校正地基摄影获取树枝倾角

针对传统树枝倾角测量方法的复杂性和精度低的问题,该文提出了通过校正地基摄影获取树枝倾角的方法。基于投影变换和小孔成像原理,通过自制树枝模型的方法,分析了直接图上量取树枝倾角与真实值之间误差的成因,提出了基于投影变化的树枝倾角计算公式。结果表明:该研究获取树枝倾角的相对误差2.72%明显优于传统测量的31.33%,同时随拍摄距离变化,树枝倾角估算结果具有稳定性。该研究方法简单、有效,非常适合复杂环境下树枝倾角的大量提取,并提出了一种基于摄影成像原理获取树枝倾角的方法,发展了树枝倾角测量系统软件,提高测量精度并降低了测量难度。     

一种基于属性值变化程度定权的聚类算法

针对经典K-means聚类算法以欧氏距离作为相似度判断法则进行聚类划分,而未考虑聚类对象的各属性值对聚类划分的影响程度存在差异的问题,该文提出了一种基于属性值变化程度定权的聚类算法。通过采用Iris dataset数据进行实验,该算法相对于其他聚类算法获得了更好的聚类效果,且该算法适用于生物物种分类、遥感影像识别等工作领域,能提高聚类运算的精准度。     

Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.     

GPS高层建筑物动态特性的小波分析提取

针对高层建筑物GPS动态监测数据特点,该文将小波分析技术应用于高层建筑物动态特性提取,研究了数据处理时4种阈值选取准则的好坏,针对观测数据不同阶段振幅和频率不同,提出分段、分层处理数据的思想,为了获得更全面的观测信号,将小波包分析应用于数据处理。结果表明:自适应阈值准则更适用于高层建筑物动态数据处理,采用分段分层的处理方法,既能满足去噪要求又能提取丰富的变形信息,小波包分析能有效提取高层建筑物动态特性,保留更多的动态信息。     

郑洛地区史前聚落分布特征的空间自相关分析

针对郑洛地区史前聚落遗址点的空间分布特征的问题,该文提出了一种空间自相关分析方法,以不同的格网尺度研究郑洛地区4个文化时期的遗址点的空间分布特征。研究发现:5 000~12 000m的格网尺度最能表现出裴李岗文化时期、仰韶文化前期、仰韶文化后期和龙山文化时期这4个文化时期全局自相关的差异。从局部自相关所表现出的变化情况来看,6 000~10 000m这一范围的格网尺度是最能保留住郑洛地区这4个文化时期遗址点的空间分布特征。将空间自相关分析应用于史前聚落考古研究中,可以探讨史前聚落考古中遗址点的空间分布模式及其变化。这不仅为史前聚落考古提供了一种新的思维方式,也扩展了史前聚落考古理论方面的研究。     

Network-based triple-frequency carrier phase ambiguity resolution between reference stations using BDS data for long baselines

Network-based ambiguity resolution (AR) between reference stations is the prerequisite to realize a precise real-time kinematic positioning service. With the help of BDS triple-frequency signals, we can efficiently deal with the ionospheric delay and tropospheric delay, and achieve rapid and reliable AR. To overcome the inaccurate ionospheric delay estimated by the geometry-free three carrier ambiguity resolution (GF TCAR) technique, which leads to failure in the original ambiguity resolution, we propose an ionospheric-free (IF) TCAR method to resolve the ambiguity between the reference stations over long baselines. Taking full advantage of the known positions of the reference stations, the easily resolved extra-wide-lane (EWL) ambiguity, and the IF phase combinations, we can reliably fix the wide-lane (WL) ambiguity. A Kalman filter is applied to estimate precise IF ambiguities and the original ambiguity is resolved with the fixed WL ambiguity. A numerical analysis with triple-frequency BDS data from three long baselines of a CORS network is provided to compare the AR performance of GF TCAR with that of IF TCAR. The results show that both methods can reliably resolve the WL ambiguity with a remarkable correctly-fixed rate of higher than 99%, and the reliably-fixed rates of the IF TCAR slightly increase from 92.19, 94.67 and 94.61–98.26, 99.54 and 97.51% for the three baselines. Herein “correctly-fixed” and “reliably-fixed” mean the difference between the float ambiguity and the true one are less than ± 0.5 and ± 0.25 cycles, respectively. On the other hand, the AR performance of the original signals with the IF TCAR method is much better than that with the GF TCAR method attaining a 100% correctly-fixed rate, while the GF TCAR method can hardly fix the original ambiguity with the largest bias being as much as 4 cycles because of the amplified systematic bias.     

A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy

Multipath disturbance is one of the major error sources in high-accuracy positioning for global navigation satellite system (GNSS). Although various methods based on software and hardware strategies have been developed to mitigate this error, they are still limited by different kinds of factors and the effect is not ideal. After analyzing the existing methods, a new single-difference sidereal filtering method, based on adaptive thresholding wavelet denoising and double reference shift strategy (ATDR), is proposed to mitigate multipath effects for static short-baseline GNSS applications. The key idea of the proposed method is the use of both the adaptive thresholding wavelet denoising to extract an accurate multipath correction model from the reference Day and the double reference shift strategy to mitigate multipath for subsequent Day 2 more accurately and efficiently. By applying the introduced adaptive thresholding method, the average improvement rate of the RMS values of the single-difference residuals can reach about 15.82% compared with the constant thresholding method. Moreover, after applying the proposed ATDR method, the 3D positioning precision is improved by about 37.73% for the single epoch mode with 30 s data sampling rate and about 31.22% for the continuous mode with 1 s high sampling rate compared with the original results. Even compared with the constant thresholding single orbital reference (CTSR) method, the improvement percentage is about 33.94% in single epoch mode and about 25.40% in continuous mode for 3D positioning precision, respectively. In conclusion, the results of the two experiments indicate that the proposed ATDR method performs much better than the CTSR method in mitigating multipath for different sampling rates and different processing modes in the measurement domain for GNSS static short-baseline postprocessing applications.     

An improved ionosphere interpolation algorithm for network RTK in low-latitude regions

A traditional interpolation algorithm with the linear interpolation method (LIM) using a fixed number of reference stations is widely used in network RTK to obtain the ionospheric delays for the users. In low-latitude regions, where the ionosphere is relatively active, however, large interpolation errors exist, especially for satellites at low elevation angles. Considering the characteristics of “coinciding ionospheric pierce points (CIPPs)” with a similar nature of ionospheric delays, an improved interpolation algorithm is proposed. In this algorithm, all stations with CIPPs are used to establish the interpolation model; thus, more precise interpolation model is achieved. To validate the performance of the proposed algorithm, data from some reference stations in Guangdong Province of China were used, and the results are compared with those with the traditional interpolation algorithm. Numerical analysis shows that the interpolation accuracy of the proposed algorithm increases by 10–30% compared with the traditional one. Since the number of reference stations is flexible, the proposed algorithm can also balance the model accuracy with the computation burdens. In addition, the proposed algorithm is less affected by the selection of master reference station. In terms of network RTK on-the-fly positioning, the time-to-first-fix is reduced when replacing the traditional interpolation algorithm with the proposed one.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

Examining human heat stress with remote sensing technology

Heat stress as an environmental hazard which can seriously affect productivity, health, or even survival of individuals has long been studied. Despite the endeavors that have been made to address the issue quantitatively with various heat stress indices, they are often measured at scatter sites. This research devotes to revealing human heat stress within continuous space with remote sensing technology. The study began with the retrieval of dry-bulb temperature from land surface temperature (LST) with empirical models. As wet-bulb temperature was calculated from dry-bulb temperature and relative humidity, discomfort index (DI) as an indicator of heat stress was revealed for the study area at 1 km spatial resolution for three summer days. Results indicated that DI can be derived within continuous space with remotely sensed data, and its spatial distribution can be dramatically affected by relative humidity. Further comparison between DI and LST indicated that LST as a widely utilized indicator of surface thermal condition fails to address human heat stress as environmental factors such as relative humidity are not taken into account.