运用归一化光谱混合模型分析城市地表组成

运用归一化光谱混合分析(NSMA)方法,用ETM 数据调查广州市海珠区城市地表组成,采用亮度标准化方法减小亮度变化。通过标准化,使亮度差异在每个植被-非渗透性表面-土壤-水体(V-I-S-W)组成中减小或者消除,这样使得一个单一的端元能够代表一种地表组分。在此基础上,通过归一化影像,选择了植被、非渗透性表面、土壤和水体4种端元,运用一种约束光谱混合分析(SMA)模型,分解了不同种类的城市地表组成。通过与已有模型计算结果比较,认为本文所构建的模型较优,其对研究区非渗透性表面估计的均方根误差为12.6%。     

基于遥感分类的植被覆盖度提取

阐述了基于遥感分类进行植被覆盖度提取的方法,分析了直接利用关系模型提取植被覆盖度的缺点,遥感分类可获得不同类型地物,此后关系模型分别提取,解决了直接利用关系模型提取中存在的缺点.     

一种面向对象的4层空间数据模型

针对“空间数据是否要建立拓扑关系并在数据库中显式地存储记录”一直是G IS领域争论的问题,给出了解决方案:融合拓扑关系数据模型和面向实体数据模型,进而在分析和总结现有数据模型的基础上提出了一种面向对象的4层空间数据模型。对模型作了4个层次划分:几何对象、基本和复杂要素、分层与分区以及多尺度表达。模型具有3个特点,即多尺度描述地理空间;能描述不同要素层、不同区之间的关系;用户可根据实际情况自定义要素层拓扑关系。最后给出了模型在自主开发的地理数据库管理平台Geoinfo中的应用情况。     

A high-precision heuristic model to detect home and work locations from smart card data

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.     

Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India

Estimation and monitoring of crop evapotranspiration (ET_c) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ET_c by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ET_c was estimated 2.72 and 2.47 in mm day^?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ET_c.     

导航应用的按需下载区域网络模型研究

提出了一种导航应用的按需下载区域数据模型。对按需下载模式的技术要求进行了分析,提出了区域导航数据模型的定义及其算法,用UML定义了区域网络概念模型,并与ISO的网络模型进行了一致性检验。通过实际算例证明了方法的可用性。     

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km²) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16 t ha⁻¹ a⁻¹. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.     

精密单点定位在机载GPS中的应用

推导了精密单点定位PPP(Precise Point Positioning)的基本原理及其解算流程。为达到分米级甚至厘米级的PPP精度,给出了基于传统模型PPP技术,PPP数据必须处理的几个关键问题。最终,在Matlab程序设计语言软件平台下开发了APTags 1.0软件包,并通过机载GPS动态数据测试得出了如下结论:序列历元的事后动态定位精确度在B,L,H方向优于25 cm(RMS);85%定位结果的精度优于15 cm的动态定位结果。APTags软件包获取的动态精密单点定位结果与传统差分定位结果基本吻合。     

玉米作物极化SAR数据模拟

通过重点研究玉米叶子的空间位置、指向角分布,分析玉米作物的结构特点,建立玉米的三维结构模型和场景,发展针对玉米作物的极化合成孔径雷达(synthetic apertureradar,SAR)数据模拟方法。利用该模拟方法和实地获取的玉米参数模拟极化SAR数据,通过与散射计实地测量的多极化、多角度后向散射系数进行对比,表明该模拟方法能够有效的模拟玉米作物的后向散射系数;通过分析模拟极化SAR数据获得的HH-VV、HH-HV、VH-VV之间的相位差,表明该模拟方法能够有效的模拟玉米作物散射的相位信息;通过分析模拟数据的极化响应图和Cloude H-α分类图,从散射类型角度验证了模拟极化SAR数据的有效性。     

面向对象空间数据模型的结构设计

以面向对象方法提出了空间数据模型,探讨了面向对象空间数据模型中空间对象及类的描述方法和体系结构,分析了体系结构中各层之间的逻辑关系,并以城市道路交通信息为例,设计了道路交通信息的层次划分和关系构成。