot comparisons. Adjustments by moving or weighted means etc. arc, however, empirical or based on assumptions too difficult to verify. An alternative stochastically best linear unbiased optimal locally weighted method of spatial prediction of micro-environmental heterogeneity indices of treatment plots was examined. Two checks used in an unreplicated evaluation of 1560 test lines of winter wheat expressed the micro-environmental variation in similar ways. About 46, 38 and 16 percent of the total variation in yield was a simple row and column effects, spatially dependent, and random errors, respectively. Optimal weights derived to simulate the micro-environmental heterogeneity indices were sensitive to the position of the test plot and thus provided a better local control. The model was validated, and prediction standard deviations of simulations computed.     

水稻遥感识别偏差修正的地统计学方法

为了进一步提高农作物遥感识别精度,充分利用高分辨率遥感影像上不同地物之间的邻域空间关系,提出农作物遥感识别偏差修正的地统计学方法。该方法综合考虑目标地物的光谱特征与空间信息,以类别隶属度偏差为研究对象,首先利用类别指示向量和类别后验概率向量之间的差异实现目标地物的类别隶属度偏差量化,然后对训练样本的类别隶属度偏差进行变异函数建模,并采用带局部均值的简单克里格插值方法预测总体类别隶属度偏差,之后用总体偏差的预测值对光谱分类所得的类别后验概率进行修正,重新确定识别结果,实现农作物遥感识别的偏差修正。以安徽省南部的一景 SPOT-5影像覆盖范围为研究区,选择2块典型区域分别作为试验区和验证区,以一季稻和晚稻为目标农作物,以支持向量机作为光谱分类的分类器,建立了水稻遥感识别的偏差修正流程;采用地面实测数据对修正效果进行评估,并与最大似然分类、模糊分类和支持向量机分类的结果进行比较。试验结果表明,该方法的总体分类精度能够达到90%以上,与传统分类方法相比,总体精度提高了近14%;且该方法能够大幅提高一季稻和晚稻的生产者精度和用户精度,有效改善了研究区的水稻识别结果,可以为中国南方复杂种植条件下的水稻识别提供参考。     

不同样本数量下土壤属性空间预测比较

【目的】通过不同样本数量情形下土壤属性空间预测精度的对比,探讨样本数对预测精度的影响。【方法】以土壤有机质、土壤质量含水量、土壤速效钾和土壤有效锰4个土壤属性作为研究对象,采用矩量法（MoM）和有限最大似然法（REML）两种变异函数计算方法,对比分析在不同样本数情形下各土壤属性空间预测精度。【结果】（1）不论是利用MoM法还是REML法计算变异函数,样本点数从50增加到70,各土壤变量预测精度都有了明显提高;样本数从70逐步增加到150过程中,预测精度没有明显提高;（2）在不同样本数情形下,REML法相对于MoM法的预测精度的提高率具有明显的变化,而且在有些情况下,REML法的预测精度比MoM低,而且对于不同土壤变量,表现结果也不相同。【结论】样本数对土壤空间预测准确性具有显著影响,在本研究区域尺度下,当样本数小于70个时,无论用哪种变异函数计算方法进行预测,预测结果的可信度都比较低。     

Within and between-field spatial variation in soil phosphorus in permanent grassland

Soil phosphorus (P) concentrations above certain critical thresholds are a problem in many areas leading to its transport into surface and ground waters. Site-specific nutrient applications and the development of nutrient management plans for farms would help to optimize nutrient applications, meet crop requirements and take into consideration current soil nutrient status. In Northern Ireland, high concentrations of soil P are common, whereas low concentrations of soil potassium (K) and sulphur (S) have been reported in many silage fields. This study used grid and transect soil sampling to measure within- and between-field spatial variation in soil Olsen-P status across a 50-ha permanent grassland site used for silage production. Soil phosphorus indices ranged from Index 1 to Index 4 within single fields. The spatial patterns of soil P across fields suggested that there was scope for site-specific P fertilizer applications, with variable quantities of P being applied to different fields and within individual fields. Site-specific nutrient management has the potential to reduce excess P applications in some areas and avoid deficiencies in others, thereby minimizing environmental problems and optimizing yield.     

云南水稻灌溉定额与农业综合灌溉定额的空间变异性

水稻灌溉定额和农业综合灌溉定额相互关联,且具有空间连续性。该文以云南省水稻灌溉定额和农业综合灌溉定额为例,分析了其分布类型和空间变异结构,结果表明它们分别符合对数正态分布和正态分布,两者表现出较小的各向异性,结构性因素起主要作用,受地形地貌、气象、土壤等因素影响较大,它们的变异函数分别很好地符合球形模型和线性模型。通过协克里金法插值得到云南水稻灌溉定额和农业综合灌溉定额的空间分布。前者在全省分布复杂,受经纬度共同作用,而后者主要受纬度影响,表现出4个特征区带。     

Spatial heterogeneity of plant species on the windward slope of active sand dunes in a semi-arid region of China

Species richness and abundance are two important species diversity variables that have attracted particular attention because of their significance in determining present and future species composition conditions.This paper aims to explain the qualitative and quantitative relationships between species diversity pattern and grain size(i.e.size of the sampling unit),and species diversity pattern and sampling area,and to analyze species diversity variability on active sand dunes in the Horqin Sandy Land,northeastern Inner Mongolia,China.A 50 m×50 m sampling plot was selected on the windward slope,where the dominant species was annual herb Agriophyllum squarrosum.Species composition and abundance at five grain sizes were recorded,and the species-area curves were produced for thirteen grain sizes.The range of values for species abundance tended to increase with increasing grain size in the study area,whereas,generally,species richness did not follow this rule because of poor species richness on the windward slope of active sand dunes.However,the homogeneity of species richness increased significantly.With the increase in sampling area,species abundance increased linearly,but richness increased logarithmically.Furthermore,variograms showed that species diversity on the windward slope of active sand dunes was weakly anisotropic and the distribution pattern was random,according to the Moran Coefficient.The results also showed that species richness was low,with a random distribution pattern.This conflicts with the results of previous studies that showed spatial aggregation in lower richness in a sampling area within a community and inferred that the physical processes play a more important role in species diversity than distribution pattern on active sand dunes.Further research into different diversity patterns and mechanisms between active sand dunes and interdune lowlands should be conducted to better understand biodiversity conservation in sand dune fields.     

基于时空变异的地下水模拟参数插值研究

由于地下水的储藏与运行特性及实际条件的限制,在对其进行监测时往往只能得到有限的监测结果,因此需要借助已知点信息来对地下水污染物运移参数的空间分布特性进行估计,着重阐述了浅层地下水环境评价指标的时空变异性,通过实验模拟水质指标在浅层地下水非均质环境中的运移,分析了示踪剂氯离子迁移过程中浓度变化的各向异性,进行了空间点去除率为33%和50%条件下的时空协同克里格估值;结果表明,在其他时刻只有参估点时间信息而无待估点时间信息,无论待估点的多寡,时空协同克立格估计效果相比普通克立格基本相当,证明了建立在地下水环境评价变量随机性空间统计分析基础之上的协同克里格最优估计方法切合实际,具有一定的实用价值。     

地质统计学评估伊朗伊斯法罕城市采矿过渡区近地表土壤上铅锌镉的污染

Due to the lack of regulation and environmental education and awareness, Sepahanshahr located in vicinity of Isfahan City, central Iran, is now a rapid growing residential area suffering from the considerable consequences of poorly regulated mining activities operating in its vicinity. A survey was carried out on soil Pb, Zn and Cd concentrations around Sepahanshahr Town to explore the spatial structure of Pb, Zn and Cd distribution and to map their concentrations using geostatistical techniques. 100 near-surface soil samples were collected and analyzed for Pb, Zn and Cd and some related soil physical and chemical variables such as pH, organic matter content, electrical conductivity, and clay, silt and sand contents. The variography results showed a strong spatial dependency in heavy metals concentration due to the dilution effects of natural factors including atmospheric dispersion and precipitation. The almost same range values calculated for both ln-transformed Pb and sand data suggested presence of spatial co-regionalization. However, ln-transformed Zn data showed a shorter spatial dependency among the three tested heavy metals. Kriged maps of all three heavy metals showed a strong gradient of contamination around the three mining sites activating in the area. The results of this study provide insight into identification of the extent and spatial variability of Pb, Zn and Cd pollution in the mining sites and surrounding urban areas.     

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site‐specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (EC_a) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and EC_a. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.