Remote sensing-based proxies for urban disaster risk management and resilience: A review

© 2018 by the authors. Rapid increase in population and growing concentration of capital in urban areas has escalated both the severity and longer-term impact of natural disasters. As a result, Disaster Risk Management (DRM) and reduction have been gaining increasing importance for urban areas. Remote sensing plays a key role in providing information for urban DRM analysis due to its agile data acquisition, synoptic perspective, growing range of data types, and instrument sophistication, as well as low cost. As a consequence numerous methods have been developed to extract information for various phases of DRM analysis. However, given the diverse information needs, only few of the parameters of interest are extracted directly, while the majority have to be elicited indirectly using proxies. This paper provides a comprehensive review of the proxies developed for two risk elements typically associated with pre-disaster situations (vulnerability and resilience), and two post-disaster elements (damage and recovery), while focusing on urban DRM. The proxies were reviewed in the context of four main environments and their corresponding sub-categories: built-up (buildings, transport, and others), economic (macro, regional and urban economics, and logistics), social (services and infrastructures, and socio-economic status), and natural. All environments and the corresponding proxies are discussed and analyzed in terms of their reliability and sufficiency in comprehensively addressing the selected DRM assessments. We highlight strength and identify gaps and limitations in current proxies, including inconsistencies in terminology for indirect measurements. We present a systematic overview for each group of the reviewed proxies that could simplify cross-fertilization across different DRM domains and may assist the further development of methods. While systemizing examples from the wider remote sensing domain and insights from social and economic sciences, we suggest a direction for developing new proxies, also potentially suitable for capturing functional recovery

A Review of Remote Sensing-Based Proxies and Data Processing Methods for Urban Disaster Risk Management

Disaster risk management (DRM) and reduction has been gaining in importance as a result of increasing impacts of natural disasters. Reliable and informative data are the foundation of any comprehensive and effective DRM. Synoptic and multi-type remote sensing has become an essential tool for rapid acquiring of geospatial data, particularly for complex and dynamic urban areas. Accordingly, it has been used for the assessment of all components of the disaster risk cycle, ranging from disaster preparedness to rapid damage assessment. However, due to the complex and multifaceted characteristics of many urban elements, in particular social and economic activities and functions, accurate risk assessment that takes account of the varied and complex set of vulnerabilities and their associated dynamics continues to be very difficult, and direct remote sensing observations are frequently insufficient. Therefore, methods have been developed to indirectly estimate the risk, utilizing image-based proxies. In recent years, using proxies has become a predominant way for such measurements in the DRM field for both pre- and post-disaster phases, at times with similar proxies being used for both situations. For example, the presence of vegetation in urban areas is used as a proxy for both pre-event social vulnerability and for post-disaster recovery assessments. In addition, existing proxies do not sufficiently address all assessment requirements, e.g. there is no proxy for building-based functional damage assessment. Another persistent challenge is the extraction those proxies as a basis for automating the urban DRM process. Although several remote sensing data processing methods have been developed to derive information for DRM in recent years, extracting proxies from remote sensing data requires more accurate results in detecting objects and features. In this study we carried out a comprehensive review of remote sensing-based proxies for different urban DRM phases, identified duplications on efforts, inconsistencies in terminology, but also remaining gaps. With a specific focus on post-disaster recovery assessment, which particularly relies on measures to assess the progress in functions and processes, the review was then used as a basis for the development of new proxies and indicators. The focus is on developing robust proxies to go beyond the physical evaluation perspective, and to extract socio- economic information and functional assessment of urban areas using new strategies, such as multiple-proxies approach, and fusing object- and pattern-based proxies from various remote sensing data, including very-high resolution satellite and aerial images, drone data, LiDAR data. In addition, the reliability of current remote sensing data processing methods in extracting proxies will be discussed, and accordingly how remote sensing data processing methods can contribute to developing reliable proxies will be demonstrated (e.g. using new pattern recognition, texture, and object detection methods)

Microdrone-Based Indoor Mapping with Graph SLAM

Unmanned aerial vehicles offer a safe and fast approach to the production of three-dimensional spatial data on the surrounding space. In this article, we present a low-cost SLAM-based drone for creating exploration maps of building interiors. The focus is on emergency response mapping in inaccessible or potentially dangerous places. For this purpose, we used a quadcopter microdrone equipped with six laser rangefinders (1D scanners) and an optical sensor for mapping and positioning. The employed SLAM is designed to map indoor spaces with planar structures through graph optimization. It performs loop-closure detection and correction to recognize previously visited places, and to correct the accumulated drift over time. The proposed methodology was validated for several indoor environments. We investigated the performance of our drone against a multilayer LiDAR-carrying macrodrone, a vision-aided navigation helmet, and ground truth obtained with a terrestrial laser scanner. The experimental results indicate that our SLAM system is capable of creating quality exploration maps of small indoor spaces, and handling the loop-closure problem. The accumulated drift without loop closure was on average 1.1% (0.35 m) over a 31-m-long acquisition trajectory. Moreover, the comparison results demonstrated that our flying microdrone provided a comparable performance to the multilayer LiDAR-based macrodrone, given the low deviation between the point clouds built by both drones. Approximately 85 % of the cloud-to-cloud distances were less than 10 cm

In memoriam of Alexander Golovin (1939–2013)

No abstract available

Micro and macro quadcopter drones for indoor mapping to support disaster management

In this paper we present the operations and mapping techniques of two drones that are different in terms of size, the sensors deployed, and the positioning and mapping techniques used. The first drone is a low-cost commercial quadcopter microdrone, a Crazyflie, while the second drone is a relatively expensive research quadcopter macrodrone, called MAX. We investigated their feasibility in mapping areas where satellite positioning is not available, such as indoor spaces

Effect of Gravity and Confinement on Phase Equilibria: A Density Matrix Renormalization Approach

The phase diagram of the 2D Ising model confined between two infinite walls and subject to opposing surface fields and to a bulk "gravitational" field is calculated by means of density matrix renormalization methods. In absence of gravity two phase coexistence is restricted to temperatures below the wetting temperature. We find that gravity restores the two phase coexistence up to the bulk critical temperature, in agreement with previous mean-field predictions. We calculate the exponents governing the finite size scaling in the temperature and in the gravitational field directions. The former is the exponent which describes the shift of the critical temperature in capillary condensation. The latter agrees, for large surface fields, with a scaling assumption of Van Leeuwen and Sengers. Magnetization profiles in the two phase and in the single phase region are calculated. The profiles in the single phase region, where an interface is present, agree well with magnetization profiles calculated from a simple solid-on-solid interface hamiltonian.Comment: 4 pages, RevTeX and 4 PostScript figures included. Final version as published. To appear in Phys. Rev. Let

VGI quality control

This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i.e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future