The function of remote sensing in support of environmental policy

Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently little academic interest in the societal contribution of environmental remote sensing. This is because none of the more than 300 peer reviewed papers described actual policy support. This paper describes and discusses the potential, actual support, and limitations of earth observation with respect to supporting the various stages of environmental policy development. Examples are given of the use of remote sensing in problem identification and policy formulation, policy implementation, and policy control and evaluation. While initially, remote sensing contributed primarily to the identification of environmental problems and policy implementation, more recently, interest expanded to applications in policy control and evaluation. The paper concludes that the potential of earth observation to control and evaluate, and thus assess the efficiency and effectiveness of policy, offers the possibility of strengthening governance

Toward an integrated disaster management approach: How artificial intelligence can boost disaster management

Technical and methodological enhancement of hazards and disaster research is identified as a critical question in disaster management. Artificial intelligence (AI) applications, such as tracking and mapping, geospatial analysis, remote sensing techniques, robotics, drone technology, machine learning, telecom and network services, accident and hot spot analysis, smart city urban planning, transportation planning, and environmental impact analysis, are the technological components of societal change, having significant implications for research on the societal response to hazards and disasters. Social science researchers have used various technologies and methods to examine hazards and disasters through disciplinary, multidisciplinary, and interdisciplinary lenses. They have employed both quantitative and qualitative data collection and data analysis strategies. This study provides an overview of the current applications of AI in disaster management during its four phases and how AI is vital to all disaster management phases, leading to a faster, more concise, equipped response. Integrating a geographic information system (GIS) and remote sensing (RS) into disaster management enables higher planning, analysis, situational awareness, and recovery operations. GIS and RS are commonly recognized as key support tools for disaster management. Visualization capabilities, satellite images, and artificial intelligence analysis can assist governments in making quick decisions after natural disasters

Flood hazard mapping of a rapidly urbanizing city in the foothills (Birendranagar, Surkhet) of Nepal

Flooding in the rapidly urbanizing city of Birendranagar, Nepal has been intensifying, culminating in massive loss of life and property during July and August 2014. No previous studies have monitored underlying land-cover dynamics and flood hazards for the area. This study described spatiotemporal urbanization dynamics and associated land-use/land-cover (LULC) changes of the city using Landsat imagery classifications for five periods between 1989 and 2016 (1989-1996, 1996-2001, 2001-2011, 2011-2016). Areas with high flood-hazard risk were also identified on the basis of field surveys, literature, and the Landsat analysis. The major LULC changes observed were the rapid expansion of urban cover and the gradual decline of cultivated lands. The urban area expanded nearly by 700%, from 85 ha in 1989 to 656 ha in 2016, with an average annual growth rate of 23.99%. Cultivated land declined simultaneously by 12%, from 7005 ha to 6205 ha. The loss of forest cover also contributed significantly to increased flood hazard. Steep topography, excessive land utilization, fragile physiographic structure, and intense monsoonal precipitation aggravate hazards locally. As in Nepal generally, the sustainable development of the Birendranagar area has been jeopardized by a disregard for integrated flood-hazard mapping, accounting for historical land-cover changes. This study provides essential input information for improved urban-area planning in this regard

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Residential building damage from hurricane storm surge: proposed methodologies to describe, assess and model building damage

Although hydrodynamic models are used extensively to quantify the physical hazard of hurricane storm surge, the connection between the physical hazard and its effects on the built environment has not been well addressed. The focus of this dissertation research is the improvement of our understanding of the interaction of hurricane storm surge with the built environment. This is accomplished through proposed methodologies to describe, assess and model residential building damage from hurricane storm surge. Current methods to describe damage from hurricane events rely on the initiating mechanism. To describe hurricane damage to residential buildings, a combined wind and flood damage scale is developed that categorizes hurricane damage on a loss-consistent basis, regardless of the primary damage mechanism. The proposed Wind and Flood (WF) Damage Scale incorporates existing damage and loss assessment methodologies for wind and flood events and describes damage using a seven-category discrete scale. Assessment of hurricane damage has traditionally been conducted through field reconnaissance deployments where damage information is captured and cataloged. The increasing availability of high resolution satellite and aerial imagery in the last few years has led to damage assessments that rely on remotely sensed information. Existing remote sensing damage assessment methodologies are reviewed for high velocity flood events at the regional, neighborhood and per-building levels. The suitability of using remote sensing in assessing residential building damage from hurricane storm surge at the neighborhood and per-building levels is investigated using visual analysis of damage indicators. Existing models for flood damage in the United States generally quantify the economic loss that results from flooding as a function of depth, rather than assessing a level of physical damage. To serve as a first work in this area, a framework for the development of an analytical damage model for residential structures is presented. Input conditions are provided by existing hydrodynamic storm surge models and building performance is determined through a comparison of physical hazard and building resistance parameters in a geospatial computational environment. The proposed damage model consists of a two-tier framework, where overall structural response and the performance of specific components are evaluated

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

Role of Remote Sensing in Disaster Management

The objective of this report is to review the existing satellites monitoring Earth’s resources and natural disasters. Each satellite has different repeat pass frequency and spatial resolution (unless it belongs to the same series of satellites for the purpose of continuation of data flow with same specifications). Similarly, different satellites have different types of sensors on-board, such as, panchromatic, multispectral, infrared and thermal. All these sensors have applications in disaster mitigation, though depending on the electromagnetic characteristics of the objects on Earth and the nature of disaster itself. With a review of the satellites in orbit and their sensors the present work provides an insight to suitability of satellites and sensors to different natural disasters. For example, thermal sensors capture fire hazards, infrared sensors are more suitable for floods and microwave sensors can record soil moisture. Several kinds of disasters, such as, earthquake, volcano, tsunami, forest fire, hurricane and floods are considered for the purpose of disaster mitigation studies in this report. However, flood phenomenon has been emphasized upon in this study with more detailed account of remote sensing and GIS (Geographic Information Systems) applicability. Examples of flood forecasting and flood mapping presented in this report illustrate the capability of remote sensing and GIS technology in delineating flood risk areas and assessing the damages after the flood recedes. With the help of a case study of the Upper Thames River watershed the use of remote sensing and GIS has been illustrated for better understanding. The case study enables the professionals and planning authorities to realize the impact of urbanization on river flows. As the urban sprawl increases with the increase of population, the rainfall and snow melt reaches the river channels at a faster rate with higher intensity. In other words it can be inferred that through careful land use planning flood disasters can be mitigated.https://ir.lib.uwo.ca/wrrr/1002/thumbnail.jp