Framing the application of adaptation pathways for rural livelihoods and global change in eastern Indonesian islands

In developing countries adaptation responses to climate and global change should be integrated with human development to generate no regrets, co-benefit strategies for the rural poor, but there are few examples of how to achieve this. The adaptation pathways approach provides a potentially useful decision-making framework because it aims to steer societies towards sustainable futures by accounting for complex systems, uncertainty and contested multi-stakeholder arenas, and by maintaining adaptation options. Using Nusa Tenggara Barat Province, Indonesia, as an example we consider whether generic justifications for adaptation pathways are tenable in the local context of climate and global change, rural poverty and development. Interviews and focus groups held with a cross-section of provincial leaders showed that the causes of community vulnerability are indeed highly complex and dynamic, influenced by 20 interacting drivers, of which climate variability and change are only two. Climate change interacts with population growth and ecosystem degradation to reduce land, water and food availability. Although poverty is resilient due to corruption, traditional institutions and fatalism, there is also considerable system flux due to decentralisation, modernisation and erosion of traditional culture. Together with several thresholds in drivers, potential shocks and paradoxes, these characteristics result in unpredictable system trajectories. Decision-making is also contested due to tensions around formal and informal leadership, corruption, community participation in planning and female empowerment. Based on this context we propose an adaptation pathways approach which can address the proximate and systemic causes of vulnerability and contested decision-making. Appropriate participatory processes and governance structures are suggested, including integrated livelihoods and multi-scale systems analysis, scenario planning, adaptive co-management and ‘livelihood innovation niches’. We briefly discuss how this framing of adaptation pathways would differ from one in the developed context of neighbouring Australia, including the influence of the province's island geography on the heterogeneity of livelihoods and climate change, the pre-eminence and rapid change of social drivers, and the necessity to ‘leap-frog’ the Millennium Development Goals by mid-century to build adaptive capacity for imminent climate change impacts.     

WUSH-TV2型超声蒸发传感器的安装与维护

介绍WUSH-TV2型超声蒸发传感器的系统组成、工作原理以及安装方法,并对实际工作运行中遇到的故障进行分析,提出了合理的保障维护方法和处理思路.     

Application of a fuzzy inference system for the prediction of longshore sediment transport

A fuzzy inference system (FIS) and a hybrid adaptive network-based fuzzy inference system (ANFIS), which combines a fuzzy inference system and a neural network, are used to predict and model longshore sediment transport (LST). The measurement data (field and experimental data) obtained from Kamphuis [1] and Smith et al. [2] were used to develop the model. The FIS and ANFIS models employ five inputs (breaking wave height, breaking wave angle, slope at the breaking point, peak wave period and median grain size) and one output (longshore sediment transport rate). The criteria used to measure the performances of the models include the bias, the root mean square error, the scatter index and the coefficients of determination and correlation. The results indicate that the ANFIS model is superior to the FIS model for predicting LST rates. To verify the ANFIS model, the model was applied to the Karaburun coastal region, which is located along the southwestern coast of the Black Sea. The LST rates obtained from the ANFIS model were compared with the field measurements, the CERC [3] formula, the Kamphuis [1] formula and the numerical model (LITPACK). The percentages of error between the measured rates and the calculated LST rates based on the ANFIS method, the CERC formula (K_sig = 0.39), the calibrated CERC formula (K_sig = 0.08), the Kamphuis [1] formula and the numerical model (LITPACK) are 6.5%, 413.9%, 6.9%, 15.3% and 18.1%, respectively. The comparison of the results suggests that the ANFIS model is superior to the FIS model for predicting LST rates and performs significantly better than the tested empirical formulas and the numerical model.     

Debris flow disaster prevention and mitigation of non-structural strategies in Taiwan

Taiwan has disadvantageous conditions for sediment-related disasters such as debris flows. The construction of engineering structures is an effective strategy for reducing debris flow disasters. However, it is impossible to construct engineering structures in all debris flow areas in a short period. Therefore, the government aims to gradually develop non-structural preventive strategies, including evacuation planning, debris flow disaster emergency action system, disaster resistant community program, recruitment of debris flow professional volunteers, debris flow warning systems, and land management strategies, to mitigate disasters and secure the safety of residents. This review describes the processes and effects of recent debris flow non-structural preventive strategies in Taiwan. The average number of casualties prior to the year 2000 was far higher than the corresponding number after 2000 because debris flow evacuation drills have been promoted since 2000 and the debris flow disaster emergency action system has been progressively improved since 2002. Furthermore, the changes in risks caused by debris flow disasters before and after the implementation of non-structural preventive strategies were used to explain the effectiveness of these strategies at the community level. The results showed that software-based non-structural preventive strategies can effectively reduce the casualties caused by debris flows at both the national and community levels.     

自适应变异粒子群优化灰色模型在变形分析中的应用

标准灰色模型GM(1,1)以序列第一个分量作为初始条件进行灰色微分建模,未能充分利用序列中的新信息;其背景值的构造本质上采用了数值积分中的梯形法,精度不高。针对上述缺点,提出一种基于粒子群算法的灰色预测模型,即PSOGM(1,1)模型,对初始值和背景值参数进行优化,并将模型应用于岩体变形分析中。计算结果表明,PSOGM(1,1)模型具有较高的预测精度,可作为变形分析的一种新方法。     

数字天顶摄像仪中CCD星象亚像素定位的改进二维矩方法

在利用数字天顶摄像仪通过天文测量确定天文垂线偏差的工作中,要求对CCD数字图像中星象中心进行亚像素定位。本文利用MATLAB实现对FITS格式CCD天文图像的正常读取,并与FV读取结果比较分析。在已有亚像素定位的修正矩方法基础上,提出一种利用迭代法寻求合适门限对二维修正矩方法进行改善。利用MATLAB实现对实测图像数据的处理与分析,探讨门限的取值对不同星等恒星定位精度的影响,给出门限的最佳取值。通过与已有修正矩算法处理结果比较分析,在以往修正矩方法计算基础上改进计算区域后再用迭代法计算,暗星定位精度有了很大提高。     

实现遥感相机自主辨云的小波SCM算法

随着遥感相机分辨力的提高和幅宽的增大,星上固存和数传带宽面临巨大的挑战。提出一种多分支云判别算法,可控制相机在有云区关机停拍。首先利用计算量较小的光谱阈值判别法对云和地物粗略分类,在不能确定云或地物时,采用纹理分析方法判别。为减小误判可能,算法采用小波SCM提取纹理特征,并提出一种基于ASM和熵的双判别方式。通过对24．5幅遥感图像进行试验验证,证明该算法能快速准确识别云层和地物,总误判率小于5％。     

基于ERDAS平台的NDVI植被覆盖变化检测

介绍了利用ERDAS IMAGINE软件对多时相遥感影像进行地表植被覆盖变化检测的方法及过程,采用归一化植被指数差值法,得到包含多时相遥感影像变化信息的差异图像,依据差异图像的灰度直方图分布情况,结合经验公式设置变化阈值来分离变化信息和非变化信息。     

两种GPS天线阵列抗干扰算法研究及仿真

介绍了自适应天线阵列信号响应的数学描述,论述了在GPS抗干扰应用中广泛采用的基于最小均平方（LMS）的自适应算法的原理和实现过程,并对算法进行了仿真。提出了一种优于LMS算法的自适应数字波束形成（DBF）技术,推导出了其最优权系数矢量的计算方法,并对该算法进行了仿真。仿真结果表明：4阵元LMS的自适应调零算法对于单干扰的抑制和双干扰的抑制都达到了较好的效果,同时也体现了该算法零陷的优点。     

利用改进的SUSAN算法提取航空影像中孤立的特征点

本文针对地形起伏较大、无明显建筑物的航空影像,分析了SUSAN算法角点检测理论,提出一种提取孤立特征点的方法.该方法先对图像进行梯度幅值运算,然后对梯度幅值进行Otsu法阈值分割,设计模板并对孤立特征点进行套合,最后利用SUSAN算法计算原始影像的角点初始响应,经过非极大值抑制提取孤立特征点.经实骑证明,与传统的Har...