Qualitative Weighting of Environmental Impact in the Southern Levant between the 4th-c. BCE to 20th-c. CE through Culture-nature Duality

Geographic information system (GIS) analysis is used to help in finding solutions for the most important geographical issues. Several programming techniques and methods are used to produce optimal solutions for GIS analysis. One of these techniques is the Solver in Microsoft Excel (MS Excel) which adjusts the values in the Excel sheet cells to produce an optimal result. Hybrid genetic algorithm (HGA) which is a combination of genetic algorithm and Hill-climbing technique is an important optimization method to solve many combinatorial problems such as GIS analysis problems. The solutions provided by HGA are better than the one obtained by any linear programming tool such as the Solver in MS Excel. The Solver produces one solution, which is most of the time not an optimal solution and leads to wrong GIS analysis. In order to prove this idea, several sites are selected as wildlife habitat locations in Lebanon using GIS analysis software, then HGA and the Solver are compared to find the maximum area for a wildlife habitat with the lowest cost of managing the habitat. This comparison proved that HGA finds many optimal solutions for wild life habitat locations better than the solution produced by MS Excel Solver. In addition, the cost provided by HGA is always similar or less than the cost of Solver solution.

This paper demonstrates the spatial and temporal dimensions of land use change in Delta State Capital Territory and derives the policy implications and lessons for the planning and implementation of sustainable urbanization. It is based on the study which combined remote sensing, geographic information system and qualitative field survey. Satellite data generated by Landsat 5(TM), Landsat 7 (ETM+) and Sentinel 2B (MSI) for the years 1990, 2011 and 2020 were used. This was also analyzed using Erdas and ArcGIS 10.6.1 software. Results from this Geographic Information Systems (GIS) analysis were triangulated with data from key informant interviews and focus group discussion. The study hypothesis was tested by applying student t-test on data sets derived from the GIS analysis. Findings of the research include reduction of undeveloped land areas from 16% in 1990 to 0.09% in 2020 and increase in built –up land areas from 7% in 1990 to 29% in 2020. The observed unorganized spread of urbanization in the capital territory is linked to the absence of Master Plan and the fact that the Delta State Capital Territory Development Agency was established 24 years after the territory was designated. The paper concludes that the Delta State Capital Territory development process does not fully conform to the growth center theory of urbanization. It is imperative for urban planners and policymakers to formulate and implement Master Plans upfront for proper land zoning and sustainable land use. In addition, the growth center theory should be applied contextually for sustainable urban development.

Recent advances in spatial data development and management in the framework of geographic information system (GIS) have created a new era in the field of land resource management. Spatial database generally refers to any set of data describing the semantic and spatial properties of real-world phenomena. Manual digitization of paper maps, existing digital datasets, satellite remote-sensing imageries, global positioning system (GPS), field surveys, internet, etc. are the promising data input sources for spatial data development in GIS. Geographic information, attribute information, and display information are the three important types of information embedded in digital maps. Relational database management system (RDBMS) is the most effective and efficient data storage and management model in spatial database generation and management in GIS. Geographic analysis in GIS facilitates the study of various processes by developing and applying suitable models. The objective of geographic analysis is to transform data into useful information to satisfy the requirements or objectives of decision-makers. GIS provides tools and methods for the integration of different data into a format to be compared and analyzed. Analysis models comprise simple user-defined views to complex stochastic models, like suitability analysis, network analysis, optimization, allocation, etc. Geometric modeling has immense potential in generating buffers, calculating areas and perimeters, and calculating distances between features. Spatial analysis in GIS helps to identify trends on the data, create new relationships from the data, and view complex relationships between datasets to make better decisions. Vector and raster overlay operations are two different types of overlays in GIS depending upon data structures. GIS provides different ways in which the information can be presented once it is analyzed and processed by GIS.

This paper presents an overview and analysis of Geographical Information Systems (GIS) in Hong Kong, through last 15 years of development in the territory. GIS in Hong Kong will be summarized in the following aspects: fundamental GIS data for Hong Kong, GIS applications in Hong Kong governmental departments, GIS applications in private sectors, GIS research and education in Hong Kong, Hong Kong GIS Association, issues for the future GIS development in Hong Kong. GIS was first adopted by Hong Kong governmental departments such as, the Lands Department and others. Today, some 15 different local governmental departments have applied GIS to support their daily works. The fundamental GIS data have been captured and managed by Lands Department. In private sectors, GIS was firstly introduced in the area of automated mapping and facility management (AM/FM) by local utility companies, and this has been further extended to telecommunication, real estate, intelligent transport system and others. Since several universities in Hong Kong play the major role for GIS research development and education, this group of people are even very active in the international communities related to GIS. Hong Kong GIS Association plays a key role in promoting GIS in Hong Kong. Although GIS development and applications in Hong Kong are getting mature, there are still a number of issues that affects its further development of GIS, e.g., developing an urban-levelled spatial data infrastructure for Hong Kong, towards a professional GIS institute for GIS industry in Hong Kong, the recognition of GIS profession in the local community and others.

A modified concept of hydrological response units (HRUs) for regional modelling of river basins using the PRMS/MMS model is presented. The HRUs are delineated by geographical information system (GIS) analysis from physiographic basin properties such as topography, soils, geology, rainfall and land use using a thorough hydrological systems analysis. The HRUs, once classified by GIS analysis, preserve the three‐dimensional heterogeneity of the drainage basin. The River Bröl basin (A = 216 km2), Rheinisches Schiefergebirge, Germany was selected to apply the concept. In total, 23 HRUs were delineated and tested with the PRMS/MMS model using a 20‐year hydrometeorological daily database. The hydrological systems analysis revealed that interflow is the dominant flow process through the basin's slopes and the major contribution to groundwater recharge and river runoff. This was accounted for by parameterizing the HRUs in the model control file to drain their surplus water not used for satisfying the demand of evapotranspiration to a common conceptual subsurface storage. This storage was simulated by interflow drainage to the groundwater aquifer in the valley floor, which in turn drained to the channel network. The PRMS/MMS model simulated the observed daily discharge very well and the fit was described by a daily correlation coefficient of r = 0.91. The NASIM and HSPF models using different means to represent the basin's physiographic heterogeneity were applied to the Bröl basin as well, but did not achieve this correlation. The HRU concept was found to be a reliable method for regional hydrological basin modelling and allows spatial up‐ and downscaling. Future research on this concept will focus on incorporating the variable precipitation distribution into the classification of HRUs and on the hydrodynamic routing of the modelled discharge. Additionally, satellite imagery must be used for classifying land use in macroscale drainage basins.

To support the ambitious bioeconomy vision outlined in Ireland’s Bioeconomy Action Plan, there is an urgent need to bring together the necessary stakeholders required to implement this vision. Farmers and other primary producers who oversee the production of sustainable biomass constitute one of the most important categories of stakeholders in the bio-based value chain. To ensure scalable, long-lasting bioeconomy collaboration, it is essential that farmers are involved in developing this bioeconomy vision. The current study provides a mixed-methods approach to co-design a green biorefinery vision with Irish farmers and other key value-chain actors. The selected value chain targeting a medium-scale grass silage biorefinery focused on the production of eco-insulation materials, with protein and biogas co-products for local markets. This was then assessed economically using an economic model, which provided a payback period of five years. To identify suitable sites for deployment of the green biorefinery in rural areas, geographical information systems (GIS) analysis was undertaken, considering various environmental, socio-economic and infrastructural variables, which identified 26 potential sites for deployment of the green biorefinery model in Ireland. This study found that early engagement with and inclusion of the farmers in a co-designed process of innovation and alternative revenue streams for them is essential. While a preferred cooperative-based business model for a grass silage biorefinery was identified in consultation with the multiple stakeholders, further research on its long-term commercial sustainability is proposed as future research.

Geographic information systems (GIS) analysis has not been widely used in underdeveloped countries to ensure that vulnerable populations have accessibility to primary health-care services. This study applied GIS methods to analyse the spatial accessibility to urban primary-care centres of the population in Kermanshah city, Islamic Republic of Iran, by age and sex groups. In a descriptive-analytical study over 3 time periods, network analysis, mean centre and standard distance methods were applied using ArcGIS 9.3. The analysis was based on a standard radius of 750 m distance from health centres, walking speed of 1 m/s and desired access time to health centres of 12.5 mins. The proportion of the population with inadequate geographical access to health centres rose from 47.3% in 1997 to 58.4% in 2012. The mean centre and standard distance mapping showed that the spatial distribution of health centres in Kermanshah needed to be adjusted to changes in population distribution.

A prototype for pipeline routing using remotely sensed data and geographic information system analysis

Solid waste is one of the important causes of the environmental crisis that negatively impacts human health throughout the world and is fast approaching a disaster level that will pose a direct threat to human life. As with all other environmental problems, the increase in solid waste production that goes hand in hand with growing population and rising consumption has become a focus of great concern. Along with these rising levels, the investment, management and maintenance of solid waste collection and transport vehicles is seeing a continual increase in financial outlay. It is clear from the budgets of local authority solid waste management systems, 65 to 80% of which are accounted for by domestic waste, that the collection and transport of solid waste is a high-cost process and that this expenditure can be significantly reduced by the reorganisation of solid waste collection routing schedules and the minimization of collection frequency. This study demonstrates a linear programming model in order to develop an optimal routing schedule for solid waste collection and transportation, thereby reducing costs to a minimum. The neighbourhood of Veysel Karani in the Haliliye District of Şanlıurfa Province, Turkey, was specifically selected for this case study, having the suitable socio-economic and demographic variables to be representative of a metropolitan urban area. Firstly, the data regarding the municipal solid waste collection and transport routes were obtained from the local authority. Analysis and verification of these data were then performed. With the field study, these data were verified on-site, and the missing data were completed. Linear programming and geographic information system (GIS) analysis were used to determine the best route. Consequently, it is concluded that it is possible to save the route by 28% with GIS analysis and 33% with linear programming analysis according to the existing municipal solid waste collection and transportation routes.

The study uses primary data, descriptive statistics, Geographic Information Systems (GIS) and correlation analysis to analyze the contributions of farming activities to climate change in Mississippi between 1992 through 2002. This involved the assessment of methane emissions from rice cultivation in the state of Mississippi as well as the relationship between the levels of methane gas concentration and other variables associated with rice production. In highlighting the extent to which rice production activities fuel climate change, the results of the study not only showed greenhouse gas emission related rice production activities to be on the rise, but there is a relationship between methane emissions and rice farming. The GIS analysis also points to a visible concentration of rice production activities associated with methane emissions in the major counties of Bolivia, Sunflower and Washington along the Northwest portion of the state. While this raises the threats of climate change predictors in the area. To remedy the problems, the paper suggests five future lines of actions from the need for education to the promotion of emission trading.

BackgroundPresenting a comprehensive picture of geographic data comprising multiple factors is an inherently integrative undertaking. Visualizing such data in an interactive form is essential for public sharing and geographic information systems (GIS) analysis. The Toxicological Prioritization Index (ToxPi) framework offers a visual analytic integrating data that is compatible with geographic data. ArcGIS is a predominant geospatial software available for presenting and communicating geographic data, yet to our knowledge there is no methodology for integrating ToxPi profiles into ArcGIS maps.ObjectiveWe introduce an actively developed suite of software, the ToxPi*GIS Toolkit, for creating, viewing, sharing, and analyzing interactive ToxPi profiles in ArcGIS to allow for new GIS analysis and an avenue for providing geospatial results to the public.MethodsThe ToxPi*GIS Toolkit is a collection of methods for creating interactive feature layers that contain ToxPi profiles. It currently includes an ArcGIS Toolbox (ToxPiToolbox.tbx) for drawing location-specific ToxPi profiles in a single feature layer, a collection of modular Python scripts that create predesigned layer files containing ToxPi feature layers from the command line, and a collection of Python routines for useful data manipulation and preprocessing. We present workflows documenting ToxPi feature layer creation, sharing, and embedding for both novice and advanced users looking for additional customizability.ResultsMap visualizations created with the ToxPi*GIS Toolkit can be made freely available on public URLs, allowing users without ArcGIS Pro access or expertise to view and interact with them. Novice users with ArcGIS Pro access can create de novo custom maps, and advanced users can exploit additional customization options. The ArcGIS Toolbox provides a simple means for generating ToxPi feature layers. We illustrate its usage with current COVID-19 data to compare drivers of pandemic vulnerability in counties across the United States.SignificanceThe integration of ToxPi profiles with ArcGIS provides new avenues for geospatial analysis, visualization, and public sharing of multi-factor data. This allows for comparison of data across a region, which can support decisions that help address issues such as disease prevention, environmental health, natural disaster prevention, chemical risk, and many others. Development of new features, which will advance the interests of the scientific community in many fields, is ongoing for the ToxPi*GIS Toolkit, which can be accessed from www.toxpi.org.

ABSTRACTAs early as the fourth century BCE, the Nabateans established the Incense Road to facilitate the transport of aromatic substances (frankincense and myrrh) from the Arabian Peninsula to the Mediterranean basin. An important part of this road was the segment between Petra and Gaza. Although studied before, the accurate route of parts of this segment is still vague since evidence of Roman milestones are scarce and significant portions of the landscape have changed dramatically in modern times, essentially wiping out the tracks of ancient roads. In this study, we use Geographic Information Systems (GIS) and Least Cost Path (LCP) analyses for reconstructing the original path of the Incense Road as well as verifying the factors influencing its establishment. The implemented analyses support the archeological evidence of two travel phases between Petra and Oboda (Avdat): During the first phase the Nabateans used the Darb es-Sultan route; during the second phase, from the first century BCE onwards, they passed through the Ramon Crater. This is the first time such reconstruction is made in the southern Levant. It was found that slope degree and the distance to water resources are dominant factors in reconstructing the accurate path of the Incense Road.

Sedimentation and Boundary Changes of Virginia Salt Marshes

This paper takes a first look at the trade effects of China’s Belt and Road Initiative (BRI), also referred to as the New Silk Road, on the 65 countries potentially involved. The pillar of the initiative consists of a number of infrastructure investment projects to improve the land and maritime transportation in the BRI region. We first use geo-referenced data and geographical information systems (GIS) analysis to compute the bilateral time to trade before and after the Belt and Road Initiative. Then, we estimate the effect of improvement in bilateral timeliness to trade on bilateral export values and on trade patterns using a gravity model and a comparative advantage model similar to Nunn (2007). We use physical geography features of transit countries as instruments of bilateral trade time to address the endogeneity between trade and infrastructure. We find that (i) the BRI would have sizeable effects on trade flows among participating countries; (ii) these effects would be magnified if deeper trade agreements complement the upgrading in transport infrastructure; (iii) products that use time sensitive inputs, and countries that are highly exposed to the new infrastructure and that are integrated in the global production chains have larger trade gains. Keywords: Belt and Road Initiative, Transport Infrastructure, GIS Analysis, Trade Flows, Time Sensitivity, Input-output Linkages

Acute stroke is a serious, time-sensitive condition requiring immediate medical attention. Emergency medical services (EMS) routing and direct transport of acute stroke patients to stroke centers improves timely access to care. This study aimed to describe EMS stroke routing and transports by rurality in North Carolina (NC). We conducted a retrospective study using existing data on EMS transports of suspected stroke patients in NC in 2019. The primary study outcome was EMS bypass of the nearest hospital for transport to a nonnearest hospital, determined by geographic information systems (GIS) analysis. Incident addresses were geocoded to census tracts and classified as urban, suburban, or rural by Rural-Urban Commuting Area codes. We compared the frequency of bypass and estimated additional transport times by urban, suburban, and rural incident locations. Of 3666 patients, 1884 (51%) EMS transports bypassed the nearest hospital. Bypass occurred less often for rural EMS incidents (39%) compared to those in urban (57%) and suburban (63%) tracts. The estimated additional transport time for rural bypasses of nonendovascular-capable stroke centers for endovascular-capable stroke centers was a median of 25min (interquartile range 13-33). Using GIS analysis, we found nearly half of EMS transports of suspected stroke patients in NC bypassed the nearest hospital, including noncertified hospitals and stroke centers. Bypasses occurred less often in rural areas, though incurred significantly longer transport times, compared to urban areas. These findings are important for regional stroke system planning, especially for improving rural access to acute stroke care.