Safe Site Selection Research Articles

Data-driven offshore CO2 saline storage assessment methodology

The world produces approximately 50 billion tonnes of greenhouse gases annually. This is measured in CO2-equivalents, and geologic CO2 storage has the potential to advance decarbonization and mitigate greenhouse gas emissions. New technologies to assess offshore carbon storage are needed to address resource, regulatory, and commercial needs. Although most efforts to assess storage resources focus on onshore criteria, offshore reservoirs offer significant storage potential and distinct development challenges. Potential advantages of offshore carbon storage include being further from human population centers and less potential to interact with groundwater. The U.S. Department of Energy's method for evaluating storage capacity in non-oil-bearing saline reservoirs has been enhanced to support assessments for offshore environments in the Offshore CO2 Saline Storage methodology (OCSS). This methodology applies data-driven capabilities to estimate saline storage capacity while accounting for features specific to offshore reservoirs. Features include changes in CO2 density and sedimentary differences that impact estimates of permanence and capacity. The Offshore CO2 Saline Storage Calculator mechanizes OCSS to estimate storage capacity. This paper presents the methodology and estimates for 18 geologic domains in the Gulf of Mexico. Potential storage distributions, sensitivity analyses, and the incorporation of spatial data and tools to support safe site selection are also discussed.

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

The site selection process for a building entails evaluating a variety of factors with varying degrees of importance or percentage influence. In order to ensure that critical site selection factors are not overlooked, a methodology for calculating a building’s safe site selection must be developed. The study identified three broad aspects widely considered in site selection, namely environmental, physical, and socioeconomic criteria. To assess the safest site selection of residential building construction for sustainable urban growth, we used GIS-based multi-criteria decision-making approach that combined Fuzzy-AHP and weighted linear combination (WLC) aggregation method used to calculate the SSPZ. The final safe site suitability map was generated by aggregating all aspects such as geophysical, socio-economic and Geo-environmental thematic layers and their associated Fuzzy-AHP weights using the weighted linear combination method. The sites potential index’s mean value of 0.513 with standard deviation of 0.340, minimum and maximum GeoPhySSSI are 0.0 and 0.91, respectively, SSS index is classified into zones by histogram profile using natural breaks (jenks)” Subsequently, safe sites identified and divided into six classes namely no construction, very low suitable site low suitable site, moderate suitable site, high suitable site, and very high suitable site.“ According to the statistical analysis, 3.64% and 32.12% of the total area were under very high and high SSSZ, while 26.40% and 6.22% accounted to the moderate and low suitable potential, respectively” Our findings suggest that integrating the fuzzy collection with AHP is highly desirable in terms of alternative and decision-making effectiveness. The study reveals that the areas of high and moderate suitability are located near existing habitant area, major roads, and educational and health services; they are not located in restricted/protected areas or are vulnerable to natural hazards. The findings indicate that unsuitable and less-suitable land uses such as vegetation, protected areas, and agriculture lands cover nearly one-third area of Abha-Khamis Mushyet regions, implying that using Fuzzy-AHP and GIS techniques will significantly aid in the conservation of the environment. This would significantly mitigate adverse effects on the ecosystem and climate.

Site selection criteria for temporary sheltering in urban environment

PurposeThe inevitable occurrence of natural disasters and crisis arising from them causes a lot of losses globally, particularly in disaster-prone countries such as Iran. One of the main issues considered by organizations involved in crisis management is the selection of suitable sites for temporary sheltering for disaster victims. This study aims to choose safe places to establish temporary sheltering in urban environment.Design/methodology/approachInitially, relevant factors are identified by reviewing literature and through consultation with disaster experts. Next, the important layers were collected and analytical hierarchy process was used to assess the criteria weights based on their effectiveness on selection of safe sites for temporary sheltering. Finally, for integrating layers of factors, overlay and fuzzy models were used in Geographic Information System (GIS) environment, and subsequently, a proper map was prepared and suitable areas were identified.Findings7 main criteria and 19 sub-criteria were selected to provide safe places for temporary sheltering. The results of fuzzy model in this study provide more accurate and limited safe areas for temporary sheltering when compared to index overlay model.Originality/valueThe results of this study will help decision-makers and local and regional managers to reduce the vulnerability of at-risk communities in urban environments. Moreover, choosing appropriate places for temporary shelters would help build community disaster resilience according to these criteria.

A GIS-based methodology for safe site selection of a building in a hilly region

Worker safety during construction is widely accepted, but the selection of safe sites for a building is generally not considered. Safe site selection (SSS) largely depends upon compiling, analyzing, and refining the information of an area where a building is likely to be located. The locational and topographical aspects of an area located in hilly regions play a major role in SSS, but are generally neglected in traditional and CAD-based systems used for site selection. Architects and engineers select a site based on their judgment, knowledge, and experience, but issues related to site safety are generally ignored. This study reviewed the existing literature on site selection techniques, building codes, and approaches of existing standards to identify various aspects crucial for SSS in hilly regions. A questionnaire survey was conducted to identify various aspects that construction professionals consider critical for SSS. This study explored the application of geographic information systems (GIS) in modeling the locational and topographical aspects to identify areas of suitability. A GIS-based methodology for locating a safe site that satisfies various spatial safety aspects was developed.

Data fusion strategies for hazard detection and safe site selection for planetary and small body landings

This paper discusses the design and evaluation of data fusion strategies to perform tiered fusion of several heterogeneous sensors and a priori data. The aim is to increase robustness and performance of hazard detection and avoidance systems, while enabling safe planetary and small body landings anytime, anywhere. The focus is on Mars and asteroid landing mission scenarios and three distinct data fusion algorithms are introduced and compared. The first algorithm consists of a hybrid camera–LIDAR hazard detection and avoidance system, the H2DAS, in which data fusion is performed at both sensor-level data (reconstruction of the point cloud obtained with a scanning LIDAR using the navigation motion states and correcting the image for motion compensation using IMU data), feature-level data (concatenation of multiple digital elevation maps, obtained from consecutive LIDAR images, to achieve higher accuracy and resolution maps while enabling relative positioning) as well as decision-level data (fusing hazard maps from multiple sensors onto a single image space, with a single grid orientation and spacing). The second method presented is a hybrid reasoning fusion, the HRF, in which innovative algorithms replace the decision-level functions of the previous method, by combining three different reasoning engines—a fuzzy reasoning engine, a probabilistic reasoning engine and an evidential reasoning engine—to produce safety maps. Finally, the third method presented is called Intelligent Planetary Site Selection, the IPSIS, an innovative multi-criteria, dynamic decision-level data fusion algorithm that takes into account historical information for the selection of landing sites and a piloting function with a non-exhaustive landing site search capability, i.e., capable of finding local optima by searching a reduced set of global maps. All the discussed data fusion strategies and algorithms have been integrated, verified and validated in a closed-loop simulation environment. Monte Carlo simulation campaigns were performed for the algorithms performance assessment and benchmarking. The simulations results comprise the landing phases of Mars and Phobos landing mission scenarios.

Landslide hazard assessment of the 2008 Wenchuan earthquake: a case study in Beichuan area

The Wenchuan earthquake (magnitude Ms = 8.0) of 12 May 2008 triggered widespread and large-scale landslides over an area of about 50 000 km2. A study was undertaken to determine the primary factors associated with seismic landslide occurrence. An index-based approach used to assess earthquake-triggered landslide hazard in the central part of the Wenchuan earthquake area affected is described. Slope gradient, relief amplitude, lithology, bedding–slope relations, fault proximity, stream proximity, and antecedent rainfall are recognized as factors that may have had an important influence on landslide occurrence. The assessment of the influence of each of these factors is presented through use of a series of maps showing areas of low, moderate, high, and very high landslide hazard. Areas identified as having “very high and high landslide hazard” were located along the earthquake-source fault and along both banks of the Jian River. The role of rainfall is very significant for future landslide occurrence in the earthquake area. The results of this study will assist decision makers in the selection of safe sites during the reconstruction process. The maps can also be used for landslide risk management in the study area.

Design and performance assessment of hazard avoidance techniques for vision-based landing

Hazard avoidance (HA) is a key technology for a safe landing of future planetary landing missions. During HA, sensors and computers onboard the lander are used to detect hazards in the landing zone, autonomously select the most suitable region for landing, and generate the trajectory that retargets the lander to the safer landing site (LS). In this paper, algorithms are described for vision-based hazard detection, safe site selection, and powered landing guidance designed for landing in planets without atmosphere. The algorithms are validated in a realistic simulated scenario representing a landing on Mercury. Results show that the developed HA algorithms are effective at detecting hazards and guiding the lander to a safe LS.

Lidar-Based Hazard Avoidance for Safe Landing on Mars

Hazard avoidance is a key technology for landing large payloads safely on the surface of Mars. During hazard avoidance, sensors and computing onboard the lander are utilized to detect hazards in the landing zone, autonomously select a location free of hazards, and then generate a trajectory that retargets the lander to the safe landing site. Algorithms are described for scanning lidar (light detection and ranging)-based hazard detection, safe site selection, and powered landing guidance designed for Mars landing. The performance of these algorithms is quantified using a closed-loop simulation of hazard avoidance, which includes a synthetic Martian terrain generator, a scanning lidar model, and the required hazard avoidance and powered landing guidance algorithms. Preliminary results show that the proposed hazard avoidance algorithms are effective at detecting hazards and guiding the lander to a safe landing site.