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661.
A model of the shape of Toutatis based on “high-resolution” radar images obtained in 1992 and 1996 consists of 39,996 triangular facets of roughly equal area, defined by the locations of 20,000 vertices. These define the average spatial resolution of the model as approximately 34 m, significantly finer than Hudson and Ostro’s (1995, Science 270, 84-86) model (1600 vertices, resolution 84 m). The high-resolution model reveals complex linear features as well as circular crater-like structures down to the resolution limit. There is a dichotomy between the gravitational slope distributions on the asteroid’s two lobes. The noncraterlike features may be the manifestation of complex interior configurations involving monolithic fragments with various sizes and shapes, presumably due to collisions in various energy regimes. However, it may be impossible to decipher the interior structure and responsible collisional history of Toutatis and other small objects without extended, intensive, direct examination. 相似文献
662.
云南天文台的H-alpha太阳色球望远镜每天的数据量约有2G bytes，大量数据带来了使用上的不便。因此，实现数据的查询和共享成为了一个相当重要的问题。为此，试图通过建立H-alpha数据的管理系统，实现对工作流程的改进，完成对数据的检索、在线浏览和远程下载。在WindwsXP操作系统和MysQL数据库管理系统的平台上，利用JAVA语言和JSP技术开发了一个基于浏览器／服务器模式的原型系统，可以完成对数据的压缩存储，实现数据的检索、实时浏览、删除(需要相应权限)和下载等功能。 相似文献
663.
Pixel-based image compositing enables production of large-area surface reflectance images that are largely devoid of clouds, cloud shadows, or haze. Change detection with spectral trend analysis uses a dense time series of images, such as pixel-based composites, to quantify the year, amount, and magnitude of landscape changes. Topographically-related shadows found in mountainous terrain may confound trend-based forest change detection approaches. In this study, we evaluate the impact of topographic correction on trend-based forest change detection outcomes by comparing the amount and location of changes identified on an image composite with and without a topographic correction. Moreover, we evaluated two different approaches to topographic correction that are relevant to pixel-based image composites: the first corrects each pixel according to the day of year (DOY) the pixel was acquired, whilst the second corrects all pixels to a single reference date (August 1st), which was also the target date for generating the pixel-based image composite. Our results indicate that a greater area of change is detected when no topographic correction is applied to the image composite, however, the difference in change area detected between no correction and either the DOY or the August 1st correction is minor and less than 1% (0.54–0.85%). The spatial correspondence of these different approaches is 96.2% for the DOY correction and 97.7% for the August 1st correction. The largest differences between the correction processes occur in valleys (0.71–1.14%), upper slopes (0.71–1.09%), and ridges (0.73–1.09%). While additional tests under different conditions and in other environments are encouraged, our results indicate that topographic correction may not be justified in change detection routines computing spectral trends from pixel-based composites. 相似文献
664.
Image classification from remote sensing is becoming increasingly urgent for monitoring environmental changes. Exploring effective algorithms to increase classification accuracy is critical. This paper explores the use of multispectral HJ1B and ALOS (Advanced Land Observing Satellite) PALSAR L-band (Phased Array type L-band Synthetic Aperture Radar) for land cover classification using learning-based algorithms. Pixel-based and object-based image analysis approaches for classifying HJ1B data and the HJ1B and ALOS/PALSAR fused-images were compared using two machine learning algorithms, support vector machine (SVM) and random forest (RF), to test which algorithm can achieve the best classification accuracy in arid and semiarid regions. The overall accuracies of the pixel-based (Fused data: 79.0%; HJ1B data: 81.46%) and object-based classifications (Fused data: 80.0%; HJ1B data: 76.9%) were relatively close when using the SVM classifier. The pixel-based classification achieved a high overall accuracy (85.5%) using the RF algorithm for classifying the fused data, whereas the RF classifier using the object-based image analysis produced a lower overall accuracy (70.2%). The study demonstrates that the pixel-based classification utilized fewer variables and performed relatively better than the object-based classification using HJ1B imagery and the fused data. Generally, the integration of the HJ1B and ALOS/PALSAR imagery can improve the overall accuracy of 5.7% using the pixel-based image analysis and RF classifier. 相似文献
665.
We aim to relate the morphology of the pore network of finely porous claystones to their fluid transport properties. By using Focused Ion Beam in combination with Scanning Electron Microscopy (FIB/SEM), we image the pore network of COx claystone from 2D image stacks and as 3D reconstructed volumes. Our FIB/SEM samples are representative of the mesoscopic matrix clay. Porosity resolvable by this technique is in the range 1.7–5.9% with peak pore sizes of 50–90 nm. 3D pore network skeletonization provides connected pore volumes between end surfaces, tortuosity, density, and shortest pore paths with their pore size distribution. At higher resolution, 2D transmission electron microscopy (TEM) reveals large amounts of smaller pores (2–20 nm) between clay aggregates, associated to a local porosity of 14–25%, and peak sizes of 4–6 nm. Liquid permeability predictions with Katz–Thompson model, at the FIB/SEM volume scale and at the TEM surface scale, are in good agreement with macroscopic measurements (on the order of 10−20 m2), showing that both mesopore sizes (peaks at 50–90 nm and 4–6 nm), located within the clay matrix, contribute to liquid transport. 相似文献
666.
以三江源测区为研究对象,采用传统法和影像自动匹配法进行DEM制作。通过试验研究及对比分析发现:两种方法制作的DEM均能满足精度要求,传统法精度高,过程流畅,工艺纯熟,不足之处是工期较长;影像自动匹配法制作的DEM精度虽不及传统法高,但其工期短,工效是传统法的5倍左右。考虑到在满足精度要求的前提下,作为提高作业效率的一种方法,影像自动匹配法大规模制作DEM可应用于实际生产。 相似文献
667.
Integration of WorldView-2 satellite image with small footprint airborne LiDAR data for estimation of tree carbon at species level has been investigated in tropical forests of Nepal. This research aims to quantify and map carbon stock for dominant tree species in Chitwan district of central Nepal. Object based image analysis and supervised nearest neighbor classification methods were deployed for tree canopy retrieval and species level classification respectively. Initially, six dominant tree species (Shorea robusta, Schima wallichii, Lagerstroemia parviflora, Terminalia tomentosa, Mallotus philippinensis and Semecarpus anacardium) were able to be identified and mapped through image classification. The result showed a 76% accuracy of segmentation and 1970.99 as best average separability. Tree canopy height model (CHM) was extracted based on LiDAR’s first and last return from an entire study area. On average, a significant correlation coefficient (r) between canopy projection area (CPA) and carbon; height and carbon; and CPA and height were obtained as 0.73, 0.76 and 0.63, respectively for correctly detected trees. Carbon stock model validation results showed regression models being able to explain up to 94%, 78%, 76%, 84% and 78% of variations in carbon estimation for the following tree species: S. robusta, L. parviflora, T. tomentosa, S. wallichii and others (combination of rest tree species). 相似文献
668.
669.
Bruno Capaccioni Laura Valentini Marco B. L. Rocchi Giovanni Nappi Damiano Sarocchi 《Bulletin of Volcanology》1997,58(7):501-514
Computer-assisted image analysis can be successfully used to derive quantitative textural data on pyroclastic rock samples.
This method provides a large number of different measurements such as grain size, particle shape and 2D orientation of particle
main axes (directional- or shape-fabric) automatically and in a relatively short time. Orientation data reduction requires
specific statistical tests, mainly devoted to defining the kind of particle distribution pattern, the possible occurrence
of preferred particle orientation, the confidence interval of the mean direction and the degree of randomness with respect
to pre-assigned theoretical frequency distributions. Data obtained from image analysis of seven lithified ignimbrite samples
from the Vulsini Volcanic District (Central Italy) are used to test different statistics and to provide insight about directional
fabrics. First, the possible occurrence of a significant deviation from a theoretical circular uniform distribution was evaluated
by using the Rayleigh and Tukey χ
2 tests. Then, the Kuiper test was performed to evaluate whether or not the observation fits with a unimodal, Von Mises-like
theoretical frequency distribution. Finally, the confidence interval of mean direction was calculated. With the exception
of one sample (FPD10), which showed a well-developed bimodality, all the analysed samples display significant anisotropic
and unimodal distributions. The minimum number of measurements necessary to obtain reasonable variabilities of the calculated
statistics and mean directions was evaluated by repeating random collections of the measured particles at increments of 100
particles for each sample. Although the observed variabilities depend largely on the pattern of distribution and an absolute
minimum number cannot be stated, approximately 1500–2000 measurements are required in order to get meaningful mean directions
for the analysed samples.
Received: 9 April 1996 / Accepted: 26 December 1996 相似文献
670.