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11.
空间插值算法在GIS中的应用 总被引：2，自引：0，他引：2
在GIS的研究中,通常需要具有一定规则的数据,而多数可获得的数据都是呈现离散状态并且是不规则分布的,这就需要应用空间插值的方法把离散的不规则数据转换成规则数据.本文介绍了几种常用的空间插值模型的原理与方法,并通过规则格网DEM的建立,说明空间插值算法在GIS中的应用. 相似文献
12.
Reference evapotranspiration (ETo) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ETo assessment at the regional scale is complicated by the limited number of weather stations and the strict requirements in terms of their location and surrounding physical conditions for the collection of valid weather data. In an attempt to overcome this limitation, new approaches based on the use of remote sensing techniques and weather forecast tools have been proposed.Use of the Land Surface Analysis Satellite Application Facility (LSA SAF) tool and Geographic Information Systems (GIS) have allowed the design and development of innovative approaches for ETo assessment, which are especially useful for areas lacking available weather data from weather stations. Thus, by identifying the best-performing interpolation approaches (such as the Thin Plate Splines, TPS) and by developing new approaches (such as the use of data from the most similar weather station, TS, or spatially distributed correction factors, CITS), errors as low as 1.1% were achieved for ETo assessment. Spatial and temporal analyses reveal that the generated errors were smaller during spring and summer as well as in homogenous topographic areas.The proposed approaches not only enabled accurate calculations of seasonal and daily ETo values, but also contributed to the development of a useful methodology for evaluating the optimum number of weather stations to be integrated into a weather station network and the appropriateness of their locations. In addition to ETo, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study. 相似文献
13.
This article evaluates different spatial interpolation methods for mapping submerged aquatic vegetation (SAV) in the Caloosahatchee Estuary, Florida. Data used for interpolation were collected by the Submersed Aquatic Vegetation Early Warning System (SAVEWS). The system consists of hydro-acoustic equipment, which operates from a slow-moving boat and records bottom depth, seagrass height, and seagrass density. This information is coupled with geographic location coordinates from a Global Positioning System (GPS) and stored together in digital files, representing SAV status at points along transect lines. Adequate spatial interpolation is needed to present the SAV information, including density, height, and water depth, as spatially continuous data for mapping and for comparison between seasons and years. Interpolation methods examined in this study include ordinary kriging with five different semivariance models combined with a variable number of neighboring points, the inverse distance weighted (IDW) method with different parameters, and the triangulated irregular network (TIN) method with linear and quintic options. Interpolation results were compared with survey data at selected calibration transects to examine the suitability of different interpolation methods. Suitability was quantified by the determination coefficient (R2) and the root-mean-square error (RMSE) between interpolated and observed values. The most suitable interpolation method was identified as the one yielding the highest R2 value and/or the lowest RMSE value. For different geographic conditions, seasons, and SAV parameters, different interpolation methods were recommended. This study identified that kriging was more suitable than the IDW or TIN method for spatial interpolation of all SAV parameters measured. It also suggested that transect data with irregular spatial distribution patterns such as SAV parameters are sensitive to interpolation methods. An inappropriate interpolation method such as TIN can lead to erroneous spatial representation of the SAV status. With a functional geographic system and adequate computing power, the evaluation and selection of interpolation methods can be automated and quantitative, leading to a more efficient and accurate decision. 相似文献
14.
15.
本文提出了两种情况下主动源数据和被动源数据的插值方法,并研究了两种数据在偏移成像中的互补效果.基于互相关法被动源数据重构原理,本文提出了结合多域迭代去噪技术的重构方法.提出了两种时间域主动源和被动源数据的插值方法,分别是共炮点域能量匹配插值和共检波点域最小平方匹配插值.然后对获得的主动源和被动源联合地震数据进行叠前深度偏移成像.在被动源活跃度不是很高的地区进行被动源地震勘探时,少量的主动源地震数据可以有效控制和补充被动源数据的成像效果.在稀疏炮点的主动源勘探中,有效利用被动源的信息能够在成像中增加更多的细节信息,提高成像质量. 相似文献
16.
高度计波高数据同化对印度洋海域海浪模式预报影响研究 总被引：1，自引：0，他引：1
为提高海浪模式预报的精度,改善初始场是途径之一。研制了基于最优插值(OI)方法的海浪数据同化并行程序模块,并将其植入第三代海浪模式WAVEWATCH IIITM,建立了印度洋海域海浪同化预报方法,使用卫星高度计波高数据进行了同化预报试验。OI模块的并行设计使得植入同化模块的海浪模式仍能以并行方式运行。文中5°S以北印度洋海域为目标区域,嵌套在WAVE-WATCH IIITM的全球网格中,使得目标区域开边界条件得到较好解决。同化数据使用Jason-2高度计测量有效波高(SWH)沿轨数据。海浪同化预报模式由大气模式WRF(Weather Research andForecasting)输出的1小时一次的海面10 m风场驱动。将同化的模式结果(SWH)、无同化的模式结果(SWH)分别与高度计沿轨数据(SWH)进行比较,表明同化改善模式预报初始场的效果是明显的。以同化初始场出发进行海浪预报试验,结果表明,高度计波高数据同化在一定程度上可改进海浪短期预报的精度。 相似文献
17.
This article presents an application of a procedure to modify the intensity distribution by assessing the reliability. There are two potential possibilities that may influence the intensity distribution: (1) For the interpolation error, we generate a measured grid across the calculation region. When the point to station spacing is <5 km, we consider the results precise; however, some points have less precision because these are farther from the corresponding stations. When the spacing is between 5 and 50 km, we consider the results imprecise and define a reliability factor that correlates with the distance. (2) Some records may have errors that result from local site conditions, equipment problems, or some disturbance such as lightning stroke, which will lead to some grid points having an incorrect intensity. We regress the attenuation relation for sites with abnormal intensities and consider the results to be accurate when the standard deviation (STD) is <σ and inaccurate when the STD is > 2σ. We then define a reliability factor to correlate with STD between σ and 2σ, such that the intensity distribution is in accord with both wave propagation theory and the investigation intensity. 相似文献
18.
气象要素是资源、环境、灾害以及全球变化等领域研究的数据基础,格点化数据在未来研究应用中显得日益重要。本文基于中国境内667个基本和基准地面气象观测站点的基本气象资料,使用ANUSPLIN专用气候插值软件对1961-2006年逐日气温、降水进行插值,并利用未参与插值的全国1667个加密站点对插值结果的准确性进行检验,同时与反向距离权重法和普通克吕格法等插值方法的结果进行对比。结果表明,利用667个站点使用ANUSPLIN软件进行逐日平均气温插值有92.0%的误差在2.0℃以内,75.0%的误差在1.0℃以内,0.9%的误差在5.0℃以上,平均绝对误差为0.8℃;对逐日降水进行插值,75.0%的误差小于5.0mm,85%的误差小于10.0mm,平均绝对误差为6.4mm,误差大小与降水量呈现出正相关性,对局地强降水的插值效果不好,这可能与参与局部拟合插值的样本数太少有关;同时,夏季的温度插值误差小于冬季,而冬季的降水误差小于夏季。将ANUSPLIN的局部薄盘样条插值结果分别与反向距离权重法和普通克吕格法的插值结果进行对比,显示ANUSPLIN软件的插值误差最小。结果同样表明,适当增加站点数量和提高DEM精度可进一步提高ANUSPLIN软件的插值精度。 相似文献
19.
古尔班通古特沙漠南缘主要土壤化学特征的空间异质性 总被引：4，自引：2，他引：2
运用半方差分析和Kriging插值研究了古尔班通古特沙漠南缘典型沙垄至垄间地浅层土壤(0～30 cm)pH值、电导率、有机质及全N含量的空间变异特征。结果表明,土壤pH值、有机质及全N含量服从正态分布,电导率符合对数正态分布。半方差分析结果显示,土壤pH值、电导率符合球状模型,而有机质、全N含量符合高斯模型。除全N具有中等空间相关性外,其余的都具有强空间相关性。用Kriging插值法对未测点的参数含量进行最优估计,绘制含量分布图,从而更直观地反映研究区土壤参数空间变异特征。 相似文献
20.
为高分辨率气候模式检验等的需要,基于2400余个中国地面气象台站的观测资料,通过插值建立了一套0.25°×0.25°经纬度分辨率的格点化数据集(CN05.1).CN05.1包括日平均和最高、最低气温,以及降水4个变量.插值通过常用的"距平逼近"方法实现,首先将计算得到的气候平均场使用薄板样条方法进行插值,随后使用"角距权重法"对距平场进行插值,然后将两者叠加,得到最终的数据集.将CN05.1与CN05、EA05和APHRO三种日气温和降水资料(四种资料的分析时段统一为1961-2005年)进行对比,分析了它们对气候平均态和极端事件描述上的不同,结果表明几者总体来说在中国东部观测台站密集的地方差别较小,而在台站稀疏的西部差别较大,相差最大的是青藏高原北部至昆仑山西段等地形起伏较大而很少或没有观测台站的地方,反映了格点化数据在这些地区的不确定性,在使用中应予以注意. 相似文献