Identifying environmental features for land management decisions

The major accomplishments of the Center for Remote Sensing and Cartography are outlined. The analysis and inventory of the Parker Mountain rangeland and the use of multitemporal data to study aspen succession stages are discussed. New and continuing projects are also described including a Salt Lake County land use study, Wasatch-Cache riparian study, and Humboldt River riparian habitat study. Finally, progress in digital processing techniques is reported

Evapotranspiration from an Olive Orchard using Remote Sensing-Based Dual Crop Coefficient Approach

A remote sensing-based approach to estimate actual evapotranspiration (ET) was tested in an area covered by olive trees and characterized by Mediterranean climate. The methodology is a modified version of the standard FAO-56 dual crop coefficient procedure, in which the crop potential transpiration, Tp, is obtained by directly applying the Penman-Monteith (PM) equation with actual canopy characteristics (i.e., leaf area index, albedo and canopy height) derived from optical remote sensing data. Due to the minimum requirement of in-situ ancillary inputs, the methodology is suitable also for applications on large areas where the use of tabled crop coefficient values become problematic, due to the need of corrections for specific crop parameters, i.e., percentage of ground cover, crop height, phenological cycles, etc. The methodology was applied using seven airborne remote sensing images acquired during spring-autumn 2008. The estimates based on PM approach always outperforms the ones obtained using simple crop coefficient constant values. Additionally, the comparison of simulated daily evapotranspiration and transpiration with the values observed by eddy correlation and sap flow techniques, respectively, shows a substantial agreement during both dry and wet days with an accuracy in the order of 0.5 and 0.3 mm d−1, respectively. The obtained results suggest the capability of the proposed approach to correctly partition evaporation and transpiration components during both the irrigation season and rainy period also under conditions of significant reduction of actual ET from the potential one

The Effect of Pilot and Air Traffic Control Experiences & Automation Management Strategies on UAS Mission Task Performance

Unmanned aircraft are relied on now more than ever to save lives and support the troops in the recent Operation Enduring Freedom and Operation Iraqi Freedom. The demands for UAS capabilities are rapidly increasing in the civilian sector. However, UAS operations will not be carried out in the NAS until safety concerns are alleviated. Among these concerns is determining the appropriate level of automation in conjunction with a suitable pilot who exhibits the necessary knowledge, skills, and abilities to safely operate these systems. This research examined two levels of automation: Management by Consent (MBC) and Management by Exception (MBE). User experiences were also analyzed in conjunction with both levels of automation while operating an unmanned aircraft simulator. The user experiences encompass three individual groups: Pilots, ATC, and Human Factors. Performance, workload, and situation awareness data were examined, but did not show any significant differences among the groups. Shortfalls and constraints are heavily examined to help pave the wave for future research

Concrete Static Stress Estimation Using Computer Vision-Based Digital Image Processing

Department of Urban and Environmental Engineering (Urban Infrastructure Engineering)As increasing interests about structural safety due to occasionally occurring collapse of structures and social infrastructures, efforts to identify and monitor the current state of structure are also increasing. Recently, most structures have been built of concrete, so identification of safety level of concrete structures becomes a critical issue. One of such techniques is to evaluate the current stress state in concrete. This technique is essential in various fields involved in an investigation of tensile stress of tendons in pre- and post-tensioned structures, building remodeling which needs to remove bearing walls and adds other foundations, and identification of load distribution in enlarged concrete structures. In other words, current stress level in concrete is an important factor to check the safety level of the structures in service. Although it is obvious that a technique for estimating the static stress level of concrete is essential, the method to identify the stress state of the currently used concrete structure is definitely limited. Several efforts for estimating the current stress state have been developed in previous research, including a stress-strain relationship based on elastic theory and a stress relaxation method (SRM) for concrete. These methods in the previous researches have made a certain contribution in this field but practical use in real structures is still inadequate. Therefore, an objective of this study is to develop a static stress estimation technique which can be applied to real concrete structures. This study proposes a method that can measure the static stress level of concrete by incorporating SRM and computer vision-based image processing. Applying a small damage to concrete specimen can release the current stress state and induce stress field change inside concrete around the damage. Computer vision-based measurement can measure the deformation due to this stress field change. This deformation measurement is used in the static stress estimation algorithm developed in this study. The proposed method is validated using several concrete specimens and consequently demonstrates the performance.clos

Benefits from remote sensing data utilization in urban planning processes and system recommendations

The benefits of utilizing remote sensor data in the urban planning process of the Metropolitan Washington Council of Governments are investigated. An evaluation of sensor requirements, a description/ comparison of costs, benefits, levels of accuracy, ease of attainment, and frequency of update possible using sensor versus traditional data acquisition techniques are discussed

Modelling optimal use of tests for monitoring disease progression and recurrence

Background: Monitoring to identify disease recurrence or progression is common, often with limited evidence to support the tests used, subsequent decisions, frequency and duration of monitoring. Aims: To develop methods for designing evidence-based monitoring strategies and estimating measurement error, a key consideration in selecting monitoring tests. Methods: To investigate studies of measurement error: frameworks were identified; design, analysis and reporting of studies were reviewed; a case study was analysed; and, simulation studies were performed to evaluate varying sample size and outlier detection methods. To develop methods for designing monitoring strategies the methods literature was reviewed and simulation models were developed and validated. Results: Biological variability studies are often poorly designed and reported. Studies are frequently small and may not produce valid results; the required precision of estimates can inform the sample size. Outlier detection can negatively bias variability estimates; methods should be used with caution, with interpretation allowing for potential bias. Modelling monitoring data requires knowledge of the natural history of disease, test performance and measurement error; such evaluation enables selection of evidence-based monitoring strategies prior to full-scale investigation. Conclusions: Poor monitoring tests can be identified early using small-scale studies and monitoring strategies should be optimised prior to full evaluation

Corporate governance

Governance is largely about the decision-making process in a complex organization Shareholders (owners) delegate authority to professionals who have the managerial skills to increase shareholders’ wealth. As a consequence the contributors of a firm's capital base are usually different from the contributors of its management base. This separation of ownership from control has led to organizations establishing a system of corporate governance controls designed to discourage managers from pursuing objectives that fail to maximize shareholder wealth. These controls constitute the firm's corporate governance framework. Corporate governance controls are designed to monitor managers behavior or align the goals of management with the goals of shareholders. In this chapter, a corporate governance framework is developed that outlines the roles and responsibilities of participants involved in governing the organization and portraying information to the capital market

The Federal Budget Surplus: Surprise or Strategy?

Canadian federal government registered 11 consecutive budgetary surpluses between 1997 and 2007. In the Canadian context, the federal surplus often has two components: the planned component and the surprise component; the latter appearing when the actual budgetary balance exceeds the planned surplus. This paper discusses whether the constantly reappearing federal budget surprise surpluses are a desirable attribute of the budgetary policy. To this end, the paper presents a brief overview of the federal surplus, the main causes leading to their reappearance, and examines negative implications associated with federal surpluses. The analysis shows that surprise surpluses may lead to eroding the credibility of the budget process, increasing pressure to spend the excessive fiscal room, pro-cyclical nature of fiscal policy and eroded vigilance of maintaining a steady level of spending. Inaccurate budget projections, but also the invisible political pressure to avoid deficits are among the main causes of the surprise surpluses.national budget, budget surplus, national debt, budget forecasting