水稻根系空间分布特性的三维建模及可视化研究

为明确水稻根系在土壤中的空间分布特性,应用"根箱法"进行试验,获取水稻根系坐标数据,分析根系生长随水稻生育进程的变化规律,采用植物模拟技术,建立了水稻根系三维形态模型,包括根节点初始位置的确定、根节点生长方向的确定、不定根位置的确定、不定根生长方向的确定等。根据水稻根系几何形态参数,采用Visual C++及Open GL标准图形库,对水稻根系的三维形态结构进行重构,使系统生成更加逼真的水稻根系图像。结果表明该模型对水稻根系形态结构动态生长具有较好的预测效果,同时也可为其他作物根系的可视化研究提供参考。     

绿地格局与温度的关系

研究旨在按照既定的尺度研究绿地格局与温度之间的关系。绿地格局利用绿地格局指数来做表征,从斑块规模、边界特征、空间特征3 方面来选取指数,温度利用遥感影像反演得到。结果表明：斑块数量超过400 时,平均斑块面积和斑块面积的离散度在一定区域变化时,温度才会下降。平均斑块的边界复杂度保持在一定区域变化时,温度才会下降。空间位置的结果也表明当平均邻近指数和平均邻近距离保持在一定区域变化时,温度才会下降。研究结果对建设城市绿地有一定的实践指导意义。     

Visualization of amino acid composition differences between processed protein from different animal species by self-organizing feature maps

Amino acids are the dominant organic components of processed animal proteins, however there has been limited investigation of differences in their composition between various protein sources. Information on these differences will not only be helpful for their further utilization but also provide fundamental information for developing species-specific identification methods. In this study, self-organizing feature maps (SOFM) were used to visualize amino acid composition of fish meal, and meat and bone meal (MBM) produced from poultry, ruminants and swine. SOFM display the similarities and differences in amino acid composition between protein sources and effectively improve data transparency. Amino acid composition was shown to be useful for distinguishing fish meal from MBM due to their large concentration differences between glycine, lysine and proline. However, the amino acid composition of the three MBMs was quite similar. The SOFM results were consistent with those obtained by analysis of variance and principal component analysis but more straightforward. SOFM was shown to have a robust sample linkage capacity and to be able to act as a powerful means to link different sample for further data mining.     

基于IDL的遥感影像缨帽变换融合

遥感影像融合可以部分消除原始影像的冗余信息,在提高影像的空间分辨率的同时保持其多光谱信息,提高影像的质量,有利于遥感解译、纹理分析以及信息提取等。该研究介绍了基于缨帽变换的遥感影像融合算法,并采用交互式数据语言IDL(Interactive Data Language)进行了实现;同时为了验证算法的有效性,将其与ENVI平台下的几种常用的影像融合方法的融合影像进行了比较。结果表明,基于IDL的遥感影像缨帽变换融合程序执行快速稳定,可靠性高,获得的影像融合效果较好。     

基于网络地理信息系统的林业资源统计数据可视化系统设计

针对传统林业资源统计数据多采用文字和表格等方式表达,其形式单一、可视化程度低,难以体现林业资源统计数据的空间分布特性等,文中提出构建基于网络地理信息系统（WebGIS）的林业资源统计数据可视化系统,介绍了该系统关键技术、设计方法、运行效果,并提出了系统发展与研究展望。该系统采用B/S模式下的3层架构:数据层存储了4年的世界森林资源统计数据和中国8次森林资源清查数据,并采用空间数据和属性数据分离存储的模式;后台服务层通过ArcGIS Server和Web Service相结合的方式为前端提供GeoJSON格式数据接口;前端页面层利用ArcGIS API for JavaScript实现具体模块。为提高可视化效果,采用Highcharts框架对数据进行图形化展示。该系统丰富了林业统计资源数据的可视化方式并有效表达出林业资源统计数据的空间分布性,提高了林业资源统计数据可视化程度。     

基于COMGIS的古树名木管理信息系统设计

阐述了如何利用组件式GIS开发平台SuperMap Objects 5.0,VB.NET编程语言,SQL Server开发古树名木管理系统的方法;探讨了系统的总体结构设计,包括技术路线、系统功能设计及数据库设计;重点分析了系统实现过程中采用的若干关键技术.     

基于图像处理的水稻叶片三维可视化研究

介绍利用数字图像处理技术提取水稻叶片几何参数及边缘轮廓曲线的方法,分别利用三角网格化技术和贝塞尔曲线来描述叶片边缘信息,并对2种方法进行比较。通过二次生长曲线方程实现了水稻叶片的三维建模及可视化表达。     

玉米小斑病病害程度图像检测

为了实时获取作物病害程度信息,研究了一种基于RGB彩色模型的玉米小斑病图像的分割方法,并利用分割结果求得的玉米冠层危害程度来计算整株玉米的发病程度.由于图像中背景复杂,将叶片与病斑同时分离出来的可能性小,故该方法分为两步:首先从获取的RGB图像中提取R、G、B分量,利用2G-R-B图像采用迭代法自动选取阈值将玉米叶片从背景中分割出来;然后根据R-G图像将病斑从叶片上分离出来.30幅图像中玉米叶片、病斑基本上能提取出来,但没有黄化的少量侵染点无法有效分割.     

虚拟植物模型及可视化的研究

虚拟植物生长是农业信息技术和计算机图形学领域中主要研究的课题之一。虚拟植物生长就是在计算机上仿真模拟植物在三维空间的生长过程,在农林业等领域有着广阔的应用前景。为此,论述虚拟植物生长模型的分类和生成植物图形的方法,介绍了植物虚拟生长的研究现状。     

A new vision-based approach to differential spraying in precision agriculture

One of the objectives of precision agriculture is to minimize the volume of herbicides by using site-specific weed management systems. To reach this goal, two major factors need to be considered: (1) the similarity of spectral signatures, shapes, and textures between weeds and crops and (2) irregular distribution of weeds within the crop. This paper outlines an automatic computer vision method for detecting Avena sterilis, a noxious weed growing in cereal crops, and differential spraying to control the weed. The proposed method determines the quantity and distribution of weeds in the crop fields and applies a decision-making strategy for selective spraying, which forms the main focus of the paper. The method consists of two stages: image segmentation and decision-making. The image segmentation process extracts cells from the image as the low-level units. The quantity and distribution of weeds in the cell are mapped as area and structural based attributes, respectively. From these attributes, a multicriteria decision-making approach under a fuzzy context allows us to decide whether any given cell needs to be sprayed. The method was compared with other existing strategies.