The calculation of surface area is meaningful for a variety of space-filling phenomena, e.g., the packing of plants or animals within an area of land. With Digital Elevation Model (DEM) data we can calculate the surface area by using a continuous surface model, such as by the Triangulated Irregular Network (TIN). However, just as the triangle-based surface area discussed in this paper, the surface area is generally biased because it is a nonlinear mapping about the DEM data which contain measurement errors. To reduce the bias in the surface area, we propose a second-order bias correction by applying nonlinear error propagation to the triangle-based surface area. This process reveals that the random errors in the DEM data result in a bias in the triangle-based surface area while the systematic errors in the DEM data can be reduced by using the height differences. The bias is theoretically given by a probability integral which can be approximated by numerical approaches including the numerical integral and the Monte Carlo method; but these approaches need a theoretical distribution assumption about the DEM measurement errors, and have a very high computational cost. In most cases, we only have variance information on the measurement errors; thus, a bias estimation based on nonlinear error propagation is proposed. Based on the second-order bias estimation proposed, the variance of the surface area can be improved immediately by removing the bias from the original variance estimation. The main results are verified by the Monte Carlo method and by the numerical integral. They show that an unbiased surface area can be obtained by removing the proposed bias estimation from the triangle-based surface area originally calculated from the DEM data. 相似文献
Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region. 相似文献
Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVID) was derived, and the global and local Moran’s I of the SVID were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVID values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.
Based on the field data acquired in the program of fast ice observation off Zhongshan Station, Prydz Bay, East Antarctica during the austral summer 2005/ 2006, physical properties evolution of fast ice during the ice ablation season is analyzed in detail. Results show that the annual maximum ice thickness in 2005 occurred in later November, and then ice started to reek, and the ablation duration was 62 days; sea water under the ice became warmer synchronously; corresponding to the warming sea ice temperature, a "relative cold mid-layer" appeared in sea ice; the fast ice marginal line recoiled back to the shore observably, and the recoil distance was 20.9 km from 18 December 2005 through 14 January 2006. In addition, based on the data of sea ice thickness survey along the investigation course of MV Xuelong on December 18 of 2005, the ice thickness distribution paten in the marginal ice zone have been described : sea ice thickness increased, but the diversity of floe ice thick-ness decreased from open water to fast ice zone distinctly. 相似文献
Based on the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data from 1950-1999, interdecadal variability of the East Asian Summer Monsoon (EASM) and its associated atmospheric circulations are investigated. The EASM exhibits a distinct interdecadal variation, with stronger (weaker) summer monsoon maintained from 1950-1964 (1976-1997). In the former case, there is an enhanced Walker cell in the eastern Pacific and an anti-Walker cell in the western Pacific. The associated ascending motion resides in the central Pacific, which flows eastward and westward in the upper troposphere, descending in the eastern and western ends of the Pacific basin. At the same time, an anomalous East Asian Hadley Cell (EAHC) is found to connect the low-latitude and mid-latitude systems in East Asia, which strengthens the EASM. The descending branch of the EAHC lies in the west part of the anti-Walker cell, flowing northward in the lower troposphere and then ascending at the south of Lake Baikal (40°-50°N, 95°- 115°E) before returning to low latitudes in the upper troposphere, thus strengthening the EASM. The relationship between the EASM and SST in the eastern tropical Pacific is also discussed. A possible mechanism is proposed to link interdecadal variation of the EASM with the eastern tropical Pacific SST. A warmer sea surface temperature anomaly (SSTA) therein induces anomalous ascending motion in the eastern Pacific, resulting in a weaker Walker cell, and at the same time inducing an anomalous Walker cell in the western Pacific and an enhanced EAHC, leading to a weaker EASM. Furthermore, the interdecadal variation of summer precipitation over North China is found to be the south of Lake Baikal through enhancing and reducing strongly regulated by the velocity potential over the regional vertical motions. 相似文献