Towards a rapid automatic detection of building damage using remote sensing for disaster management

2014 ◽  
Vol 23 (1) ◽  
pp. 53-66 ◽  
Author(s):  
Thi-Thanh-Hiên Pham ◽  
Philippe Apparicio ◽  
Christopher Gomez ◽  
Christiane Weber ◽  
Dominique Mathon
Keyword(s):  
Disaster Management ◽  
Spatial Resolution ◽  
Rapid Assessment ◽  
Building Damage ◽  
Visual Interpretation ◽  
Content Type ◽  
Emergency Situations ◽  
Optical Images ◽  
Damage Maps ◽  
Damage Mapping

Purpose – Satellite and airborne images are increasingly used at different stages of disaster management, especially in the detection of infrastructure damage. Although semi- or full automatic techniques to detect damage have been proposed, they have not been used in emergency situations. Damage maps produced by international organisations are still based on visual interpretation of images, which is time- and labour-consuming. The purpose of this paper is to investigate how an automatic mapping of damage can be helpful for a first and rapid assessment of building damage. Design/methodology/approach – The study area is located in Port-au-Prince (Haiti) stricken by an earthquake in January 2010. To detect building damage, the paper uses optical images (15 cm of spatial resolution) coupled with height data (LiDAR, 1 m of spatial resolution). By undertaking an automatic object-oriented classification, the paper identifies three categories of building damages: intact buildings, collapsed buildings and debris. Findings – Data processing for the study area covering 11 km2 took about 15 hours. The accuracy of the classification varies from 70 to 79 per cent depending to the methods of assessment. Causes of errors are numerous: limited spectral information of the optical images, resolution difference between the two data, high density of buildings but most importantly, certain types of building collapses could not be detected by vertically taken images (the case of data in this study). Originality/value – The automatic damage mapping developed in this paper proves to be reliable and could be used in emergency situations. It could also be combined with manual visual interpretation to accelerate the planning of humanitarian rescues and reconstruction.

Towards Rapid Citywide Damage Mapping Using Neighborhood Edge Dissimilarities in Very High-Resolution Optical Satellite Imagery—Application to the 2003 Bam, Iran, Earthquake

2005 ◽  
Vol 21 (1_suppl) ◽  
pp. 255-266 ◽  
Author(s):  
Charles K. Huyck ◽  
Beverley J. Adams ◽  
Sungbin Cho ◽  
Hung-Chi Chung ◽  
Ronald T. Eguchi
Keyword(s):  
Assessment Tool ◽  
The United States ◽  
Building Damage ◽  
Urban Environments ◽  
Detection Algorithms ◽  
Sensing Technology ◽  
Change Detection Algorithms ◽  
Damage Mapping ◽  
Relief Efforts ◽  
Very High

Remote sensing technology is increasingly recognized as a valuable post-earthquake damage assessment tool. Recent studies performed by research teams in the United States, Japan, and Europe have demonstrated that building damage sustained in urban environments can be identified through analysis of optical imagery and synthetic aperture radar (SAR) data. Damage detection using automated change detection algorithms will soon facilitate the scaling and prioritization of relief efforts, as well as the monitoring of the recovery operations. This paper introduces the use of an edge dissimilarity algorithm to quantify the extent of building damage.

Exploring critical success factors (CSFs) of humanitarian supply chain management (HSCM) in flood disaster management (FDM)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Isaac Sakyi Damoah
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Disaster Management ◽  
Success Factors ◽  
Flood Disaster ◽  
Chain Management ◽  
Content Type ◽  
Humanitarian Operations ◽  
Critical Success ◽  
Humanitarian Supply Chain

PurposeThis study explores the critical success factors (CSFs) in humanitarian supply chain management (HSCM) by focussing on flood disaster management (FDM) in Ghana.Design/methodology/approachAn in-depth semi-structured interview and questionnaire surveys in a sequential data collection approach were used to collect data from definitive stakeholders of humanitarian organisations. The data was analysed using exploratory factor analysis (EFA), confirmatory factors analysis (CFA) and structural equation modelling (SEM) techniques.FindingsSeventy-four factors were identified as success factors of HSCM of flood disaster management. However, 41 of these factors were statistically significant and considered as critical. In descending order, these factors relate to management practices, education and training, stakeholder involvement and cooperation, infrastructure, innovation and technology, materials and resources, administrative practices, socio-cultural and economic. Whilst some factors are internal to the humanitarian organisations, others are external factors that are beyond the control of humanitarian organisations.Research limitations/implicationsEven though this study offers empirical results that could guide policymakers in their decision-making about humanitarian operations, care needs to be taken since the data is within one country and within a specific disaster context – hence, policymakers need to consider the local contextual dynamics. Future studies could look at different disasters context to make a comparative analysis of various types of disaster operations.Practical implicationsInstitutions such as World Health Organization, Red Cross organisations and UN seeking to curbs global-warming-related disasters and the reduction of the effects of flood disaster can use findings as a guide during the formulation of HSCM policies and strategies.Originality/valueUnlike previous studies of humanitarian operations that focussed extensively on theoretical expositions, simulations, conceptual frameworks and models, this present study offers empirical evidence of humanitarian operations in the context of SCM. Further, by highlighting on the HSCM CSFs, this study contributes to disaster reduction and their effects on humanity in the context of FDM. This research could be used as guide by governments and FDM organisations to make informed decisions on SCM areas to focus the most during FDM.

Evaluating the effectiveness of drones in emergency situations: a hybrid multi-criteria approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Justin Zuopeng Zhang ◽  
Praveen Ranjan Srivastava ◽  
Prajwal Eachempati
Keyword(s):  
Fuzzy Ahp ◽  
Use Cases ◽  
Fuzzy Decision Making ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Emergency Situations ◽  
High Rise ◽  
Criteria Weights ◽  
Infrastructure Inspection ◽  
Logistic Support

PurposeThe paper aims to build a customized hybrid multi-criteria model to identify the top three utilities of drones at both personal and community levels for two use cases: firefighting in high-rise buildings and logistic support.Design/methodology/approachA hybrid multi-criterion model that integrates fuzzy analytical hierarchy process (AHP), Best Worst, fuzzy analytical network process (ANP), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is used to compute the criteria weights. The weights are validated by a novel ensemble ranking technique further whetted by experts at the community and personal levels to two use cases.FindingsDrones' fire handling and disaster recovery utilities are the most important to fight fire in high-rise buildings at both personal and community levels. Similarly, drones' urban planning, municipal works and infrastructure inspection utilities are the most important for providing logistics support at personal and community levels.Originality/valueThe paper presents a novel multi-criteria approach, i.e. ensemble ranking, by combining the criteria ranking of individual methods – fuzzy AHP, Best-Worst, fuzzy ANP and fuzzy DEMATEL – in the ratio of optimal weights to each technique to generate the consolidated ranking. Domain experts also validate this ranking for robustness. This paper demonstrates a viable methodology to quantify the utilities of drones and their capabilities. The proposed model can be recalibrated for different use case scenarios of drones.

The impact of corporate bankruptcy on strategic management: using a textual analysis approach to analyze executives’ opinions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Raphael Nagel ◽  
Carmen Aviles
Keyword(s):  
Strategic Management ◽  
Global Economy ◽  
Textual Analysis ◽  
New Technologies ◽  
Organizational Structures ◽  
Analysis Approach ◽  
Management Decision ◽  
Content Type ◽  
Emergency Situations ◽  
The Impact

Purpose In the past decade, the development of the global economy, the change in organizational structures and the maturing of new technologies have led to considerable changes in business structures. Emergency situations, such as the recent COVID-19 pandemic, have led many companies to declare bankruptcy. In this context, the present study aims to analyze strategic opinions of company executives in a declaration of bankruptcy. Design/methodology/approach To this end, an innovative approach is applied to strategic management and business. First, the authors conducted 14 interviews with executives, and the interview data were transcribed. Second, using textual analysis and data mining techniques, the transcripts were analyzed to understand the importance of indicators identified as relevant in companies in a declaration of bankruptcy. Findings This resulted in identification of 10 relevant indicators perceived by executives to avoid or anticipate a state of bankruptcy, including innovation, business adaptability, room for improvement in production processes, time to react to situations of alarm, layoffs, support from public institutions, suppliers, international and national regulations, impact on the industry, credits and debts. Originality/value The paper concludes with a discussion of important theoretical and practical implications of these findings for the industry. Also, strategic management decision-making strategies are presented as a result of the innovative textual analysis approach used.

scholarly journals “It can’t happen to me”

2017 ◽  
Vol 34 (5) ◽  
pp. 385-399 ◽  
Author(s):  
Vendula Belackova ◽  
Barbara Janikova ◽  
Jaroslav Vacek ◽  
Hana Fidesova ◽  
Michal Miovsky
Keyword(s):  
Rapid Assessment ◽  
Alcoholic Beverages ◽  
Vulnerable Groups ◽  
Lower Probability ◽  
Drinking Patterns ◽  
Structured Interviews ◽  
Emergency Situations ◽  
Response Method ◽  
Alcohol Users ◽  
The Impact

Background: In September 2012, a series of methanol poisonings occurred in the Czech Republic as a result of an influx of illicit alcohol into (predominantly) cheap alcoholic beverages on the retail market. The public authorities decided to prevent public health risks by prohibiting sales of liquors that contained more than 20% alcohol (> 20% liquor). The “partial” prohibition lasted for almost two weeks, but the poisonings still continued. This article assesses the impact of the methanol poisoning risks and the (partial) prohibition on alcohol drinking patterns, and describes the understanding of risks and their mitigation in vulnerable groups. Methods: The rapid assessment and response method (RAR) was used during the (partial) alcohol prohibition. Semi-structured interviews were conducted with respondents recruited for the study in alcohol-intake settings (e.g., bars and restaurants, street alcohol outlets) in six regions. In total, 107 alcohol users were interviewed, mostly with risky drinking patterns (69% scored ≥ 1 on the CAGE scale), and 53 alcohol retailers/staff members serving alcohol. Results: About one third of the alcohol users in the study (35%) drank > 20% liquors during the prohibition; a higher score on the CAGE scale was associated with a lower probability of drinking > 20% liquors during the period of the prohibition, probably because of the perception of being at high risk of poisoning. There was some increase in drinking liquors with an alcohol content less than 20%. Those who continued drinking > 20% liquors typically did so in the belief that some sources of these were safe. Conclusions: Public policies aimed at reducing the risk of methanol poisonings in emergency situations should adopt broader measures than those focusing on market control. These measures include increased access to brief interventions, addressing the strategies that alcohol consumers adopt to prevent risk, and, in general, helping consumers make informed choices to prevent further fatalities.

scholarly journals ACCURACY ASSESSMENTS OF PAN-SHARPENED IMAGE FOR BENTHIC HABITATS MAPPING

2017 ◽  
Vol 4 (1) ◽  
pp. 27 ◽  
Author(s):  
Pramaditya Wicaksono ◽  
Faza Adhimah
Keyword(s):  
Spatial Resolution ◽  
Classification Scheme ◽  
Spectral Response ◽  
Hierarchical Classification ◽  
Visual Interpretation ◽  
Benthic Habitats ◽  
Visual Appearance ◽  
Accuracy Assessments

Image-sharpening process integrates lower spatial resolution multispectral bands with higher spatial resolution panchromatic band to produce multispectral bands with finer spatial detail called pan-sharpened image. Although the pan-sharpened image can greatly assist the process of information extraction using visual interpretation, the benefit and setback of using pan-sharpened image on the accuracy of digital classification for mapping remain unclear. This research aimed at 1) highlighting the issue of using pan-sharpened image to perform benthic habitats mapping and 2) comparing the accuracy of benthic habitats mapping using original and pan-sharpened bands. In this study, Quickbird image was used and Kemujan Island was selected as the study area. Two levels of hierarchical classification scheme of benthic habitats were constructed based on the composition of in situ benthic habitats. PC Spectral sharpening method was applied on Quickbird image. Image radiometric corrections, PCA transformation, and image classifications were performed on both original and pan-sharpened image. The results showed that the accuracy of benthic habitats classification of pan-sharpened image (maximum overall accuracy 64.28% and 73.30% for per-pixel and OBIA, respectively) was lower than the original image (73.46% and 73.10%, respectively). The main setback of using pan-sharpened image is the inability to correct the sunglint, hence adversely affects the process of water column correction, PCA transformation and image classification. This is mainly because sunglint do not only affect object’s spectral response but also the texture of the object. Nevertheless, the pan-sharpened image can still be used to map benthic habitats using visual interpretation and digital image processing. Pan-sharpened image will deliver better classification accuracy and visual appearance especially when the sunglint is low.

scholarly journals A Comparison of Methods for Determining Forest Composition from High-Spatial-Resolution Remotely Sensed Imagery

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1290
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remotely Sensed ◽  
Local Scale ◽  
Google Earth ◽  
Forest Composition ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Remotely Sensed Imagery ◽  
Composition Classes

Remotely sensed imagery has been used to support forest ecology and management for decades. In modern times, the propagation of high-spatial-resolution image analysis techniques and automated workflows have further strengthened this synergy, leading to the inquiry into more complex, local-scale, ecosystem characteristics. To appropriately inform decisions in forestry ecology and management, the most reliable and efficient methods should be adopted. For this reason, our research compares visual interpretation to digital (automated) processing for forest plot composition and individual tree identification. During this investigation, we qualitatively and quantitatively evaluated the process of classifying species groups within complex, mixed-species forests in New England. This analysis included a comparison of three high-resolution remotely sensed imagery sources: Google Earth, National Agriculture Imagery Program (NAIP) imagery, and unmanned aerial system (UAS) imagery. We discovered that, although the level of detail afforded by the UAS imagery spatial resolution (3.02 cm average pixel size) improved the visual interpretation results (7.87–9.59%), the highest thematic accuracy was still only 54.44% for the generalized composition groups. Our qualitative analysis of the uncertainty for visually interpreting different composition classes revealed the persistence of mislabeled hardwood compositions (including an early successional class) and an inability to consistently differentiate between ‘pure’ and ‘mixed’ stands. The results of digitally classifying the same forest compositions produced a higher level of accuracy for both detecting individual trees (93.9%) and labeling them (59.62–70.48%) using machine learning algorithms including classification and regression trees, random forest, and support vector machines. These results indicate that digital, automated, classification produced an increase in overall accuracy of 16.04% over visual interpretation for generalized forest composition classes. Other studies, which incorporate multitemporal, multispectral, or data fusion approaches provide evidence for further widening this gap. Further refinement of the methods for individual tree detection, delineation, and classification should be developed for structurally and compositionally complex forests to supplement the critical deficiency in local-scale forest information around the world.

Design and development of an aircraft type portable drone for surveillance and disaster management

2018 ◽  
Vol 6 (3) ◽  
pp. 147-159 ◽  
Author(s):  
Kazi Mahmud Hasan ◽  
S.H. Shah Newaz ◽  
Md. Shamim Ahsan
Keyword(s):  
Performance Analysis ◽  
Real Time ◽  
Disaster Management ◽  
Ground Control ◽  
Content Type ◽  
Recovery System ◽  
Ground Control Station ◽  
Autonomous Aircraft ◽  
Aircraft Type ◽  
The Cost

Purpose The purpose of this paper is to demonstrate the development of an aircraft-type autonomous portable drone suitable for surveillance and disaster management. The drone is capable of flying at a maximum speed of 76 km/h. This portable drone comprises five distinct parts those are easily installable within several minutes and can be fit in a small portable kit. The drone consists of a ballistic recovery system, allowing the drone landing vertically. The integrated high-definition camera sends real-time video stream of desired area to the ground control station. In addition, the drone is capable of carrying ~1.8 kg of payload. Design/methodology/approach In order to design and develop the portable drone, the authors sub-divided the research activities in six fundamental steps: survey of the current drone technologies, design the system architecture of the drone, simulation and modeling of various modules of the drone, development of various modules of the drone and their performance analysis, integration of various modules of the drone, and real-life performance analysis and finalization. Findings Experimental results: the cruise speed of the drone was in the range between 45 and 62 km/h. The drone was capable of landing vertically using the ballistic recovery system attached with it. On the contrary, the drone can transmit real-time video to the ground control station and, thus, suitable for surveillance. The audio system of the drone can be used for announcement of emergency messages. The drone can carry 1.8 kg of payload and can be used during disaster management. The drone parts are installed within 10 min and fit in a small carrying box. Practical implications The autonomous aircraft-type portable drone has a wide range of applications including surveillance, traffic jam monitoring and disaster management. Social implications The cost of the cost-effective drone is within $700 and creates opportunities for the deployment in the least developed countries. Originality/value The autonomous aircraft-type portable drone along with the ballistic recovery system were designed and developed by the authors using their won technology.

Ecosystem-based disaster risk reduction concept for forest and land fire disaster

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Philein Hafidz Al Kautsar ◽  
Nur Budi Mulyono
Keyword(s):  
Law Enforcement ◽  
Disaster Management ◽  
Real Life ◽  
Structured Interview ◽  
Technical Problems ◽  
Content Type ◽  
Economic Problems ◽  
Technology And Innovation ◽  
Management Of Technology ◽  
Management Context

PurposeThe purpose of this study is to develop an ecosystem-based DRR concept and explore how far the concept can be applied in a disaster-management context.Design/methodology/approachThe authors used the ecosystem concept established by Tsujimoto et al. (2018) as the foundation of this study. They then conducted a literature search to adapt the ecosystem concept to fit the context of disaster management. Thus, they developed an ecosystem-based DRR concept. They used a case study method to test whether the adapted ecosystem concept can be applied to examine a real-life case of disaster management. For data collection, they used qualitative methods; a semi-structured interview with practitioners and other actors involved in disaster-management practice as well as document review. For data analysis, they used thematic analysis to find themes within the data.FindingsBy using this concept, the authors found some actors fulfil their role in the ecosystem toward the DRR effort, some actors are ill-equipped, and some actors are actively working against DRR effort. There are also implementation challenges, as numerous programs are only halfway done due to a lack of resources. However, the main problems of this disaster can be summarized into three categories: technical problems, socio-economic problems and law-enforcement problems. All three problems need to be addressed altogether because even neglecting only one problem would lead to a flawed solution.Research limitations/implicationsOne of the limitations is the respondents' bias. This research aims to find out their part, or more accurately what they are representative of, regarding disaster management for forest and land fire case. As some of the questions may reveal unflattering action or may even hurting their credibility, respondents might not have provided an entirely honest answer. Another limitation is the differing respondents' roles within the disaster. As each of the respondents is a representative of an actor in disaster management, they all have different traits. Thus, this situation makes it challenging to produce similar quality and quantity data for each of them.Practical implicationsAs concluded, the ecosystem-based DRR concept can be used as a framework to examine a real-life case of disaster management. It can be utilized to explain roles, relationships and the whole network of disaster-management actors. The authors hope that this concept could help decision-makers in designing their policies.Social implicationsThe main problems of this disaster can be summarized into three categories: technical problems, socio-economic problems and law-enforcement problems. All three problems need to be addressed altogether for even neglecting only one problem would lead to a flawed solution. However, the yearly reoccurrences of fires and the widespread of illegal and dangerous practice, slash and burn agriculture, are evidence that the government mishandles the other two problems. There is a need for reform within legal institutions and government's treatment regarding local farmers. There is a need for trust, cooperation and synergy between disaster-management actors.Originality/valueThe ecosystem concept has been used widely in the field of management of technology and innovation. However, while ecosystem concept is commonly used in the management of technology and innovation, it is rarely used in a disaster-management context.

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