一种改进的生成区域日降水场的方法及精度分析

利用全国687个气象站点11年的日降水数据,对基于地理特征和统计回归的函数拟合类模型DAYMET生成中国区域日降水场的能力进行了验证。交叉验证表明,DAYMET模型估计日降水累计得到的年降水量的绝对偏差11年平均为29.8%,年降水总量估计偏差低于20％的站点占48.3％。鉴于中国陆地区域降水深受季风的影响,不同方位气象站点对插值点的影响也有所不同,引入了站点不同方位对插值的影响权重,对DAYMET模型进行了改进,改进后年降水量的绝对偏差降为27%。与梯度距离平方反比法相比,该方法具有较高的区域降水插值精度。还以无定河流域降水插值为例,说明降水插值精度的高低与区域内雨量站点的多寡紧密相联。     

基于ε-Voronoi图的矢量数据自适应简化方法

针对矢量数据简化的问题,提出一种基于帧缓存和四叉树索引的自适应简化方法,即采用四叉树索引对矢量数据进行区域划分,通过评价各个区域地物实体分布密度的指标,判断各个区域内的矢量数据密度、图幅宽度,得到各区域ε-Voronoi图中的ε值,再借助帧缓存技术,自适应地简化各个区域内的矢量数据。实验表明,该方法一定程度上提高了简化质量,为矢量数据可视化应用提供一定的基础。     

干旱沙区陆面蒸散量与土壤水分关系的数值计算

利用电子称重式蒸渗仪（Ｌｙｓｉｍｅｔｅｒ）测定田间蒸散量（ＥＴ），并用中子水分仪同步测定沙面下１０～１５０ｃｍ土壤水分含量，求得含水率Ｗ（％）。通过研究沙区不同植被区域内，土壤剖面不同深度土体含水率Ｗ与ＥＴ的关系，估算出了三种处理（油蒿栽植区、柠条栽植区、裸露沙区）的不同深度土壤水分对蒸散过程的贡献值，模拟出了土壤含水量对区域陆面蒸散量的相关关系式     

1951-2010年中国季平均降水高精度曲面建模分析

利用1951-2010年中国711个气象观测站的月降水资料,对多年季平均降水根据中国农业气候类型进行分区模拟。针对中国降水特点,首先分析了影响各分区降水的地理、地形因素及局部地形因素,利用多项式回归和逐步回归的方法对各分区降水进行了趋势拟合;在此基础上,采用改进的高精度曲面建模(HASM)方法,对各模拟区域去掉趋势后的残差进行迭代修正,并比较验证了模拟效果。同时,为保证HASM在边界附近的模拟精度,根据区域内站点间的距离,对每一分区设置一个缓冲区,将HASM实际插值区域扩展为缓冲区内的部分。模拟结果表明:HASM方法的模拟精度在不同区域不同季节内均比经典的插值方法模拟精度高。利用上述方法分析了同一季节各分区降水的分布特点,并模拟了不同季节内多年平均降水的空间分布状况,模拟结果符合我国降水的实际分布特点。     

基于GIS的侵蚀冲沟与地貌因子的关系

冲沟是多种外力作用的结果,展示为多种地貌现象。选择胶东半岛北岩子口小流域作为研究对象,以正射影像（DOM）和数字高程模型（DEM）为数据源,选择土地利用、地形湿度指数、坡度坡长因子、水流动力指数、坡向、平面曲率和地表粗糙度等7个地貌因子,计算小流域土壤侵蚀敏感性,研究侵蚀冲沟与地貌因子的关系。结果表明:冲沟多发生在坡度坡长较大、水流动力强、地表湿度较低的林草地区域,多分布在阳坡的凹面;冲沟大多分布在土壤侵蚀中等敏感性及以上的区域,约占总冲沟的96.4%;在土壤侵蚀中等敏感性及以上区域,实验权重值对验证区冲沟分布的响应精度为87.9%,与实际值93.3%相差较小,精度较高。研究结果可为区域内冲沟侵蚀的评价提供一定科学依据。     

西部边疆旅游城市功能区空间集聚模式——以云南省丽江市为例

以丽江市古城区与玉龙纳西族自治县为研究区域,基于丽江市POI数据,采用土地利用混合度熵值、行业地区集中度指数作为研究指标,用ArcGIS,MATLAB等提取旅游城市的空间格局及行业分布特征。结果表明:丽江市形成“以人文景点为导向”的城市空间格局,景点周围区域以不同比例分布着与旅游产业关联性显著的商业、公共服务;与旅游产业相关的住宿、餐饮集聚程度最高,行业集中度指数分别为0.97(住宿)、0.96(餐饮);区域内住宿、餐饮服务对景点的依附程度高,并且高度集聚于丽江古城周围区域,区域内98.7%的住宿服务、97.5%的餐饮服务均分布在以丽江古城所在地为中心、半径为10 km的区域内。     

武汉城市圈省级经济开发区土地集约利用水平比较研究

在开发区土地集约利用评价的基础上,对一定区域内的同类型开发区土地集约利用水平进行统一比较,以期为相关部门提供区域开发区土地集约利用水平评价工具和制定科学管理政策的决策依据。对武汉城市圈内省级经济开发区的实证分析显示,综合采用统一理想值法和灰色关联分析法对现有开发区土地集约利用评价成果进行再处理后,可以实现对区域范围内各开发区土地利用集约程度的评价及排序,并可以侦测出不同指标对区域内开发区土地集约利用的影响程度。因此,在利用政策工具提高一定区域内开发区土地管理水平时,应以不同类型的指标对土地利用集约度影响程度作为决策依据。     

基于GIS的农业气候资源区域化问题研究——以甘肃省为例

在农业气候资源研究中,站点数据的区域化问题是进行资源优化配置和高效利用的一个重要环节。通过采用逐步回归分析与空间插值相结合的方法,以甘肃省及其相邻省区的112个站点1970~2001年31年的月平均温度和降水数据以及计算得到的月平均太阳辐射和潜在蒸散量为数据源,对甘肃省气候资源进行了区域化。对每种气象要素都采用了两种空间插值方法,并对插值结果运用了绝对验证和相对验证两种方法进行了验证和对比。结果表明:温度残差的平均绝对误差(MAE)是Spline< IDW, 其值分别为:0.744℃和0.754℃,平均相对误差(RME)分别为:9.56%和9.66%。降水的平均绝对误差是Kriging温度>潜在蒸散量>降水,但都达到了较高的精度。     

基于能值分析与模糊评价的粮食主产区耕地健康评价——以石家庄市栾城县为例

粮食主产区耕地健康是事关粮食安全(产量与品质)的重要因素.该文在探讨耕地健康评价方法的基础上,结合粮食主产区的实际情况,以石家庄市栾城县为例,进行耕地健康评价实践研究.结果显示:研究区域耕地能值指数介于0.631～0.863,耕地健康模糊指数介于0.603～0.878,耕地健康综合指数介于0.531～0.753,分为很健康、健康和亚健康3个级别,其面积构成分别为7.6％、48.4％和44.0％,区域内耕地健康状况较好.研究表明:模糊评价与能值分析互为补充,建立耕地健康诊断指标体系与评价模型科学可行,可为不同区域开展耕地健康评价提供方法借鉴.     

广州中心城区基本医疗服务等级区域分布及其特征

以广州市最新一轮行政区划结果与医疗机构相关数据为基础,运用ARCGIS和SPSS软件,通过构建基本医疗服务优势度模型,对3项子指标(距离、质量、频率)在各个优势度等级区域进行对照分析.发现广州中心城区基本医疗服务等级区域分布具有如下特征:以老城区(越秀区、荔湾区、海珠区)组成团块状的高优势度区域为中心,优势度分值自中心向外围区域呈环状递减,且优势度高分值区域有向市区东部及北部延伸的趋势.基本医疗服务等级区域指标具有如下特征:①极高值区、高值区与极低值区3项子指标得分均衡;②中高值区、中值区和中低值区存在质量低下型特征,低值区尤甚:③在基本医疗服务良好区域,区域内医疗服务条件差异显著,具有距离低下型特征.     

Book reviews

A digital elevation model (DEM), which is used to represent a terrain surface, is normally constructed by applying an interpolation method on given sample elevation points. Interpolation methods can be classified into two classes: linear methods, which have a low time cost and are suitable for terrains where there is little change in elevation, and nonlinear methods, which normally consume comparatively more time and are more suitable for terrains where there are frequent changes in elevation. A hybrid interpolation method, which involves both a linear method and a nonlinear method of interpolation, is proposed in this paper. The proposed method aims to integrate the advantages of both linear and nonlinear interpolation methods for the refinement of regular grid DEM. Here, the bilinear is identified as the linear method, and the bi‐cubic is taken to be the nonlinear interpolation method. The hybrid method is an integration of a linear model and nonlinear interpolation model with a parameter that defines the weights for each of the models. The parameter is dependent on the complexity of the terrain, for which a DEM is to be interpolated. The experimental results in this study demonstrate that the hybrid method is effective for interpolating DEMs for various types of terrain.     

喀斯特地区春季土壤水分空间插值方法对比

以杨眉河小流域为研究区,通过土壤水分采样,选取辅助变量,采用普通克里金、协同克里金、回归克里金3种地统计学方法对土壤水分数据进行空间插值。结果表明：1）回归克里金对研究区土壤水分估算误差最小,其次为协克里金,普通克里金的误差最大;2）普通克里金生成的土壤水分表面最为平滑,而回归克里金最大程度反映了研究区实际的土壤水分空间变化;3）对于协同克里金,以湿度指数（WI）样点数据作为辅助变量的估算误差小于将WI栅格数据作为辅助变量的估算误差。总之,在可获得有效辅助变量的条件下,回归克里金对研究区土壤水分估算的效果优于协同克里金与普通克里金。     

基于DEM的中国陆地多年平均温度插值方法

以1961~2000年全国726个气象站点旬平均温度为基础数据,在分析了多年月平均温度和年平均温度的空间分布与经度、纬度、高度的内在关系后,提出了一种基于DEM和智能搜索距离的温度空间插值方法(SSI),并与反距离平方(IDS) 等传统方法进行了对比。交叉验证结果表明:1) 传统的IDS方法最优结果的MAE范围是1.44 oC~1.63 oC,平均1.510C;而SSI温度插值方法的平均绝对误差为0.53 oC~0.92 oC,平均值0.69 oC,精度超过IDS等方法一倍以上。2) 随着距离的增大,站点间温度的相关性逐渐降低,会降低估算精度;小于一定的搜索半径,被估算点周围的相邻站点的数目逐渐减少,同样会降低插值的精度,因而对中国陆地部分温度插值而言,最优的空间插值搜索半径介于150~250 km之间。最后,结合DEM数据,生成了0.1o ×0.1o中国陆地区域多年月平均和年平均温度栅格图像数据集,该结果表明:利用SSI方法不仅可以生成高精度、高空间分辨率的网格温度结果,而且其插值结果能客观细致的反映温度随经度、纬度和高度梯度变化的地带性特征。     

On the prediction error variance of three common spatial interpolation schemes

Three forms of linear interpolation are routinely implemented in geographical information science, by interpolating between measurements made at the endpoints of a line, the vertices of a triangle, and the vertices of a rectangle (bilinear interpolation). Assuming the linear form of interpolation to be correct, we study the propagation of error when measurement error variances and covariances are known for the samples at the vertices of these geometric objects. We derive prediction error variances associated with interpolated values at generic points in the above objects, as well as expected (average) prediction error variances over random locations in these objects. We also place all the three variants of linear interpolation mentioned above within a geostatistical framework, and illustrate that they can be seen as particular cases of Universal Kriging (UK). We demonstrate that different definitions of measurement error in UK lead to different UK variants that, for particular expected profiles or surfaces (drift models), yield weights and predictions identical with the interpolation methods considered above, but produce fundamentally different (yet equally plausible from a pure data standpoint) prediction error variances.     

自适应的IDW插值方法及其在气温场中的应用

反距离权重(Inverse Distance Weighting,IDW)插值通常采用距离搜索策略选择插值参考点,当采样点集分布不均匀时,距离搜索策略使得参考点聚集一侧影响插值精度。自然邻近关系具有良好的自适应分布特性,可有效地解决参考点分布不均匀问题。结合自然邻近关系,提出自适应的反距离权重(Adaptive-IDW,AIDW)插值方法。首先对采样数据构建初始Delaunay三角网,然后采用逐点插入法,将待插值点插入初始Delaunay三角网中,局部调整得到新的Delaunay三角网,以待插值点的一阶邻近点作为IDW插值的参考点,使参考点自适应均匀地分布在待插值点周围,再进行IDW插值计算。利用AIDW插值方法对Franke函数、全国气温观测数据进行插值实验,结果表明此方法具有较高的精度,且减少了“牛眼”现象。     

A Point-Based Intelligent Approach to Areal Interpolation

Areal interpolation is the data transfer from one zonal system to another. A survey of previous literature on this subject points out that the most effective methods for areal interpolation are the intelligent approaches, which often take two-dimensional (2-D) land use or one-dimensional (1-D) road network information as ancillary data to give insight on the underlying distribution of a variable. However, the 2-D or 1-D ancillary information is not always applicable for the variable of interest in a specific study area. This article introduces a point-based intelligent approach to the areal interpolation problem by using zero-dimensional (0-D) points as ancillary data that are locationally associated with the variable of interest. The connection between zonal variables and point locations can be modeled with a linear or a nonlinear exponential function, which incorporates the distribution of the variables in the transferring of the information from the source zone to the target zone. An experimental study interpolating the population data at a suburbanized area suggests that the proposed method is an attractive alternative to other areal interpolation solutions based on the evaluation of its resulting accuracy and efficiency.     

基于Kriging的地形高程插值

将地形高程作为区域化变量,根据普通Kriging法由散乱的高程点进行地形高程插值,并采用Matlab软件开发专门的程序,实现研究区高程插值计算与结果可视化分析。以广州市南沙区10 km2范围内的200个高程点数据为例,分别运用球面模型、指数模型和高斯理论变差函数模型进行10 m×10 m格网插值,借助Matlab可视化分析插值结果及其精度,表明采用指数模型效果最好。     

Surface modeling of DEMs based on a sequential adjustment method

A sequential adjustment (SA) method is employed to decrease the computational cost of high-accuracy surface modeling (HASM), and the SA of HASM (HASM-SA) is being developed. A mathematical surface was used to comparatively analyze the computing speed of SA and the classical iterative solvers provided by MATLAB 7.7 for solving the system of linear equations of HASM. Results indicate that SA is much faster than the classical iterative solvers. The computing time of HASM-SA is determined by not only the total number of grid cells but also the number of sampling points in the computational domain. A real-world example of surface modeling of digital elevation models (DEMs) with various resolutions shows that HASM-SA is averagely more accurate and much faster than the commonly used interpolation methods, such as inverse distance weighting (IDW), kriging, and three versions of spline, namely regularized spline (RSpline), thin-plate spline (TPS), and ANUDEM in terms of root mean square error (RMSE), mean absolute error (MAE), and mean error (ME). In particular, the ME of HASM-SA at different spatial resolutions is averagely smaller than those of IDW, kriging, RSpline, TPS, and ANUDEM by 85%, 83%, 83%, 53%, and 19%, respectively. The high speed and high accuracy of HASM-SA can be due to the absence of matrix inversion computation, combined with the perfect fundamental theorem of HASM.     

“Krige”空间内插技术在地理学中的应用

称为“Krige”技术的内插稀疏观测资料的随机方法是Matheron(1970年)提出的,D.R.Krige首先将这一方法应用于找矿上,因而命名于“Krige”技术。本文首先定义和说明了空间协方差曲线,基于无偏估计和最优原理导出了“Krige”内插权重系数的代数方程组,最后给出实例说明该方法如何应用到地理学和水文学中。     

Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods

Accurate estimations of spatio-temporal fields at unsampled locations are important in a number of applications. Often, spatio-temporal fields are advected, which means the change in field values over time at a particular point in space stems to a large extent from motion of a more or less constant spatial field. For such dynamic fields, interpolation methods including information on the motion behaviour of the field are promising extensions of solely spatial (snapshot) and symmetric spatio-temporal methods. In this paper, the performance of different deterministic and geostatistical interpolation methods is compared for precipitation estimation from 1-minute time series of spatially distributed rain gauges. The focus is on spatio-temporal methods that include information on the motion behaviour of the rainfield, estimated from weather radar using optical flow. The different interpolation methods are introduced and evaluated using rain gauge measurements of a 15-day period and cross-validation. The results show that including information on the motion behaviour significantly improves interpolation quality in terms of RMSE.