南方丘陵山区典型地物景观特征尺度研究

景观的特征尺度反映了人与自然交互作用的空间过程,合理识别景观空间结构及其特征尺度有助于遥感影像景观空间异质性分析。论文以地处南方丘陵山区的福建省福州市为研究区,针对城市、农田、森林与水域4种地物景观,基于SPOT 10 m影像,分别利用半方差分析、小波分析与平均局部方差方法,开展景观特征尺度研究。结果表明:①不同景观类型的空间异质性差异较大,其中森林景观空间异质性最大,其次为城市、农田景观,水域的空间异质性最小;②小波方差分析和半方差分析分别检测到两个不同的特征尺度,而局部方差仅仅检测到较小的空间结构;③森林景观特征尺度比通常偏小,与南方丘陵山区破碎地形有关,城市景观更多体现为人类活动的影响,南方丘陵山区城市景观至少具有两种不同的空间结构,其特征尺度均较小,农田景观特征尺度最大。基于小波分析与半方差各自的特点,总结提炼出综合两种方法合理识别景观特征尺度的基本流程,即:首先开展小波分析,然后在此基础上利用半方差分析多种理论模型组合从而获得更详细的特征尺度信息,模型组合个数与参数初始值依据小波分析的结果而定。     

Utility of semivariogram for spatial variation of soil nutrients and the robust analysis of semivariogram

ＩｎｔｒｏｄｕｃｔｉｏｎＧｅｏｓｔａｔｉｓｔｉｃｓｈａｓｐｒｏｖｅｎｕｓｅｆｕｌｆｏｒｃｈａｒａｃｔｅｒｉｚｉｎｇａｎｄｍａｐｐｉｎｇｔｈｅｓｐａｔｉａｌｖａｒｉａｔｉｏｎｏｆｓｏｉｌｐｒｏｐｅｒｔｉｅｓ (Ｗｅｂｓｔｅｒ,1985;Ｔｒａｎｇｍａｒ,1985;Ｇｏｏｖａｅｒｔｓ ,1999) .Ｍｏｓｔｐｒｅｖｉｏｕｓｇｅｏｓｔａｔｉｓｔｉｃａｌｓｔｕｄｉｅｓｆｏｃｕｓｅｄｏｎｔｈｅｄａｔａｏｆａｒｅｌａｔｉｖｅｌｙｓｍａｌｌｓｐａｔｉａｌｓｃａｌｅ(Ｃｈｉｅｎ ,1997) .Ｔｈｅａｐｐｌｉｃａｔｉｏｎｏｆｇｅｏｓｔａｔ…     

五道梁高寒草原土壤水分和植被盖度空间异质性的地统计分析

青藏高原高寒草原区,由于长期冻融和地下冰的存在形成了独特的生态水文结构,土壤水分是控制高寒草原生态过程的关键因子。利用地统计学对多年冻土区高寒草原土壤表层含水量和植被盖度的空间变异性进行研究,结果表明,高寒草原生态系统浅层剖面(0~50 cm)土壤水分和植被盖度均符合正态分布,土壤含水量沿垂直方向逐渐增大,介于19.43%~25.37%之间,变异系数介于23.77%~40.92%;植被盖度具有强变异性,变异系数为47.99%。0~50 cm土壤含水量具有高度的空间异质性,其中91.1%的空间异质性是由空间自相关部分引起的,主要体现在10~190 m的中尺度上;植被盖度在研究尺度上具有中等程度的空间自相关,植被盖度随机部分的空间变异性占总空间变异性的比例为34.2%,主要体现在10 m的尺度内。各向异性分析表明,土壤水分和植被盖度具有明显的各向异性,其空间格局有明显的差异。     

基于时空地质统计学的滇池水质时空分布模拟

使用滇池水域10个观测站（外海8个,草海2个）上TN、TP、CODMn、DO、BOD、叶绿素a等6个指标在2a间（2005～2006）每个月的观测数据,利用时空地质统计学计算了各指标的时空变异函数和进行了普通克立格估值。从结果来看,时空变异函数可以较好地刻划环境变量与时空变化之间的关系,能更精确地估计环境变量在时间和空间的分布。从各水质指标的模拟结果来看,滇池的污染严重区域主要为北部的昆明城区、东北部的呈贡、东部的大渔地区。     

城市污泥与猪粪混合堆肥过程中湿度空间变异

对城市污泥与猪粪混合堆肥过程中堆体内湿度的空间变异性进行了研究 ,利用克里格法对湿度进行最优插值 .结果发现 :不同堆肥期湿度半变异函数在堆体水平方向上用对数函数拟合效果较好 ,在垂直方向上用线性函数拟合效果较好 .升温期、降温期和腐熟期各剖面的等湿线呈不同的分布特征 ,高温期呈较规则的“拱形”分布 .升温期、高温期及腐熟期 ,仓门附近的湿度变化较大 ,降温期堆体中轴线附近的湿度变化较大 .升温期堆体湿度最佳 ,从高温期开始 ,堆体中下部出现高湿区 ,且不断缩小 ;同时 ,堆体的顶部和两侧壁出现低湿区 ,且向堆体的中下部扩大 .由升温期到降温期 ,湿度空间变异不断增大 ,但腐熟期开始减小 .最后讨论了形成湿度空间变异的原因 ,并提出相应提高堆肥效率和质量的措施 .     

安徽省2017—2018年PM2.5浓度时空分异特征

以2017—2018年安徽省133个空气质量监测站（国控点66个,省控点67个）228万条PM_2.5质量浓度数据为基础,基于空间自相关和地统计方法对该区PM_2.5浓度的时空分异特征进行分析。结果显示：安徽省年平均PM_2.5质量浓度为49.63 μg/m³,88%的监测站点PM_2.5质量浓度超过国家环境空气质量标准二级限值;PM_2.5浓度呈现明显的冬季高、夏季低、春秋季适中的特征,日变化曲线呈双峰结构,峰值在09：00和22：00前后,低值在16：00—17：00;全省PM_2.5浓度全局Moran指数为0.673 6,月度指数为0.389 6~0.745 6,均表现为空间聚集性,且冬季PM_2.5浓度的空间聚集性更强;局部空间自相关指数表明全省PM_2.5浓度呈西北高-高集聚、东南低-低集聚的特点,低值集聚区稳定在黄山市及其周边;全省PM_2.5浓度总体表现为由北向南递减的趋势,但受局部地形的影响,PM_2.5浓度在西部大别山和皖南山区出现明显的下降趋势。研究结果综合了国控点和省控点监测数据,更加详细地表征区域PM_2.5浓度的时空分异特征,为该区实施有效的环境污染防控提供重要参考。     

Chemometric characterization of soil and plant pollution: Part 1: Multivariate data analysis and geostatistical determination of relationship and spatial structure of inorganic contaminants in soil

Geostatistical and multivariate methods of data analysis are used to describe patterns of soil pollution with inorganic contaminants in Celje County, Slovenia. Groups of contaminants and polluted sites were identified using cluster analysis and confirmed with multidimensional variance and discriminant analysis. Factor analysis yields an identification of not directly observable relationships between the contaminants. The spatial structure and distribution of contaminants were assessed by applying semivariogram analysis and kriging interpolation method. Zinc, Cd and Cu were identified as a pollutant emitted from the zinc smelter, Pb also from other sources, and Cr and Ni mostly from geological parent material.     

Spatial variability of sydney air quality by cumulative semivariogram

This paper establishes that an isotropic spatial correlation function in the form of a modified Bessel function of the second kind, first order, can be used to model the spatial variability of a pollution concentration field over a sufficiently long period of time in which the variability due to meteorological factors has been smoothed out. The corresponding cumulative semivariogram is derived and fitted by nonlinear least-squares to monthly averaged ozone data at 18 monitoring stations of the Sydney region. The good fit of the model indicates that the Sydney airshed has homogeneous and isotropic subregions whose radius of influence is about 17 km. The Bessel function form of the spatial correlation has a physical meaning as it is derived from the diffusion equation; hence, it is expected that the model can be used, in general, to represent the spatial variability of a smoothed homogeneous and isotropic concentration field.     

地球化学分散模式分维计算方法的探讨

用半变异函数法、关联维法和三棱柱法对新疆东准噶尔金、银贵金属成矿区内卡拉麦里一带Au、As原生晕数据的空间结构性进行了研究 ,结果显示 ,Au、As元素在不同方向上的分维值变化情况与区域上的构造控矿特征相吻合 ;就区域上而言 ,As比Au的空间分布更复杂些。此外 ,对三种分维计算方法各自的优、缺点和实用性进行了探讨 ,并指出了分形地球化学的找矿意义     

Spatial error propagation when computing linear combinations of spectral bands: The case of vegetation indices

The collection of accurate and timely information on land use, crops, forest and vegetation are increasingly based on remote sensing spectral measurements produced by satellites. The most recent spacecrafts like the Earth Observing 1 (EO-1) produce a rich source of information being endowed with hyperspectral sensors that can provide up to 200 or more channels. In many instances such a multivariate signal has to be reduced to just one single value per pixel representing a particular characteristic of land. Linear combinations of bands are the general form of many indices. Since each individual image used to construct indices contains errors, when combined they produce a propagation of errors, a process that can distort a final output map. In this paper we measure the extent of error propagation when building linear vegetation indices. We consider three types of indices: the difference vegetation index (DVI), selected Kauth-Thomas indices (SBI, GVI and WET), and principal components, using benchmarking examples taken from the remote sensing literature. The main implication emerging from these examples is that the SBI and the first principal component are the indices more prone to error propagation. The formalization presented here allows a user to derive measures of error propagation in cases where technical characteristics of a sensor and physical characteristics of a landscape are known. These results can help a user to choose between alternative vegetation indices, and to associate a measure of reliability with such indices.