The use of Landsat imagery to assess large-scale forest cover changes in space and time,minimizing false-positive changes

A new approach, based on the application of multi-spectral remote sensing data of Landsat imagery, is introduced to determine large-scale spatiotemporal variations of forest cover changes quantitatively and with a high degree of precision. The test area covers about 837,330.5 ha of a mountainous region in Central Italy. The approach employs several multi-temporal Landsat acquisitions to account for forest cover changes larger than 0.5 ha for the period from March 2002 to July 2011. In contrast to automated approaches that strongly curtail mapping time, the approach introduced here allowed us to map only the real forest cover change, based on a robust validation and rectification of the detected forest change. Derived high spatial resolution data of forest change estimates indicate that about 5.7% (47,670.5 ha) of the observed forest area was subject to human-induced change between 2002 and 2011. Moreover, the detected forest cover changes, most of which are identifiable as timber harvesting, are considerably larger than those reported in the official statistics and often fall within the perimeter of restricted areas (i.e., national parks and natural reserves).     

中古志怪小说女性形象塑造艺术浅析

在人物描写方面，魏晋南北朝志怪小说不像以后的小说那样神形兼备，甚至基本上没有肖像描写，但志怪小说的作者已经开始注意表现所写人物的特定情感和个性，使人物形象具有了一定程度的可感性和生动性。浪漫主义象征性艺术手法、第三人称限知叙事、相对生动细致的细节描写、人物对话、诗歌辞赋的运用以及描写的多样性在一定程度上完成了人物形象塑造和性格揭示，一些优秀篇章中的女性形象塑造，都已达到了生动鲜明、栩栩如生的程度。即便这些只是处在萌芽阶段的尝试，却对后世产生了深远的影响。     

Shape, size and multiplicity of main-belt asteroids: I. Keck Adaptive Optics survey

This paper presents results from a high spatial resolution survey of 33 main-belt asteroids with diameters >40 km using the Keck II Adaptive Optics (AO) facility. Five of these (45 Eugenia, 87 Sylvia, 107 Camilla, 121 Hermione, 130 Elektra) were confirmed to have satellite. Assuming the same albedo as the primary, these moonlets are relatively small (∼5% of the primary size) suggesting that they are fragments captured after a disruptive collision of a parent body or captured ejecta due to an impact. For each asteroid, we have estimated the minimum size of a moonlet that can positively detected within the Hill sphere of the system by estimating and modeling a 2-σ detection profile: in average on the data set, a moonlet located at 2/100×RHill (1/4×RHill) with a diameter larger than 6 km (4 km) would have been unambiguously seen. The apparent size and shape of each asteroid was estimated after deconvolution using a new algorithm called AIDA. The mean diameter for the majority of asteroids is in good agreement with IRAS radiometric measurements, though for asteroids with a D<200 km, it is underestimated on average by 6-8%. Most asteroids had a size ratio that was very close to those determined by lightcurve measurements. One observation of 104 Klymene suggests it has a bifurcated shape. The bi-lobed shape of 121 Hermione described in Marchis et al. [Marchis, F., Hestroffer, D., Descamps, P., Berthier, J., Laver, C., de Pater, I., 2005c. Icarus 178, 450-464] was confirmed after deconvolution. The ratio of contact binaries in our survey, which is limited to asteroids larger than 40 km, is surprisingly high (∼6%), suggesting that a non-single configuration is common in the main-belt. Several asteroids have been analyzed with lightcurve inversions. We compared lightcurve inversion models for plane-of-sky predictions with the observed images (9 Metis, 52 Europa, 87 Sylvia, 130 Elektra, 192 Nausikaa, and 423 Diotima, 511 Davida). The AO images allowed us to determine a unique photometric mirror pole solution, which is normally ambiguous for asteroids moving close to the plane of the ecliptic (e.g., 192 Nausikaa and 52 Europa). The photometric inversion models agree well with the AO images, thus confirming the validity of both the lightcurve inversion method and the AO image reduction technique.     

High-resolution model of Asteroid 4179 Toutatis

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.     

H-alpha太阳全日面像数据管理系统的建立

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。     

Effect of topographic correction on forest change detection using spectral trend analysis of Landsat pixel-based composites

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.     

Fusion of HJ1B and ALOS PALSAR data for land cover classification using machine learning methods

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.     

Multi-scale pore structure of COx claystone: Towards the prediction of fluid transport

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.     

高分辨率遥感影像自动生成DEM的研究

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。     

Integration of WorldView-2 and airborne LiDAR data for tree species level carbon stock mapping in Kayar Khola watershed,Nepal

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).