Automatically Detecting Changes and Anomalies in Unmanned Aerial Vehicle Images

The use of unmanned aerial vehicles (UAVs) in civil aviation is growing up quickly, enabling new scenarios, especially in environmental monitoring and public surveillance services. So far, Earth observation has been carried out only through satellite images, which are limited in resolution and suffer from important barriers such as cloud occlusion. Microdrone solutions, providing video streaming capabilities, are already available on the marketplace, but they are limited to altitudes of a few hundred feet. In contrast, UAVs equipped with high quality cameras can fly at altitudes of a few thousand feet and can fill the gap between satellite observations and ground sensors. Therefore, new needs for data processing arise, spanning from computer vision algorithms to sensor and mission management. This paper presents a solution for automatically detecting changes in images acquired at different times by patrolling UAVs flying over the same targets (but not necessarily along the same path or at the same altitude). Change detection in multi-temporal images is a prerequisite for land cover inspection, which, in turn, sets up the basis for detecting potentially dangerous or threatening situations

Monitoring War Destruction from Space: A Machine Learning Approach

Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep learning techniques combined with data augmentation to expand training samples. We apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. The approach allows generating destruction data with unprecedented scope, resolution, and frequency - only limited by the available satellite imagery - which can alleviate data limitations decisively

車載画像を用いた都市の4次元モデリング

Tohoku University岡谷貴之課

Geometric, Semantic, and System-Level Scene Understanding for Improved Construction and Operation of the Built Environment

Recent advances in robotics and enabling fields such as computer vision, deep learning, and low-latency data passing offer significant potential for developing efficient and low-cost solutions for improved construction and operation of the built environment. Examples of such potential solutions include the introduction of automation in environment monitoring, infrastructure inspections, asset management, and building performance analyses. In an effort to advance the fundamental computational building blocks for such applications, this dissertation explored three categories of scene understanding capabilities: 1) Localization and mapping for geometric scene understanding that enables a mobile agent (e.g., robot) to locate itself in an environment, map the geometry of the environment, and navigate through it; 2) Object recognition for semantic scene understanding that allows for automatic asset information extraction for asset tracking and resource management; 3) Distributed coupling analysis for system-level scene understanding that allows for discovery of interdependencies between different built-environment processes for system-level performance analyses and response-planning. First, this dissertation advanced Simultaneous Localization and Mapping (SLAM) techniques for convenient and low-cost locating capabilities compared with previous work. To provide a versatile Real-Time Location System (RTLS), an occupancy grid mapping enhanced visual SLAM (vSLAM) was developed to support path planning and continuous navigation that cannot be implemented directly on vSLAM’s original feature map. The system’s localization accuracy was experimentally evaluated with a set of visual landmarks. The achieved marker position measurement accuracy ranges from 0.039m to 0.186m, proving the method’s feasibility and applicability in providing real-time localization for a wide range of applications. In addition, a Self-Adaptive Feature Transform (SAFT) was proposed to improve such an RTLS’s robustness in challenging environments. As an example implementation, the SAFT descriptor was implemented with a learning-based descriptor and integrated into a vSLAM for experimentation. The evaluation results on two public datasets proved the feasibility and effectiveness of SAFT in improving the matching performance of learning-based descriptors for locating applications. Second, this dissertation explored vision-based 1D barcode marker extraction for automated object recognition and asset tracking that is more convenient and efficient than the traditional methods of using barcode or asset scanners. As an example application in inventory management, a 1D barcode extraction framework was designed to extract 1D barcodes from video scan of a built environment. The performance of the framework was evaluated with video scan data collected from an active logistics warehouse near Detroit Metropolitan Airport (DTW), demonstrating its applicability in automating inventory tracking and management applications. Finally, this dissertation explored distributed coupling analysis for understanding interdependencies between processes affecting the built environment and its occupants, allowing for accurate performance and response analyses compared with previous research. In this research, a Lightweight Communications and Marshalling (LCM)-based distributed coupling analysis framework and a message wrapper were designed. This proposed framework and message wrapper were tested with analysis models from wind engineering and structural engineering, where they demonstrated the abilities to link analysis models from different domains and reveal key interdependencies between the involved built-environment processes.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155042/1/lichaox_1.pd

Automated Building Information Extraction and Evaluation from High-resolution Remotely Sensed Data

The two-dimensional (2D) footprints and three-dimensional (3D) structures of buildings are of great importance to city planning, natural disaster management, and virtual environmental simulation. As traditional manual methodologies for collecting 2D and 3D building information are often both time consuming and costly, automated methods are required for efficient large area mapping. It is challenging to extract building information from remotely sensed data, considering the complex nature of urban environments and their associated intricate building structures. Most 2D evaluation methods are focused on classification accuracy, while other dimensions of extraction accuracy are ignored. To assess 2D building extraction methods, a multi-criteria evaluation system has been designed. The proposed system consists of matched rate, shape similarity, and positional accuracy. Experimentation with four methods demonstrates that the proposed multi-criteria system is more comprehensive and effective, in comparison with traditional accuracy assessment metrics. Building height is critical for building 3D structure extraction. As data sources for height estimation, digital surface models (DSMs) that are derived from stereo images using existing software typically provide low accuracy results in terms of rooftop elevations. Therefore, a new image matching method is proposed by adding building footprint maps as constraints. Validation demonstrates that the proposed matching method can estimate building rooftop elevation with one third of the error encountered when using current commercial software. With an ideal input DSM, building height can be estimated by the elevation contrast inside and outside a building footprint. However, occlusions and shadows cause indistinct building edges in the DSMs generated from stereo images. Therefore, a “building-ground elevation difference model” (EDM) has been designed, which describes the trend of the elevation difference between a building and its neighbours, in order to find elevation values at bare ground. Experiments using this novel approach report that estimated building height with 1.5m residual, which out-performs conventional filtering methods. Finally, 3D buildings are digitally reconstructed and evaluated. Current 3D evaluation methods did not present the difference between 2D and 3D evaluation methods well; traditionally, wall accuracy is ignored. To address these problems, this thesis designs an evaluation system with three components: volume, surface, and point. As such, the resultant multi-criteria system provides an improved evaluation method for building reconstruction

Adaptor of last resort? An economic perspective on the government’s role in adaptation to climate change

Abstract Individuals and societies have always adapted to change, whether catastrophic or slow onset. Over the last two centuries, however, governments have significantly extended their role as ultimate social manager of risk.  It is as yet unclear whether, how, or to what extent governments will add adaptation to climate change to their portfolio of responsibilities.  This report investigates this question on the basis of review and analysis of economic and policy thinking on the issues, and by using a new dataset on the 2011 Brisbane flood. Uncertainties about the future impacts of climate change obviate definitive conclusions about future adaptation actions and insights for specific situations cannot be generalised.  Economic precepts suggest that governments should limit intervention to cases of genuine market failure, such as the provision of information on likely impacts of climate change including at the local level, or to support for people affected by uninsurable events.  But any role as ‘insurer of last resort’ needs to be circumscribed by rigorous social cost-benefit analysis to ensure that government intervention is beneficial, in the context of the need to adapt to climatic changes.  Although the phenomenon of ‘government failure’ is generally ignored in the adaptation literature (and often by policy makers), it too can stymie efficient adaptation.  A standard justification for government intervention is market failure, including misperception of risk by individuals and businesses.  We use Brisbane property prices before and after the January 2011 flood, as well as property-level flood risk information to test the hypothesis that buyers do not accurately perceive the risk of riverine flooding.  The results indicate that buyers do take risk into account, and even discriminate between zones of differing flood risk.  The concepts of ‘government as insurer of last resort’ and ‘government as insurer of first resort’ as alternative forms of intervention in markets are examined with a view to disambiguation.  In contrast to much current thinking in academic and government circles, we conclude that the government should not act as an ‘adaptor of first or last resort’.  Rather, government can best contribute to efficient adaptation by reducing the economic costs and institutional barriers to adaptation faced by individuals and organisations.Comprehensive micro-economic reform, and the promotion of institutional flexibility are potential ‘no regrets’ strategies because they will also promote economic growth and welfare.Please cite as: Dobes, L, Jotzo, F, Doupé, P 2013 Adaptor of last resort? An economic perspective on the Government’s role in adaptation to climate change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 81.Individuals and societies have always adapted to change, whether catastrophic or slow onset. Over the last two centuries, however, governments have significantly extended their role as ultimate social manager of risk.  It is as yet unclear whether, how, or to what extent governments will add adaptation to climate change to their portfolio of responsibilities.  This report investigates this question on the basis of review and analysis of economic and policy thinking on the issues, and by using a new dataset on the 2011 Brisbane flood. Uncertainties about the future impacts of climate change obviate definitive conclusions about future adaptation actions and insights for specific situations cannot be generalised.  Economic precepts suggest that governments should limit intervention to cases of genuine market failure, such as the provision of information on likely impacts of climate change including at the local level, or to support for people affected by uninsurable events.  But any role as ‘insurer of last resort’ needs to be circumscribed by rigorous social cost-benefit analysis to ensure that government intervention is beneficial, in the context of the need to adapt to climatic changes.  Although the phenomenon of ‘government failure’ is generally ignored in the adaptation literature (and often by policy makers), it too can stymie efficient adaptation.  A standard justification for government intervention is market failure, including misperception of risk by individuals and businesses.  We use Brisbane property prices before and after the January 2011 flood, as well as property-level flood risk information to test the hypothesis that buyers do not accurately perceive the risk of riverine flooding.  The results indicate that buyers do take risk into account, and even discriminate between zones of differing flood risk.  The concepts of ‘government as insurer of last resort’ and ‘government as insurer of first resort’ as alternative forms of intervention in markets are examined with a view to disambiguation.  In contrast to much current thinking in academic and government circles, we conclude that the government should not act as an ‘adaptor of first or last resort’. Rather, government can best contribute to efficient adaptation by reducing the economic costs and institutional barriers to adaptation faced by individuals and organisations.Comprehensive micro-economic reform, and the promotion of institutional flexibility are potential ‘no regrets’ strategies because they will also promote economic growth and welfare.Please cite as: Dobes, L, Jotzo, F, Doupé, P 2013 Adaptor of last resort? An economic perspective on the Government’s role in adaptation to climate change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 81.&nbsp

Stakeholder attributes and approaches in natural disaster risk management in the built environment: the case of flood risk management in transport infrastructure

The increasing number of natural disasters has demonstrated the importance of natural disaster risk management. There is little consensus regarding the role of stakeholder attributes in reducing flood damage and explaining stakeholder approaches. Local Councils are important stakeholders in flood risk management in transport infrastructure. Hence, the characteristics of floods, Local Councils’ stakeholder attributes, and the exposure and vulnerability of the socio-economic and transport infrastructure were contextualised to examine flood damage and Local Councils’ proactive and reactive approaches. This study examines three dominant Local Councils’ stakeholder attributes of power, legitimacy and urgency by focusing on flood damage and Local Councils’ proactive and reactive approaches. Data was collected from historical archive databases and a structured questionnaire survey involving Local Councils in New South Wales, Australia that covered the time period from 1992 to 2012. This data was analysed using multi-attribute decision-making and structural equation modelling with partial least square estimation approaches. The results show that the exposure and vulnerability of Australian states and territories to flood damage depend on both socio-economic and built environment conditions. The greater the flood characteristics such as frequency, severity and type, the greater the flood damage. The exposure and vulnerability of socio-economic and transport infrastructure of a Local Council have mediating effects on the direct relationship between their stakeholder attributes and flood damage. Proactive and reactive approaches by Local Councils are highly affected by stakeholder attributes. The developed stakeholder disaster response index shows that Local Councils have practised more reactive approaches than proactive approaches. Policy makers might use the stakeholder disaster response index through continuous assessment of proactive and reactive approaches to achieve a high level of flood risk management

Stakeholder attributes and approaches in natural disaster risk management in the built environment: the case of flood risk management in transport infrastructure

The increasing number of natural disasters has demonstrated the importance of natural disaster risk management. There is little consensus regarding the role of stakeholder attributes in reducing flood damage and explaining stakeholder approaches. Local Councils are important stakeholders in flood risk management in transport infrastructure. Hence, the characteristics of floods, Local Councils’ stakeholder attributes, and the exposure and vulnerability of the socio-economic and transport infrastructure were contextualised to examine flood damage and Local Councils’ proactive and reactive approaches. This study examines three dominant Local Councils’ stakeholder attributes of power, legitimacy and urgency by focusing on flood damage and Local Councils’ proactive and reactive approaches. Data was collected from historical archive databases and a structured questionnaire survey involving Local Councils in New South Wales, Australia that covered the time period from 1992 to 2012. This data was analysed using multi-attribute decision-making and structural equation modelling with partial least square estimation approaches. The results show that the exposure and vulnerability of Australian states and territories to flood damage depend on both socio-economic and built environment conditions. The greater the flood characteristics such as frequency, severity and type, the greater the flood damage. The exposure and vulnerability of socio-economic and transport infrastructure of a Local Council have mediating effects on the direct relationship between their stakeholder attributes and flood damage. Proactive and reactive approaches by Local Councils are highly affected by stakeholder attributes. The developed stakeholder disaster response index shows that Local Councils have practised more reactive approaches than proactive approaches. Policy makers might use the stakeholder disaster response index through continuous assessment of proactive and reactive approaches to achieve a high level of flood risk management