Assessing reference evapotranspiration at regional scale based on remote sensing,weather forecast and GIS tools

Reference evapotranspiration (ET_o) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ET_o 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 ET_o 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 ET_o 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 ET_o 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 ET_o, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study.     

Mapping Submerged Aquatic Vegetation with GIS in the Caloosahatchee Estuary: Evaluation of Different Interpolation Methods

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.     

Modifying the intensity distribution by assessing the reliability

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.     

基于ANUSPLIN软件的逐日气象要素插值方法应用与评估

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。     

古尔班通古特沙漠南缘主要土壤化学特征的空间异质性

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。     

Bi-cubic interpolation for shift-free pan-sharpening

Most of pan-sharpening techniques require the re-sampling of the multi-spectral (MS) image for matching the size of the panchromatic (Pan) image, before the geometric details of Pan are injected into the MS image. This operation is usually performed in a separable fashion by means of symmetric digital low-pass filtering kernels with odd lengths that utilize piecewise local polynomials, typically implementing linear or cubic interpolation functions. Conversely, constant, i.e. nearest-neighbour, and quadratic kernels, implementing zero and two degree polynomials, respectively, introduce shifts in the magnified images, that are sub-pixel in the case of interpolation by an even factor, as it is the most usual case. However, in standard satellite systems, the point spread functions (PSF) of the MS and Pan instruments are centered in the middle of each pixel. Hence, commercial MS and Pan data products, whose scale ratio is an even number, are relatively shifted by an odd number of half pixels. Filters of even lengths may be exploited to compensate the half-pixel shifts between the MS and Pan sampling grids. In this paper, it is shown that separable polynomial interpolations of odd degrees are feasible with linear-phase kernels of even lengths. The major benefit is that bi-cubic interpolation, which is known to represent the best trade-off between performances and computational complexity, can be applied to commercial MS + Pan datasets, without the need of performing a further half-pixel registration after interpolation, to align the expanded MS with the Pan image.     

Applying essentially non‐oscillatory interpolation to controlled‐source electromagnetic modelling*

Modelling and inversion of controlled‐source electromagnetic (CSEM) fields requires accurate interpolation of modelled results near strong resistivity contrasts. There, simple linear interpolation may produce large errors, whereas higher‐order interpolation may lead to oscillatory behaviour in the interpolated result. We propose to use the essentially non‐oscillatory, piecewise polynomial interpolation scheme designed for piecewise smooth functions that contains discontinuities in the function itself or in its first or higher derivatives. The scheme uses a non‐linear adaptive algorithm to select a set of interpolation points that represent the smoothest part of the function among the sets of neighbouring points. We present numerical examples to demonstrate the usefulness of the scheme. The first example shows that the essentially non‐oscillatory interpolation (ENO) scheme better captures an isolated discontinuity. In the second example, we consider the case of sampling the electric field computed by a finite‐volume CSEM code at a receiver location. In this example, the ENO interpolation performs quite well. However, the overall error is dominated by the discretization error. The other examples consider the comparison between sampling with essentially non‐oscillatory interpolation and existing interpolation schemes. In these examples, essentially non‐oscillatory interpolation provides more accurate results than standard interpolation, especially near discontinuities.     

天津滨海新区潜在淹没区发展趋势研究

本文利用2006年以前天滓地面沉降监测资料和塘沽、汉沽地区潜在淹没区RTK加密观测资料,以水准监测点为基本研究对象,深入分析研究了每个测点随时间的沉降变化规律,进而“以点带面”绘制了2005年和2011年天津滨海新区地面沉降速率等值线图。同时,还绘制了2005年塘沽、汉沽地区潜在淹没区地面标高等值线分布图,以及预测的2011年塘沽、汉沽地区潜在淹没区的时空分布和面积。最后,提出了应对地面沉降的相关建议,以供政府控制地面沉降时参考。     

Mapping radar-derived sea surface currents with a variational method

High-frequency radars measure projections of surface velocity vectors on the directions of the radar beams. A variational method for reconstruction of the 2d velocity field from such observations is proposed. The interpolation problem is regularized by penalizing high-frequency variability of the surface vorticity and divergence fields. Twin-data experiments are used to assess the method's skill and compare it with two well-known approaches to HFR data processing: conventional local interpolation and more sophisticated non-local scheme known as open-boundary modal analysis (OMA). It is shown that the variational method and OMA have a significant advantage over local interpolation because of their ability to reconstruct the velocity field within the gaps in data coverage, near the coastlines and in the areas covered only by one radar. Compared to OMA, the proposed variational method appears to be more flexible in processing gappy observations and more accurate at noise levels below 30%.     

利用随机天气模式及多种插值方法生成逐日气候变化情景的研究

针对目前大气环流模式在用于气候变化影响评估研究中时间分辨率较低的局恨性, 以及气候情景的要求和气候变化影响研究的需要, 结合GCM的模拟试验结果, 利用随机天气模式WGEN生成了中国东北地区未来气候变化的逐日情景, 其中包含了可能的气候变率信息, 可与作物动力模式等气候影响模式嵌套, 研究作物生长发育及其产量的可能变化, 及气候变率变化的可能影响等.