Building Capacity for Environmental Management: local knowledge and rehabilitation on the Gippsland Red Gum Plains

Community-based natural resource management (CBNRM) continues to attract interest as a way of achieving social and environmental outcomes at the local and regional scale. Central to the success of CBNRM is the importance of capacity building and participatory approaches to research and management. This paper discusses an initiative in East Gippsland which involved a facilitated process to assist local residents build their capacity to manage their landscape. Through conducting a community survey, the project facilitated landholders to voice, develop and refine their understanding of remnant vegetation management, dieback and revegetation on private land. In doing so, landholders have improved not only their understanding of the issues but also their ability to act upon them. The empirical findings of the study highlight two issues of relevance to dieback on the East Gippsland Red Gum Plains. First, there is a perception that dieback has remained stable for at least 10 years. Second, scattered trees and small patches of trees are more vulnerable to dieback than clumped trees in larger patch sizes, as well as roadside vegetation. The research demonstrates the value of a community-based approach to NRM in terms of harnessing local knowledge, fostering human and social capital and engaging with interested landholders.     

三层套合方差分析在区域化探中的应用及计算机实现——以新疆某地1:50 000区域化探为例

在区域化探中必须应用三层套合方差分析对样品的采样误差和分析误差进行统计分析。这里结合实例分析了该方法的计算模型,给出了计算流程,并应用VB语言实现了该统计方法。通过应用证明,该程序算法合理、操作简单、大大提高了工作效率。并且,该程序可以应用到其它领域对样品质量的分析评估。     

LOCAL LABOR MARKETS: THEORIES AND POLICIES IN THE U.S. DURING THE 1970s*

Local labor market policies of the federal government are critically evaluated with respect to their target efficiency and underlying theoretical assumptions. Policies of the Economic Development Administration are considered to be target inefficient compared to those of the Comprehensive Employment Training Act. Experimental mobility policies of the Department of Labor appear to be have questionable impact locally as opposed to nationally. Some local hybrid programs offer improved place and people targeting.     

Effect of heteroscedasticity and heterogeneousness on outlier detection for geodetic networks

The robustness of an outlier detection method strongly depends on the weights of observations, i.e., the type of the stochastic model applied (homoscedasticity, heteroscedasticity and heterogeneousness). In this paper, we have investigated how the reliability of the robust methods and tests for outliers changes depending on the weights of the observations in geodetic networks. Furthermore, the contribution of the directions and distances to horizontal control network with regard to reliability are investigated separately. The concept of a breakdown point is used as a global measure of robustness against outliers. The mean success rate (MSR) is found to be a practical tool for confirming the breakdown point. Many different “good” data samples are generated for each network and then deliberately contaminated using a Monte-Carlo simulation. Six robust methods and Baarda’s test are applied to the corrupted samples and the degree of corruption is varied. The performance of each method is measured using both local and global MSRs. Our research shows: (1) The MSRs of Baarda’s test change depending on the strength of the heteroscedasticity, but do not change for trilateration and leveling networks, (2) the global MSRs of robust methods do not differ considerably from the local ones     

GALILEO系统完备性指标SISMA的计算和分析

利用GALILEO全球监测网络和中国地壳运动监测网络分别对GALILEO系统完备性指标SISMA进行仿真计算。结果表明,全球完备性监测SISMA结果不稳定,随地理位置的变化较大,不能满足局部地区的生命安全服务要求;利用适当布设的局域监测网络进行的SISMA局域监测数值稳定,变化较小,结果明显优于全球SISMA监测结果,可以满足生命安全服务要求,可信度达到100%。在我国进行局域SISMA监测,是对全球完备性监测进行的有效和必要补充,提高系统的可用性和定位可信度。     

基于地震同相轴预测的剩余静校正方法研究

为解决野外地表参数测定不准确等因素引起的地震数据剩余静校正问题,通过平面波分解滤波器计算时空变地震同相轴局部倾角,利用局部倾角与同相轴的时空预测量之间的关系计算剩余静校正量,在剩余静校正量计算所需局部平面波方程求解过程中,加入时间方向倾角为常数的整形正则化约束条件,以保证剩余静校正方法的准确性。结果表明,基于地震同相轴预测的剩余静校正方法可以有效地处理共中心点道集数据的剩余静校正问题,同时本方法具有一定的抗噪能力,为实际资料处理提供了较好的适用性。     

基于无人机影像密集匹配点云的传统村落地面点提取及DEM生成——以湘西德夯村为例

目前,针对利用无人机技术在山地起伏大、山体植被密集区域,难以获取地面点及DEM等问题,本文提出了一种结合布料模拟算法和改进的局部最大值算法,利用树顶点、树高等植被信息,提取地面点,进而生成整个区域的DEM的方法。以中国传统村落德夯村为例,利用植被系数和高程信息将点云分割为植被密集区和非植被密集区两个部分。在非植被密集区,通过布料模拟算法和改进的局部最大值算法分别提取地面点和树顶点,计算平均树高;在植被密集区,通过该区域的树顶点推算得到植被密集区的近似地面点,最终将两部分的地面点云进行TIN插值得到该地区的DEM。试验结果表明,利用此方法生成的DEM均方根误差,在非植被密集区达0.037 m,植被密集区可达1.606 m,整体平均误差达1.492 m,总体精度较好,基本可以满足村落尺度空间分析的需求。