无人机影像的面向对象水稻种植面积快速提取

基于抽样技术的地面调查与遥感影像分类相结合的方法在大范围作物种植面积提取中得到广泛使用。无人机影像具有低成本、高时效、高分辨率的一系列优点,可以快速实现特定区域范围内的农情采样任务。本文以水稻样地为研究对象,采用便携式无人机Mavic Pro进行航拍。对所获取无人机影像进行预处理生成分辨率为3.95cm/pix的正射影像,采用面向对象的思想,目视评价和ESP工具相结合快速选择了最优分割尺度为300,应用了支持向量机、随机森林和最邻近监督分类方法对影像进行了地物分类和水稻面积快速提取。采用目视解译分类结果进行分类结果和面积精度评价,总体精度最高的方法为最邻近分类法,此时水稻分类用户精度为95%,面积一致性精度为99%。研究结果说明了无人机遥感和自动分类能够在平原水稻种植区快速获取样方内高分辨率影像并提取水稻种植面积,弥补了农田被遮挡时地面调查数据的缺失,为大范围水稻种植面积、产量等信息的计算提供样本和验证依据。     

改进加权距离定位算法在室内定位中的应用

基于RSSI(Received Signal Strength Indication)的距离测量技术是一种新型低成本的距离测量技术,并且在距离定位的领域中得到广泛的运用。针对常规的Zigbee指纹定位的加权最邻近定位算法较为复杂且精度低下的问题,该文对基于RSSI的Zigbee指纹数据库定位算法中加权最邻近算法进行了研究,提出了利用一种新的加权距离定位算法,并且使用Zigbee无线网络系统进行实验。结果表明,使用加权定位算法后,与常规的3种定位算法相比,Zigbee定位系统的定位偏差得到一定程度的提高且优于1.57m。     

一种基于点法矢的三维非均匀栅格压缩算法

提出一种适用于散乱点云的基于点云法矢量的三维非均匀栅格压缩算法,通过求取k邻近构造出点云的法矢量以反映曲面形状信息,并构造八叉树数据结构对栅格进行细分,通过比较分析,该方法取得了较好的压缩效果。     

DEM构建中的断裂线处理

根据断裂线在地表曲面中的数学性质,将断裂线分为硬断裂线和软断裂线,处理软断裂线时采用修改采样点权值的方法,处理硬断裂线时采用直接划分两侧采样点的方法。实验结果表明,该方法思路简单、容易实现,计算结果精度较高。     

中巴地球资源一号卫星CCD图像色差自动消除方法研究

 采用CBERS-02星CCD数据，提出一种基于统计的最邻近法，该方法能自动消除中巴地球资源一号卫星CCD图像上的色差，不 仅能取代传统的手工方法，而且可大幅度提高CBERS-02星CCD预处理系统的生产能力，为中巴地球资源一号卫星数据的广泛应用奠 定基础。     

Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines – SVM), and hybrid (unsupervised–supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different depending on land use/cover classes. Early-growth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land use/cover classes were mapped with producer's and user's accuracies of ∼90%. Our classification approach seems very well suited to accurately map land use/cover of heterogeneous landscapes, thus having great potential to contribute to climate change mitigation schemes, conservation initiatives, and the design of management plans and rural development policies.     

基于DEM数据的古沉积面的重建方法——以青藏高原东北缘青海贵德盆地为例

广泛使用的数字高程模型（DEM）数据使得古沉积面的恢复成为可能。以青藏高原东北缘的青海贵德盆地为例,分析对比了前人获取代表古沉积面地表露头样本数据的几种方法．提出了插值样本应选择露头中代表原始沉积地层的顶面点的优选方法,并提取了更新统地表露头顶面点的样本数据。通过分析样本的特征、比较插值的结果,选择了自然邻点法进行插值预测,重建了贵德盆地更新统的古沉积面。正确样本,最的提取加上合适插值算法的选择．优化了重建的古沉积面。     

基于最邻近时空距离的土地变化过程时空模式分析

土地利用/土地覆盖受人类活动和城市的快速扩张的影响发生了巨大的变化,这种变化对生态环境和地表景观的影响极大。土地利用/土地覆盖的变化过程既受自然、经济等多种因素的影响,也是人类活动规律和自然因素制约的外部表征。因此研究土地利用/土地覆盖的变化过程具有重要的意义。土地利用/覆盖变化的监测和分析,在传统的方法中侧重于分别对各个时空快照上土地利用结构的整体差异的研究,割裂了不同快照间土地利用单元在演化过程上的有机联系。本文以序列土地利用数据构成的土地变化过程为核心研究对象,在土地变化过程的最邻近时空距离度量的基础上,开展基于蒙特卡洛随机模拟的土地变化过程的时空聚集性度量,量化分析土地利用变化过程时空聚集模式的显著性。使用淮南市市辖区2008-2017年土地利用数据,选取典型的时空演化类型(任意2年间从"耕地"演变为"草地")进行实证研究,结果表明此类土地变化过程在过去10年呈现出时空聚集模式,但统计上并不显著。本文的研究有利于把握土地利用单元在时空上的演变过程,探查土地利用变化过程中潜在的时空演化模式。     

正则化距离准则的Wi-Fi位置指纹室内定位方法

针对K-近邻法中常规指纹相似度匹配准则未能充分利用测试点和参考点的几何距离信息问题,该文提出了正则化距离准则的Wi-Fi位置指纹室内定位方法。该方法较常规距离准则兼顾了测试点与参考点的指纹距离和可靠几何距离,仅增加了正则化距离和K-近邻位置估算的迭代流程。而且,该方法仅含一个正则化因子,确定方法简便且可解释性好。密集与稀疏参考点格网间距下智能手机Wi-Fi平面定位实验表明,所提方法在正则化距离准则下能够有效提高约20%的定位精度,其中曼氏和欧氏定位中误差不超过2m。     

Neighbor competition modifies demographic responses of desert dune annuals to gradients in sand stability

A field experiment was conducted to test the hypothesis that competitive interactions affect demographic responses of desert dune annuals to gradients in sand stability. The experiment was based on a three-way factorial design with two types of neighbor treatments (complete neighbor removalvs. control), two types of habitats (stablevs. unstable sands) and two species which characterize sandy areas of the western Negev Desert (Neurada procumbensandBromus fasciculatus). Each of the eight treatment/habitat/species combinations was characterized by three demographic variables: seedling survival to reproduction, fruit number per reproductive plant and fruit number per seedling. All of these variables exhibited significant interactions between the effects of neighbor removal and habitat type, indicating that neighbor conditions were important in determining the observed patterns of demographic variation. Moreover, while plants ofNeurada procumbensgrowing without neighbors suffered more mortality on unstable sands, conspecific plants growing at natural density conditions suffered more mortality on stable sands. In the case ofBromus fasciculatus, individuals growing in the absence of competitive effects produced more fruits on stable sands, but conspecific plants growing at natural density conditions exhibited higher fruit production on unstable sands. These findings indicate that competitive effects not only modify, but may even reverse demographic responses of desert dune annuals to gradients in sand stability. Based on these results and evidence from two other studies it is suggested that seed dispersal from abiotically favorable into less favorable habitats may increase fitness of desert annuals by reducing the average effect of competition.