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This paper aims to present physical and geotechnical study in terms of experimental field and laboratory investigations of the subgrade soils in severely damaged and highly degraded road section with numerous potholes between Chencha to Ezo towns of Ethiopia needs to be addressed for a robust pavement.

Eighteen soil samples were collected from 18 km road stretch at a kilometer interval by considering variation and composition of soils along the road alignment. The field density with dry density, natural moisture content, consistency limit, compaction and California Bearing Ratio (CBR) were determined.

Soils were classified predominantly as silty-clay that replicates its expansive nature, characterized as bad to medium subgrade. The average optimum moisture content and maximum dry density are 17.18% and 1.83 g/cc, whereas the average CBR and swell as 8.40% and 1.49%, respectively. The investigated results indicated that the indispensable way for a stable and durable road subgrade in the existing silty clayey soil requires a capping layer. The results were uploaded into ArcGIS platform to create interactive maps for spatial distribution, composition and strength of the subgrade properties.

Experimental investigation of subgrade soils by scientific procedures and presenting important properties through integrated approach using ArcGIS Mapping for the road pavement design and construction purpose of under developed areas like Chencha-Ezo. ArcGIS-based mapping of all required and numerical subgrade properties with a single click using ArcGIS tool is the main significance and contribution of this study. To the best of the authors’ knowledge, this paper is original, and all the references are properly cited.

The purpose of this study is to provide the location of natural disasters that are poured into maps by extracting Twitter data. The Twitter text is extracted by using named entity recognition (NER) with six classes hierarchy location in Indonesia. Moreover, the tweet then is classified into eight classes of natural disasters using the support vector machine (SVM). Overall, the system is able to classify tweet and mapping the position of the content tweet.

This research builds a model to map the geolocation of tweet data using NER. This research uses six classes of NER which is based on region Indonesia. This data is then classified into eight classes of natural disasters using the SVM.

Experiment results demonstrate that the proposed NER with six special classes based on the regional level in Indonesia is able to map the location of the disaster based on data Twitter. The results also show good performance in geocoding such as match rate, match score and match type. Moreover, with SVM, this study can also classify tweet into eight classes of types of natural disasters specifically for the Indonesian region, which originate from the tweets collected.

This study implements in Indonesia region.

(a)NER with six classes is used to create a location classification model with StanfordNER and ArcGIS tools. The use of six location classes is based on the Indonesia regional which has the large area. Hence, it has many levels in its regional location, such as province, district/city, sub-district, village, road and place names. (b) SVM is used to classify natural disasters. Classification of types of natural disasters is divided into eight: floods, earthquakes, landslides, tsunamis, hurricanes, forest fires, droughts and volcanic eruptions.

The purpose of this article is to assist facilities asset managers who are dealing with regulatory environments pertaining to earthquakes and buildings. These professionals can learn a great deal from the successes and short-comings of a case study programme from the Auckland Council Property Department (ACPD), which manages the public facilities portfolio for the largest local administrative region in New Zealand in both population and landmass.

ACPD has initiated its response to New Zealand’s earthquake mitigation mandates by identifying buildings most at risk to an earthquake in its large and varied portfolio through the use of a rapid building evaluation programme strategically targeted to vulnerable building types with consequential attributes, including service type, number of occupants, floor area and geographic location.

ACPD was able to rapidly cull down its portfolio of approximately 3,500 buildings to just over 100 “high-exposure” buildings in urgent need of evaluation, set priorities for future evaluations, estimate needed operational and capital expenditures for long-term planning and provide useful information to more general facilities management decision-making processes.

A number of major cities around the world in areas of high seismicity have enacted ordinances mandating seismic retrofitting. However, much of the existing guiding literature regarding earthquake-related portfolio evaluations and costs pertains to specific scenarios involving real or hypothetical earthquakes. This case study, in contrast, details the approach taken by a public portfolio owner responding to legal mandates and attempting to quantify and reduce its life-safety risk exposure across a large portfolio as efficiently as possible using readily available information, a rapid building evaluation programme and best-practice predictive models for consulting and construction work.

Dams are constructed for many purposes such as for power generation, irrigation, water supply and flood control. However, dams can also impose risks to the public, and the situation could be disastrous if dam failure occurred. The study area, Bertam Valley, is located downstream of hydroelectric dam known as Sultan Abu Bakar Dam, Cameron Highlands. The key objectives of the study are to determine the potential risk area at downstream and to assess the flooding impact on damage to buildings and infrastructures due to dam break event. ArcGIS application and output from two-dimensional flood modelling have been used as an integrated approach to analyse the impact due to dam break flood, by creating flood severity grid analysis. The result obtained shows that the estimated inundated area is about 0.28 km², and almost 197 buildings are potentially affected. Results from this study show that in the event of dam break, the huge volume of impounding water will pound to the downstream areas, threatening the populations, and environment along its path. The finding is useful to assist the local authorities and emergency responders in formulating an emergency procedure to save the people during an emergency.

The purpose of this paper is to show that despite the critical importance of using accurate data when identifying geographic patterns and studying hotspots, few have explored the data quality issues introduced by Geographic Information Systems (GIS) software applications. While software manufacturers provide some information about the address matching process, critical details are left out or are buried in technical, and sometimes proprietary, jargon. The purpose of this paper is to address these issues.

The paper demonstrates, with three datasets of 100 cases each, how the assumptions built into popular GIS software produce systematically missing data during the data importing process commonly referred to as address matching.

Inclusion of directional indicators and zip codes are more important than previously thought. The results highlight the critical need to provide complete descriptions of research methodology. All geographic analyses must be accompanied with: information about the hit rate (percent of cases plotted), details about the software and process used to import tabular crime data, information about the software parameters set for the importation process (geocoding preferences), reference information about the street file used; and, an examination of the missing cases to identify some of the sampling error. When forecasting crime issues or identifying hot spots, analysts must be cognizant of the differential impact this bias will have on the generalizability of the results.

The paper explores previously neglected issues in data quality introduced by GIS software applications.

Geotechnologies have a long tradition in several areas of society and research. The recent development of the ‘Internet of Everything’ (IoE) and Geographic Information Systems (GIS) technologies opened several doors to the contribution of tourism. Emergent technologies contributions to tourism and planning such as web mapping, augmented reality (AR), crowdsourcing and crowdsensing are relatively recent, and there is a lack of research around their potential for Creative Tourism enhancement. For example, combining web mapping with AR or storytelling can be an excellent contribution to operators, planners and tourists. For research purposes, new opportunities are open, particularly by integrating community-shared data. It is well known for the popularity of social networks, the exponential growth of photo sharing, but few studies have been implemented to understand their contribution to research. This chapter focuses on emerging geotechnologies concerning cultural mapping, Creative Tourism and sustainability. Since it is a new growing niche, more research is needed to develop and understand the potential of new approaches. Besides traditional techniques such as quantitative (e.g. surveys) and qualitative ones (e.g. interviews, focus groups and world café), it revises the role of geotechnologies on Creative Tourism development and growing activities. Results from case studies from Europe are analysed.

The COVID-19 pandemic has impacted every community across the globe, but the global COVID-19 data show that the United States remains the most affected country where well over 666,000 people died, and approximately 40 million citizens became ill due to the virus' spread by mid-2021 (CDC, 2021). It is also noteworthy that extreme racial disparities in rates of COVID-19 cases and deaths are high in the United States, specifically among African American population. This situation is particularly evident among African American population in Alabama's Black Belt. Subsequently, COVID-19, racial disparities, and health inequalities have become central to the national and regional conversation. This chapter examines the associations between COVID-19, social determinants of health, and the systematic health disparity in African American population in Alabama's Black Belt region using Geographic Information Systems and the concept of uneven spatial development. Understanding the relationship between COVID-19 and these disparities within a spatial context vital to developing pathways to overcome the pandemic's effects and combat the systemic discrimination in this region. The derived policy recommendation could apply to other regions experiencing social inequality and health disparity.

Archaeological predictive maps can be valuable tools for planning officers, spatial developers and archaeologists. In 2012, the Dutch Ministry of Education, Culture and Science asked the St Eustatius Center for Archaeological Research (SECAR) to create archaeological predictive maps for St Eustatius and Saba. The maps were supposed to contribute to more effective management and protection of archaeological sites. The maps were published in 2013 and 2015. The purpose of this paper is to address the question whether the subsequent use of these maps has indeed improved site management and protection.

The evaluation proceeded by identifying the users and applications of the maps through questionnaires and an internet search engine, along with follow-up interviews with heritage professionals on both islands.

The use of the predictive maps has not yet contributed to improved management and protection of archaeological sites on St Eustatius and Saba. Suggestions have been made to ameliorate this situation and to ensure the preservation of archaeological heritage for future generations.

The creation of archaeological predictive maps can be an important step towards improving management and protection of archaeological heritage, education and heritage awareness. This is important for St Eustatius and Saba, islands that are characterised by vulnerable archaeological heritage, rapid spatial development and a lack of efficient protection measures. This paper points to the importance of follow-up efforts to ensure effective site management and protection.

The purpose of this paper is to demonstrate the importance of exploiting a geographic information system (GIS)-based data management, designed and implemented for an important monumental site. In particular, data collected during the years have been used to create a storytelling experience to disseminate the tangible and intangible heritage of Chan Chan (Peru), the wider site in mud bricks of Latin America.

The paper discusses the steps that have been performed to use the data stored in a GIS, arguing over the importance of sharing the knowledge through web-based tools, and in particular by the implementation of a storytelling. In this context, the data were structured in interoperable forms in order to preserve the universal value of the archaeological site. The exploitation in an all-in-one solution of the archival research, field surveys and planning represents a step forward for let known ancient testimonies to the whole mankind.

The GIS-based inventories represent the backbone for an affordable management of heritage resources. The novelty of the proposed approach lies on the creation of an integrated, accessible and updatable data system sharable on web.

The GIS of Chan Chan is an example of documentation of a wide archaeological area (14 km²) with complex and heterogeneous data. The developed web tool makes use of these data which can be queried even by non-expert users. The pipeline of this paper can act as useful guidelines to practitioners and researchers who want to disseminate cultural information.