Effects of laser beam alignment tolerance on lidar accuracy

One of the major lidar error sources not yet analyzed in the literature is the tolerance of the laser beam alignment with respect to the scanning mirror. In this paper, the problem of quantifying these errors is solved for rotating polygon mirror type lidar systems. An arbitrary deviation of the beam from its design direction–the vector of beam misalignment–can be described by two independent parameters. We choose these as horizontal and vertical components of the misalignment vector in the body frame. Either component affects both, horizontal and vertical lidar accuracy. Horizontal lidar errors appear as scan line distortions—along and across track shifts, rotations and scaling. It is shown that the horizontal component of misalignment results in a scan line first being shifted across the track and then rotated around the vertical at the new center of the scan line. Resulting vertical lidar error, being a linear function of the scan angle, is similar to that produced by a roll bias. The vertical component of the beam misalignment causes scan line scaling and an along track shift. The corresponding vertical error is quadratic with respect to the scan angle. The magnitude of these effects is significant even at tight alignment tolerances and cannot be realistically accounted for in the conventional calibration model, which includes only range, attitude and GPS biases. Therefore, in order to attain better accuracy, this model must be expanded to include the beam misalignment parameters as well. Addition of new parameters into the model raises a question of whether they can be reliably solved for. To give a positive answer to this question, a calibration method must utilize not only ground control information, which is typically very limited, but also the relative accuracy information from the overlapping flight lines.     

Performance of the electrochemical ozone sonde OSR

Summary The accuracy of the electrochemical ozone sonde, type OSR, has been estimated by analysing tandem ozone soundings of the balloon-borne electrochemical ozone sonde OSR at the Lindenberg Observatory from May to November 1982. A negative bias, though not significant, has been observed above about 28 km for soundings having high single correction factors. Random errors are at their minimum just above the level of the maximum of ozone partial pressure, and reach their maximum in the troposphere. Except at heights above about 28 km the random error of ozone sondes is a factor 2 to 3 times less than the error of the short Umkehr method. Provided that soundings with too high correction factors are neglected, the ozone sonde OSR has an accuracy comparable to that of other Brewer type sondes.The maximum amount of information on the vertical ozone distribution can be drawn from sonde measurements in the lower stratosphere. A study is underway to improve the sensitivity of the sonde OSR and thus to further enhance its reliability.     

速度差对井间走时层析成像质量的影响及其改进方法

在井间地震初至走时层析成像中,随着相邻地质体速度差的增大,使得射线分布不均匀,以及网格剖分不合适,导致层析成像结果不理想.物理和数值模型的井间走时层析成像表明：当速度差超过30.0%时,层析结果畸变较大;在30.0%～15.0%之间时,层析结果较好;低于15.0%时,层析结果好.在此基础上,提出了井间多尺度初至走时层析成像方法,即对同一模型采用多种网格剖分来同时进行层析成像,以获得研究区域的速度图像.数学和物理模型的井间多尺度走时层析结果表明：该方法很好地兼顾了层析成像的分辨率和精度,极大地改善了井间地震层析成像的质量.即使速度差超过30%,其多尺度的层析结果仍然较好.因此,这种方法具有实际应用的潜力.     

A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data

We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.     

顾及起始数据误差的双点测边交会的精度计算

推导了起始数据误差对双点测边交会定点精度影响的估算式,并依此给出顾及起始数据误差的点位精度计算公式。     

Introducing scale parameters for adjusting area objects in GIS based on least squares and variance component estimation

In this paper, a least‐squares based cadastral parcel area adjustment in geographic information systems (GIS) is developed based on (1) both the areas and coordinates being treated as observations with errors; and (2) scale parameters being introduced to take the systematic effect into account in the process of cadastral map digitization. The area condition equation for cadastral parcel considerations of scale parameters and geometric constraints is first constructed. The effects of the scale error on area adjustment results are then derived, and statistical hypothesis testing is presented to determine the significance of the scale error. Afterwards, Helmert's variance component estimation based on least‐squares adjustment using the condition equation with additional parameters is proposed to determine the weight between the coordinate and area measurements of the parcel. Practical tests are conducted to illustrate the implementation of the proposed methods. Four schemes for solving the inconsistencies between the registered areas and the digitized areas of the parcels are studied. The analysis of the results demonstrates that in the case of significant systematic errors in cadastral map digitization, the accuracies of the adjusted coordinates and areas are improved by introducing scale parameters to reduce the systematic error influence in the parcel area adjustment. Meanwhile, Helmert's variance component estimation method determines more accurate weights of the digitized coordinates and parcel areas, and the least‐squares adjustment solves the inconsistencies between the registered areas and the digitized areas of the parcels.     

The accuracy of methods used to estimate the whole-lake accumulation rate of organic carbon, major cations, phosphorus and heavy metals in sediment

The accuracy of three methods used to estimate the whole-lake accumulation rate of chemicals in sediment, the simple mean accumulation rate, regression against water depth and the mean accumulation rate in sedimentation zones, was assessed. The concentrations and accumulation rates of organic carbon, four major cations, phosphorus and four heavy metals in the 1902 to 1988 sediment layer at 43 sites in Kassjön were used and the three methods gave identical results. The accuracy of the simple mean accumulation rate method using 5 or 10 sites was investigated using Monte Carlo simulation and both versions gave accurate results. If the method used the dry sediment accumulation rate at 5 or 10 sites, along with chemical concentration at one central site, then the errors were less than ±10% for five of the chemicals and larger for the others (?20 or 20–40%), although the direction of the bias was predictable. If chemical accumulation rate at the central site only was used to estimate the whole-lake value, the bias increased to 25% for the major cations, 50% for the heavy metals and P, and 85% for organic carbon. Having 43 sites in Kassjön meant that the true whole-lake chemical accumulation rate was known and so the accuracy of the methods and their variants could be assessed for the first time. These findings allow the particulars of the simple mean accumulation rate method to be chosen to suit the accuracy needed for a palaeolimnological investigation.     

Comparison and relative quality assessment of the GLC2000, GLOBCOVER,MODIS and ECOCLIMAP land cover data sets at the African continental scale

Land cover dynamics at the African continental scale is of great importance for global change studies. Actually, four satellite-derived land cover maps of Africa now available, e.g. ECOCLIMAP, GLC2000, MODIS and GLOBCOVER, are based on images acquired in the 2000s. This study aims at stressing the compliances and the discrepancies between these four land cover classifications systems. Each of them used different mapping initiatives and relies on different mapping standards, which supports the present investigation. In order to do a relative comparison of the four maps, a preamble was to reconcile their thematic legends into more aggregated categories after a projection into the same spatial resolution. Results show that the agreement between the four land cover products is between 56 and 69%. While all these land cover datasets show a reasonable agreement in terms of surface types and spatial distribution patterns, mapping of heterogeneous landscapes in the four products is not very successful. Land cover products based on remote sensing imagery can indeed significantly be improved by using smarter algorithms, better timing of image acquisition, improved class definitions. Either will help to improve the accuracy of future land cover maps at the African continental scale. Data producers may use the areas of spatial agreement for training area selection while users might need to verify the information in the areas of disagreement using additional data sources.     

页岩储层叠前密度稳定反演方法

密度参数是页岩储层评价的重要敏感参数,但通常认为准确获得密度信息难度较大.本文探索提出了一种稳定的基于弹性阻抗的叠前密度反演方法,以提高优质页岩的识别精度.首先,基于不同的参数化弹性阻抗方程开展密度敏感性分析,优选了敏感性最高的Aki-Richards近似弹性阻抗方程作为反演方程.然后,在弹性阻抗方程线性化的基础上,假设反演方程系数矩阵的逆存在,将密度（取对数）表示为多个角度弹性阻抗（取对数）的加权和,通过井旁道弹性阻抗反演结果与测井数据的回归求取加权系数,避免了常规反演方法对大型系数矩阵的求逆计算,从而提高了密度反演的稳定性,同时由于利用测井资料作为匹配目标,密度反演的精度也得到了提高.模型试算和涪陵页岩气田的实际资料应用实践均表明了该方法能够有效地提高密度反演的精度与稳定性.