A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

Analysis of Housing Partnerships using the Balanced Scorecard framework

Housing Partnerships (HPs) are collaborative arrangements that assist communities in the delivery of affordable housing by combining the strengths of the public and private sectors. They emerged in several states, counties, and cities in the eighties as innovative solutions to the challenges in affordable housing resulting from changing dynamics of delivery and production. ^ My study examines HPs with particular emphasis upon the identification of those factors associated with the successful performance of their mission of affordable housing. I will use the Balanced Scorecard (BSC) framework in this study. The identification of performance factors facilitates a better understanding of how HPs can be successful in achieving their mission. The identification of performance factors is significant in the context of the current economic environment because HPs can be viewed as innovative institutional mechanisms in the provision of affordable housing. ^ The present study uses a mixed methods research approach, drawing on data from the IRS Form 990 tax returns, a survey of the chief executives of HPs, and other secondary sources. The data analysis is framed according to the four perspectives of BSC: the financial, customer, internal business, and learning and growth. Financially, revenue diversification affects the financial health of HPs and overall performance. Although HPs depend on private and government funding, they also depend on service fees to carry out their mission. From a customer perspective, the HPs mainly serve low and moderate income households, although some serve specific groups such as seniors, homeless, veterans, and victims of domestic violence. From an internal business perspective, HPs’ programs are oriented toward affordable housing needs, undertaking not only traditional activities such as construction, loan provision, etc., but also advocacy and educational programs. From an employee and learning growth perspective, the HPs are small in staff size, but undertake a range of activities with the help of volunteers. Every part of the HP is developed to maximize resources, knowledge, and skills in order to assist communities in the delivery of affordable housing and related needs. Overall, housing partnerships have played a key role in affordable housing despite the housing market downturn since 2006. Their expenses on affordable housing activities increased despite the decrease in their revenues.^

Water Governance in Haiti: An Assessment of Laws and Institutional Capacities

The Republic of Haiti struggles to sustainably manage its water resources. Public health is compromised by low levels of water supply, sanitation, and hygiene, and water resources are often contaminated and unsustainably allocated. While poor governance is often blamed for these shortcomings, the laws and institutions regulating water resources in Haiti are poorly understood, especially by the international community. This study brings together and analyzes Haitian water laws, assesses institutional capacities, and provides a case study of water management in northern Haiti in order to provide a more complete picture of the sector. Funded by the Inter-American Development Bank as part of the Water Availability, Quality and Integrated Water Resources Management in Northern Haiti (HA-T1179) Project, this study took place from January-July 2015, with the help of local experts and participating stakeholders. The results indicate that Haiti’s water law framework is highly fragmented, with overlapping mandates and little coordination between ministries at the national level, and ambiguous but unrealistic roles for subnational governments. A capacity assessment of institutions in northern Haiti illustrates that while local stakeholders are engaged, human and financial resources are insufficient to carry out statutory responsibilities. The findings suggest that water resources management planning should engage local governments and community fixtures while supplementing capacities with national or international support.