海洋空间规划管控平台建设的总结思考

新时期国家着力构建陆海统筹、区域统筹、城乡统筹的国土空间规划体系,为更好的服务国土空间规划体系与海岸带专项规划的建立实施,满足新形势下海域海岛管理的新要求,深化落实主体功能区制度,本文对已经建立的海洋空间规划管控平台进行了总结。海洋空间规划管控平台主要目标是实现海洋空间“一张图”、海洋主体功能区监测评估、海洋空间综合决策,主要功能包括多规分析与一张图、海洋主体功能区监测评估、海洋空间分区辅助编制与审查、海洋空间符合性判断等.     

钙质土中重力串锚水平承载力特性有限元研究

目前没有规范给出串锚的水平承载力计算公式,为了利用有限元法研究串锚水平承载力特性,采用相关理论计算以及室内试验的方法来验证有限元法模拟计算的可靠性。实践证明,有限元法具有较高的计算精度。利用有限元分析软件ABAQUS建立了串锚-土体模型,模拟串锚在水平荷载作用下破坏过程,研究了串锚在水平荷载作用下破坏机理,从而得到了串锚水平承载力特性。在相同的工况条件下,串锚的水平承载力与其锚链长度有关,在一定范围内,增加锚链的长度可以提高串锚的水平承载力;串锚的水平承载力不是相应的单个锚的水平承载力相加,其水平承载力小于相应的单个锚水平承载力之和,在进行串锚水平承载力设计计算时应给与相应的考虑。     

偏振激光雷达探测大气—水体光学参数廓线

激光雷达在上层水体垂直廓线的遥感中展现出巨大优势。本文研制了一套高垂直分辨率的实时探测偏振激光雷达,提出了一种基于偏振激光雷达回波信号的反演算法,采用Fernald理论和多次散射原理反演非均匀大气—水体的衰减和退偏光学产品,以高效稳定地处理偏振激光雷达实验数据。展示了一个中国内陆水体激光雷达探测实例,观测到了两次气溶胶积聚现象和一次水体浑浊现象。对实验数据的分析表明,退偏比主要由前向多次散射和后向单次散射产生的退偏两部分组成。当多次散射强度较大时,退偏比的变化主要取决于多次前向散射退偏;反之,则主要依赖于单次后向散射退偏。     

BDS静态精密单点定位模糊度固定解精度分析

针对BDS单系统未校准相位延迟(UPD)估计以及不同时长精密单点定位(PPP)模糊度固定对定位精度影响的问题,该文选取56个测站估计UPD,利用未参与UPD计算的8个测站进行不同时长BDS静态PPP模糊度固定实验。结果表明:BDS星间单差宽巷和窄巷UPD在连续时段内具有一定的稳定性,其估计精度满足用于PPP模糊度固定要求。时长越短模糊度固定率越低。以IGS周解为参考值,不同时长模糊度固定解较浮点解三维定位精度均提高12%以上,时长越短模糊度固定解精度提高越显著。因此,模糊度固定是提高BDSPPP定位精度的重要手段。     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

武汉城市圈经济与环境协调性分析和评价研究

以用地现状、人口调查、经济统计等信息为基础,搭建了武汉城市圈生态环境分析和评价信息平台,设计了统计分析、指标评价、决策支持等模块。按照区县单元分析了武汉城市圈人口、经济与生态环境相关性和协调性,其研究结果对开展武汉城市圈“两型”社会建设具有重要意义,可为武汉城市圈的社会经济与生态环境协调发展提供科学的决策参考。     

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

利用多频多系统GNSS OEM板卡实现高精度变形监测

针对近年来被广泛应用的多频多系统GNSS OEM板卡,设计并实现了一套基于多频多系统OEM板卡的低成本变形监测系统,包括数据解码、基线处理、网平差和坐标转换等,能够实时获取测站点高精度空间坐标。以某高层建筑形变监测为例,通过串口通信获取板卡多频多系统观测信息,并经过该系统解算,实现了监测点实时定位,且系统成本相比市场上测量型GNSS接收机系统下降了约40%。实验结果表明,该系统解码精度可达0.2 mm,静态模式定位精度可达到平面2 mm以内,高程5 mm以内,动态模式定位精度可达到平面5 mm以内,高程10 mm以内,验证了该系统的可靠性和适用性。