Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R² = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.     

多光谱遥感影像亮度空间相位一致性特征点检测

提出了一种基于亮度空间和相位一致性理论的多光谱遥感影像特征点检测算法。首先利用参数自适应的灰度变换函数建立影像亮度空间;然后结合相位一致性方法在影像亮度空间进行候选特征点检测,并将候选特征点映射到原始影像上进行非极大值抑制;最后在尺度空间计算特征点的特征尺度值。本文方法有效结合了亮度空间特征检测和相位一致性特征检测的优势,对多光谱遥感影像的辐射变化具有较强的稳健性。试验结果证明,与传统特征点检测算法相比,本文方法在特征重复率和重复特征数量方面都具有明显的优势。     

双频BDS实时精密单点定位算法和精度分析

为了对BDS实时精密单点定位性能进行评估,该文提出了一种适用于BDS系统的实时精密单点定位算法。采用无电离组合模型作为双频实时精密单点定位的数学模型,采用电离层残差法和Melbourne-Wübbena组合实时探测相位周跳,进而单历元实时估计坐标、模糊度等参数,实现了BDS双频实时精密单点定位算法。基于此算法,采用轨道钟差产品和采样间隔为1s的观测数据,模拟实时BDS双频精密单点定位算法,并评估其定位精度。实验结果表明:BDS双频实时定位的平面精度和三维精度均为0.2m左右。     

一种底座式ADCP流量自动监测探头支撑装置的研制与应用

在流量自动监测系统中,底座式ADCP设备探头位于河底,维修极为不便。该研制装置采用304不锈钢支架配合滑轮、钢索、绞盘等手摇传动系统,将底座式ADCP设备探头从河底传送到水上岸边检修台,实现对设备探头的维护、检修、更换、安装、调试等操作,再通过该装置将底座式ADCP设备探头传送到河底原位,经十里长街等站实际应用,运行稳定可靠,运用极为方便;该装置防磁、防锈、防腐性能良好,为底座式ADCP探头提供一个很好的工作环境,且结构简单,运输方便,可作为中小河流永久流量自动监测站装置使用。     

A Method for Automatically Selecting Aids to Navigation Based on their Spatial Influence Domains

To address the limitations of manually selecting aids to navigation (AtNs) on charts, a method for automatically selecting AtNs based on their spatial influence domains (SIDs) is proposed. First, the associations between the spatial attributes of an AtN are analyzed. Second, an SID of the AtN is defined, and a model of the SID is constructed based on the associations between the spatial attributes. Third, the importance of the location of the AtN is weighted based on the SID model. Fourth, an algorithm to automatically select AtNs based on the maximum coverage of the SIDS of preselected AtNs is developed. Finally, several AtNs are selected automatically using the algorithm. The experimental results demonstrate that (1) the proposed method can automatically select AtNs and the results comply with the requirements; (2) the automatic selection can eliminate the human-induced errors or the inconsistent results of manual selections from different operators; and (3) the efficiency of the proposed method is higher than that of current manual methods.     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

Seismic attenuation estimation using a complete ensemble empirical mode decomposition-based method

The frequency attenuation gradient method can provide important information for hydrocarbon detection. In this paper, a method using Complete Ensemble Empirical Mode Decomposition (CEEMD), Hilbert transform and the least-squares curve-fitting is proposed for seismic attenuation estimation as an effective frequency attenuation gradient estimation approach. We first use CEEMD to obtain the different Intrinsic Mode Functions (IMFs), which have a narrow band and can enhance the physical meaning of instantaneous attributes trace by trace. The time-frequency spectrum, which is computed using a Hilbert transform of each IMF, is represented as a spectrum with a single-peak that has narrow side lobes, which is conducive to frequency attenuation gradient estimation. Second, for each time sample, the frequency-amplitude spectrum of each IMF trace is extracted from the time-frequency spectrum to conduct the attenuation gradient computation. Then, the logarithm operation is performed for each IMF trace. Due to the very narrow bands of some IMFs in some seismic traces, a variable frequency window is adopted along the IMF trace according to the local data characteristics. Finally, the attenuation gradient for each IMF in a seismic trace can be computed using least-squares fitting. A different IMF reflects a seismic trace with a different spatiotemporal scale and can highlight different geologic and stratigraphic information. The correlation weighted average operation is used to highlight some useful details in seismic trace and obtains the attenuation gradient for each seismic trace. Field data examples demonstrate our method and its effectiveness. The proposed method can stably estimate the frequency attenuation gradient.     

高频地波雷达海杂波背景下的船只目标检测研究进展

针对海杂波对高频地波雷达目标检测的干扰问题,分目标处于海杂波谱区之内和之外两种情况综述了海杂波背景下的目标检测方法。对于海杂波内目标检测的难题,介绍了一种基于现场海态同步观测信息的检测新思路以及初步验证结果。对国内外相关研究进展的归纳总结和新思路的提出,为提出更加有效的海杂波干扰下的目标检测方法提供了重要的参考。     

地质雷达电磁干扰分析及在隧洞岩溶探测中的应用

将地质雷达用于千岛湖配水工程某隧洞岩溶探测,分析了倾斜状电磁干扰异常与溶洞雷达异常差异,通过雷达剖面及疑似异常区单道时间-频率谱的分析,推断了隧底岩溶的性质及空间分布特征,含水溶洞在雷达剖面反映为同相轴错断,强振幅及能量高衰减的特性,高频干扰波振幅幅值较异常区小且能量不满足随时间推移逐渐衰减的规律,雷达成果为隧洞安全施工提供了准确的参考。      

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.