高分1号冬小麦解译面积核算方法研究

[目的]以高分1号(GF-1)融合2m卫星遥感影像为基础数据源,结合土地利用现状数据、高分多源遥感影像和地面样方等数据,对冬小麦分类提取中存在的面积误差问题进行研究和分析。[方法]文章以河南省永城市为研究区,在冬小麦提取结果聚类处理基础上,基于线性地物缓冲区数据,采用GIS空间运算实现线性地物面积扣除,接着分析了样方数据和土地利用现状数据再扣除零星地物面积比例上的差异,并采用样方零星地物平均扣除系数对全市各乡镇耕地与非耕地中冬小麦提取面积进行了相关统计和误差分析。[结果]永城市冬小麦最终解译面积11. 29万hm~2,其中线性地物和零星地物扣除面积分别为6 613. 08hm~2和3 875. 22hm~2,占研究区冬小麦解译面积的5. 86%和3. 32%,与统计上报数据相比,其处理前后误差由14. 12%降低至4. 41%,有效地提高冬小麦提取面积精度。[结论]误差来源分析与修正对冬小麦解译面积核算精度具有重要影响,该研究为县级区域尺度下冬小麦面积提取核算提供了思路和借鉴。     

一种针对压缩域信号的新型锁相环技术

针对通信信号压缩采样获得的压缩域信号频率、相位提取问题,提出了一种基于压缩感知的新型锁相环技术。通过深入研究压缩域的信号估计问题,提出了压缩域锁相环路,可以直接在压缩域同步跟踪信号频率和相位变化,不再需要高复杂度的信号重构处理。分析了环路模型及其估计性能,并针对该锁相环可行性和性能分别进行了仿真实验。仿真结果不仅验证了压缩域锁相环的可行性,同时表明该环路能够实现高动态信号的高精度频率提取。压缩域锁相环的应用潜力较大,例如可以作为压缩感知通信接收机的同步解调方法。     

遥感卫星接收系统故障诊断专家系统设计

针对遥感卫星接收系统故障诊断智能化、自动化的技术需求,分析了遥感卫星接收系统的故障特征,给出了故障诊断专家系统的架构。通过对系统设备监测信息及任务流程的分析、故障树的建立与分析,利用产生式的知识表示方式,建立了故障诊断专家系统的知识库;采用启发式的正向推理模式,实现故障的定位。该故障诊断专家系统已用于实际工程项目,提高了遥感卫星接收系统故障诊断的效率。     

单光子卫星量子通信噪声和干扰分析

卫星量子通信是建立全球量子通信网络的最佳选择之一。针对采用偏振编码的卫星量子通信中的偏振保持问题,研究了大气散射和卫星与地面站间相对运动等因素对量子偏振态相位和对准的影响以及相位延迟和对准误差对系统量子误码率的影响,分析了背景噪声和系统硬件噪声对通信产生的影响以及单光子通信过程中可能受到的光子分离攻击干扰,为量子信号认知设计提供借鉴意义。     

供应链风险评估:一个贝叶斯——量子决策的推理网络研究范式

为了分析供应链运作过程中存在风险的性质,采用贝叶斯网的方式,构建了供应链风险因素、风险事件之间的系统模型,并在量子概率的基础上,分析各种风险发生的规律,并分析了供应链风险事件之间存在的共同发生的可能性。结论认为:供应链风险是一个具有多源、多维、交叉等多种属性的复杂系统,其中,道德风险与牛鞭效应最容易发生,双重边际效应、资金链断裂以及牛鞭效应的影响最大;若干种风险之间按照一个较高的概率发生着共振现象。     

Implications of land use transitions on soil nitrogen in dynamic landscapes in Tanzania

Land use transitions are rated among the leading sources of greenhouse gas emissions in the tropics. They significantly challenge the functioning of ecosystems and affect multi-temporal stability of greenhouse gases such as N₂O and soil properties. Studies on dynamics in nitrogen balances are essential in understanding greenhouse gas emissions such as N₂O and to manage their impacts on productivity. In this study, multi-temporal Landsat images (1975, 1995 and 2012) were classified to determine land use transitions and potential drivers. The classified images were categorized into degraded and non-degraded lands and eighty sampling plots generated within the entire study area. Soil samples were then collected at 0–15, 15–30 and 30–60 cm depths on each plot and soil nitrogen determined. A regression analysis was developed to determine the influence of forest and grassland degradation on soil nitrogen. Results indicated a significant change in major land use and land cover types. Specifically, there was a decrease in areas covered by forests, woodland and grassland, however, area covered by less dense forest increased. Results also indicated variability in mean nitrogen content between degraded and non-degraded areas and depths. Furthermore, levels of degradation influence nitrogen content up to a soil depth of 30 cm. The present study is relevant in the detailed assessment of the extent of damage and threats posed to biodiversity hotspots in sub-Saharan Africa. These results are transferable to other parts of the world characterized by dynamic ecological transformation.     

基于量子三叉树的量子Black-Scholes期权定价

将量子概率引入到期权定价是最近几年一个新的研究趋势,也称为量子金融.为了期权定价更方便,文章建立了量子三叉树模型,同时利用量子概率建立了连续量子Black-Scholes(B-S)模型。实例应用和Matlab期权敏感性分析都验证了量子B-S优于经典B-S,从而为连续期权定价提供量子决策的途径。     

Quantifying and understanding land cover changes by large and small oil palm expansion regimes in the Peruvian Amazon

With rapid increases in global food demand and production, oil palm expansion constitutes a major emerging challenge for forest conservation in Amazonia and other tropical forest regions. This threat is evident in the Peruvian Amazon, where local and national incentives for oil palm cultivation along with growing large-scale investments translate into accelerated oil palm expansion. Environmental sustainability of oil palm cultivation in the Peruvian Amazon is contingent on policy incentives for expansion onto already-cleared lands instead of biodiverse, high carbon primary rainforests. Previous research indicates that while industrial plantations use less land area than local smallholders, companies have a higher tendency to expand into primary rainforests. However, the motivations behind these differing expansion scenarios remain unclear. In this study we combine data from optical and radar satellite sensors with training information, field discussions, and review of public documents to examine the policy incentives and spatial patterns associated with oil palm expansion by smallholders and industries in one of Peru’s most rapidly changing Amazonian landscapes: the Ucayali region of the city of Pucallpa. Based on our satellite-based land cover change analysis, we found that between 2010 and 2016, smallholders utilized 21,070 ha more land area for oil palm than industries but industrial expansion occurred predominantly in old growth forests (70%) in contrast to degraded lands for smallholders (56%). Our analysis of national policies related to oil palm expansion reveal policy loopholes associated with Peru’s “best land use” classification system that allow for standing forests to undergo large-scale agricultural development with little government oversight. We conclude that both sectors will need careful, real-time monitoring and government engagement to reduce old-growth forest loss and develop successful strategies for mitigating future environmental impacts of oil palm expansion.     

城市三维形态与热环境的相关关系研究——以大连市金普新区为例

由城市各种实体空间结构所构成的三维形态是城市形态的重要组成部分。而城市的空间结构与城市空间环境的热场分布也有着密不可分的关系。本文运用地理信息系统与遥感技术,获取三维形态指标与地表温度,对各因子进行回归分析,建立城市空间形态热场分布研究的回归模型。分析了金普新区空间实体的占空度、错落度、建筑密度等空间形态对城市亮度温度的影响,发现占空度与城市亮温成正相关并且相关性较高,绿化率与亮温成负相关,而建筑密度与错落度对城市热场的影响较小。     

农业水循环与水环境遥感应用研究进展

农业生产受环境因素影响大,进入农耕文明以来,农业对气候的高度依赖局面没有得到根本性的改变,频繁的自然灾害给我国的农村经济发展造成了极大的困难。遥感技术是运用各类非接触的主被动的探测设备,对地面目标物的电磁波辐射与反射特性进行探测,通过其特性分析,探明其物体性质、特征及状态的综合性探测技术。它具有覆盖面积广、空间分辨率高、获取信息大、重访周期短等优点,适用于农业资源调查与自然灾害监测等农业相关领域的研究,对农业生产的指导与相关部门的决策管理意义重大。文章主要针对国内遥感技术在农业水循环与水环境的发展、应用现状进行综述与分析,并对遥感技术在农业水资源领域的发展趋势进行展望。