玉米种子脱粒过程高速摄影观察分析

为优化差速式玉米种子脱粒机脱粒系统的有关参数,进而降低玉米种子在脱粒过程中的损伤,采用高速摄影方法对单个玉米果穗喂入与脱粒过程进行了观察分析.分析结果表明:果穗在开始喂入阶段,籽粒破碎大;在脱粒起始阶段,果穗撞击强烈,越到后段,撞击越弱;果穗在正常脱粒情况下,脱下籽粒多,籽粒运动轨迹可近似为沿直辊与果穗接触点的切线方向;而果穗非正常脱粒情况下,脱下籽粒少,籽粒运动规律呈杂乱状态,没有一定飞行方向;螺旋辊的转速偏大造成果穗的非正常脱粒加大,果穗的非正常脱粒会影响果穗的脱粒质量和脱粒效率.     

Methodology for urban vegetation segmentation based on cartesian hue and saturation characteristics using UAV images

A renewed importance in the urban vegetation segmentation task has been growing over the last years, mainly due to new urban planning and management projects, which require proper data on green spaces. Although multi-spectral sensors and complex systems for image acquisition that support this task are standard in some works, they show disadvantages in cost and spatial resolution. Unmanned aerial vehicles (UAV) offer an affordable alternative so that they can get high-quality images. Such images deliver some challenges for the urban vegetation segmentation job, such as the color dispersion that urban green spaces present, vegetation greenness, and lightning conditions, like those seen in related works that use the most advanced devices. In this research, a cartesian chromatic histogram-based algorithm is proposed for urban vegetation segmentation in UAV images. The developed method uses morphological operators to enable the reduction in histogram color discontinuities. The tests that were carried about over sample images resulted in accuracy up to 98 %, surpassing the state-of-the-art tested techniques. The results validated the robustness and the accuracy of the proposal against different conditions presented in study cases.     

Soil surface infiltration capacity classification based on the bi-directional reflectance distribution function sampled by aerial photographs. The case of vineyards in a Mediterranean area

Spatially distributed hydrological modelling is required to understand and predict erosion, flooding and pollution risks that affect the vine cultivated Mediterranean environment. Previous field studies have demonstrated the dominant influence of soil surface features on overland flow and they therefore constitute an essential input to the hydrological model. In this paper we propose a remote sensing based method to map vineyard soil surface features with a spatial and temporal resolution appropriate for integration into the model. Our goal was to classify each soil surface portion in accordance with a pre-established, field measured infiltration capacity based typology. The radiometric characteristics of the classes of this typology were measured in the field and their Bi-directional Reflectance Distribution Function (BRDF) was modelled. Vineyard sunlit soil surface pixels were automatically extracted from high spatial resolution scanned aerial colour photographs Wassenaar et al., 2001 and Wassenaar et al., 2002. These pixels are radiometrically classified by comparison of their reflectance with BRDF-based reflectance predictions of each soil surface type for the specific illumination and viewing geometry of the pixel.The results show that most hydrological soil surface classes have distinct bi-directional radiometric properties. For one given geometric configuration however, the predicted reflectance ranges of some classes can considerably overlap (tilled soils and stone layers for example), while others can always unambiguously be identified (bare soil crusts, surfaces covered for more than 50% by weed or litter).We conclude that our fuzzy classification approach and the simple radiometric information used, allow us to identify the majority of the hydrological surface types. The method can easily be transposed in time and space. Its performance quite strongly depends on the radiometric and geometric accuracy of the input data. Significant improvements in soil surface classification precision are expected from considering spatial context information and monitoring the soil surface evolution.     

西吉县黄家二岔小流域彩红外航片判读与制图

以目视判读为主,并辅以立体镜分析与地面踏查收集资料相结合的方法,对1∶1万彩红外航片进行了判读,根据土地类型、土地利用现状和坡度分级的分类原则,获得了影像的判读标志与专题系列图,同时对1∶1万彩红外航片的影像利用效果进行了讨论。实践证明,利用该手段制图比常规调查方法提高效率5～6倍,不同土地类型的判读精度在95％以上,林地类型影像判读精度可达90％,农地与人工草地判读精度达80％,不同地类的侵蚀程度的判读精度也达85％以上。1∶1万彩红外航片可以直观地反映各种自然和社会因素的综合效果,是小流域动态监测的一种必不可少的有效手段。     

利用遥感信息对呼市大气污染的研究

环境的问题是世界性问题。空气质量直接关系到人们的生产和生活。以及人类的生命健康。现在遥感技术的迅速发展，为大握环境质量的评价提供了有效的途径。使用彩红外航空象片地调查的方法，对大气质量评价和结果分析发挥很大的作用。     

基于Agisoft PhotoScan的无人机影像快速拼接在新农村规划中的应用

以新农村建设规划中存在的问题为基础,提出了基于Agisoft Photo Scan无人机影像的快速拼接方法在新农村建设规划中的应用,给新农村建设规划测量带来了极大的便利,可满足新农村建设的需要。     

航空摄影测量像片的几何关系分析

本文以航空摄影测量像片为分析对象．根据中心投影的特性,论述了像片在倾斜条件下所引起的像点位移和像片因地面起伏而引起的像点位移,在对其进行分析的基础上总结出倾斜误差和投影误差的规律,从而说明了不能把像片当作地形图使用．这是使用航空像片时必须注意的基本问题     

基于无人机遥感影像的大豆叶面积指数反演研究

作物叶面积指数的遥感反演是农业定量遥感研究热点之一,利用无人机遥感监测系统获取农作物光谱信息精确反演叶面积指数对精准农业生产与管理意义重大。本研究以山东省嘉祥县一带的大豆种植区为试验区,设计以多旋翼无人机为平台同步搭载Canon Power Shot G16数码相机和ADC-Lite多光谱传感器组成的无人机农情监测系统开展试验,分别获取大豆结荚期和鼓粒期的遥感影像。使用比值植被指数(RVI)、归一化植被指数(NDVI)、土壤调整植被指数(SAVI)、差值植被指数(DVI)、三角植被指数(TVI)5种植被指数,结合田间同步实测叶面积指数(leaf area index,LAI)数据,采用经验模型法分别构建了单变量和多变量LAI反演模型,通过决定系数(R2)、均方根误差(RMSE)和估测精度(EA)3个指标筛选出最佳模型。研究表明,有选择性地分时期进行农作物的叶面积指数反演是必要的,鼓粒期作为2个生育期中大豆LAI反演的最佳时期,其NDVI线性回归模型对大豆LAI的解释能力最强,R2=0.829,RMSE=0.301,反演大豆LAI最准确,EA=85.4%,生成的鼓粒期大豆LAI分布图反映了当地当时大豆真实长势情况。因此,以多旋翼无人机为平台同步搭载高清数码相机和多光谱传感器组成的无人机农情监测系统对研究大豆叶面积指数反演是可行性,可作为指导精准农业研究的一种新方法。     

小区植被覆盖度动态快速测量方法研究

选择北京密云、怀柔的2块农地作为样地,对照相法测量植被覆盖度的效果进行了分析,并将之与目估法进行了对比。结果显示照相结合数字图像处理计算植被覆盖度的方法便捷客观,计算植被覆盖度的最大绝对误差不到5%,而目估法测量植被覆盖度具有明显的不可靠性,不同人的目估结果有明显差异。图像分类计算覆盖度的最大误差只相当于个人目估最大绝对误差的10.9%,相当于7人目估平均最大绝对误差的43.1%。     

长春遥感试验区航片土地利用现状解译

本文利用近期黑白航摄像片,依据土地利用现状分类系统,通过室内判读和外业调绘,对各个类型单元进行解译,提出了土地利用现状类型单元航片上的主要影像特征,建立了解译标志.为土地资源详查提供参考资料。