广西森林转型与森林扰动遥感监测研究

近20年来由于封山育林政策的实施和人工乔木林的大面积种植,广西森林面积大幅增加,正在经历深刻的森林转型,森林转型过程中农林交错带和森林内部的结构重组都给生态系统带来了不容忽视的扰动。本文基于2000—2016年MODIS-EVI影像数据、1∶100万地貌图和4期土地利用数据,采用变化矢量法和Sen+Mann-Kendall对广西进行森林转型背景下的森林转型路径和森林内部扰动特征分析。研究表明:自2000年以来广西森林的EVI变化强度以无变化和低变化类型为主,总体EVI上升趋势略大于下降趋势,EVI显著下降主要分布于十万大山、大瑶山、海洋山和越城岭等山地区域和桂西北的百色水利枢纽和龙滩水利枢纽周围,显著上升部分主要集中于桂中南的左江-邕江-郁江流域平原丘陵区、桂西南喀斯特区和桂东北山地区地势低平的河谷地带。广西森林面积增加的土地来源于耕地和草地,森林转型路径表现为"经济增长型"和"森林短缺型"两种路径并存,或者存在更为复杂的复合型路径。广西森林内部扰动的减少型和扰动型分布于桂西北喀斯特和桂东北山地起伏度较大的陡坡区域,增加型分布于桂中南的平原丘陵地区。由于山地陡坡区域和喀斯特地区的生态敏感性,应更多关注扰动型和减少型在桂西北和桂东北地区的集中分布问题。     

Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

利用多面函数拟合和欧拉矢量法建立福建省GPS速度场模型

通过处理福建省卫星导航定位基准服务系统(FJCORS)2013-2015年观测资料,获得GPS站实测运动速度值,在此基础上,分别利用多面函数拟合法和欧拉矢量法构建了福建省及周边区域GPS速度场模型.内符合精度方面,多面函数拟合的速度精度南北分量为1.06 mm/a、东西分量为2.00 mm/a;欧拉矢量法得到的速度精度南北分量为1.36 mm/a、东西分量为1.22 mm/a.外符合精度方面,两种方法模拟得到的检核点速度值与实测速度值的较差均在±2.28 mm/a以内.在福建省陆域内,两种方法得到的速度场具有高度的一致性,运动速度均为35 mm/a左右,运动方向为SE-E向.     

Geospatial data mining for digital raster mapping

We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.     

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.     

海洋石油管线探测多波束剖面声纳设计

针对海洋石油管线探测多波束剖面声纳的高速、大容量的实时信号处理任务,以及声纳系统进一步扩展的需求,设计并实现了一种基于IP网络互连的、以并行DSP为处理节点的多波束剖面声纳系统.该系统应用于海底石油管线探测与定位,系统中的每个处理节点与数据采集转换部分采用TCP/IP网络连接,可以通过物理上添加一个或多个处理节点成倍的提高系统的信号处理能力,而在软件上无须大的改动.通过电联调与水槽试验,验证了系统的可行性和稳定性,该设计为高速水声阵列信号实时处理系统提供了一种全新的解决思路.     

The influence of light availability and predatory behavior of the decapod crustacean Nephrops norvegicus on the activity rhythms of continental margin prey decapods

The day–night cycle is one of the strongest geophysical cycles modulating species' behavioral rhythms. However, in deep-water continental margins, where light intensity decreases over depth, interspecific competition may alter behavioral responses to day–night cycles. The burrowing decapod crustacean Nephrops norvegicus is a large-size predator in benthic communities, exerting despotic territorial behavior. In this study, we analysed how the effect of light intensity cycles on decapod behavioral rhythms is reduced as one moves from shelves to slopes. In the Western Mediterranean, the predatory behavior and interspecific competition for substrate use of Nephrops increases moving from the shelf (100–110 m) to the slope (400–430 m). Vector fitting and generalized additive models were used to assess the effect of light intensity and behavioral rhythms of N. norvegicus on the temporal variation of prey decapods co-occurring in trawl tow catches carried out on the shelf and the slope during October 1999 and June 2000. The combination of diel variations in light intensity and N. norvegicus abundance influences the activity rhythms of prey decapods in a depth- and seasonal-dependent manner. Light modulation is stronger on the shelf and weaker on the slope, where Nephrops population size is greater. Although present regression analysis does not necessarily imply a direct cause–effect relationship between rhythms of predators and prey, we suggest that Nephrops alters the temporal patterning in the behavior of its prey on the slope, where light intensity is reduced. This alteration is stronger in endobenthic species than in benthopelagic species; the former rely on bottom substrate for the expression of behavioral rhythms, experiencing stronger interspecific competitions with Nephrops at time of activity.     

矢量图形与影像图像一体化实现

本文在阐述影像金字塔相关理论（构建方法、影像切割等）的基础上,采用VC2005编程实现了在同一GIS系统中进行矢量数据和栅格数据叠加显示的功能模块。该模块可确定是否加载影像,并根据当前矢量图显示范围自动加载不同分辨率的影像图。     

航向测量仪在车载三维信息采集系统中的应用

航向测量仪(Vector Sensor)的作用就是为车载惯导系统初始化提供所必须的航向角;根据不同的应用环境和特性,用航向测量仪获取在各种条件下的航向角数据,通过对这些数据在精度、稳定性以及解算时间等性能上的对比分析,得到该仪器的最佳工作状态,进而获取该状态下的航向数据;通过实际的实验测试,此状态下的数据在精度和稳定性方面都能满足惯导系统的需求。     

基于模板阴影体算法的矢量数据在三维场景中的绘制

提出一种基于模板阴影体算法的矢量数据绘制方法,实现矢量数据在三维场景中的高质量实时叠加显示。南于该方法基于屏幕空间,所以具有像素级的精度,不会出现传统的基于纹理方法所产生的绘制走样现象;而且不受地形几何数据的约束,其执行效率与地形数据的复杂度无关,仅取决于矢量数据本身的复杂度。详细论述基于模板阴影体算法矢量数据绘制的关键技术,并通过试验验证该方法的有效性。