This study analyzes the characteristics of land use/land cover change in Jordan's Irbid governorate, 1984-2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful planning. Satellite images of Landsat 5-thematic mapper and Landsat 8 operational land imager for the years 1984, 1994, 2004, 2015 and 2018 were used to explore the characteristics of land use/land cover for this study. The results indicate that the built-up area expanded by 386.9% during the study period and predict further expansion by 19.5% and 64.6% from 2015 to 2030 and 2050 respectively. The areas around the central and eastern parts of the governorate are predicted to have significant expansion of the built-up area by these dates, which should be taken into consideration in future plans. Land use/land cover change and urban expansion in Irbid are primarily caused by the high rate of population growth rate as a direct result of receiving large numbers of immigrants from Syria and Palestine in addition to the natural increase of population and other socio-economic changes. (C) 2020 GJESM. All rights reserved.

Jordan has received more than 1.2 million Syrian refugees, including 656,213 registered with United Nations High Commissioner for Refugees (UNHCR) since the beginning of Syrian crisis in 2011. Jordanians are acutely feeling significant impacts of the refugees on their daily lives and refugees' pressure on services, natural resources and the labor market, especially in host communities where the impact is the highest. This study aims to analyze economic, social and environmental impacts of Syrian refugees in Jordan from Jordanians' point of view. It also aims to identify the suggestions of Jordanians to alleviate the impacts of Syrians and adapt with the refugees issue in Jordan. This study relies primarily on the available data of Syrian refugees taken from the relevant corporations in Jordan such as Department of Statistics, Ministry of Planning and International Cooperation (MOPIC), and UNHCR. In addition, a questionnaire was designed and distributed online to a representative sample of Jordanians (1080 respondents) to achieve the study’s objectives. The results revealed that pressure on labor market, services, and infrastructure as well as increasing housing rents were the main economic impacts of Syrian refugees especially in the neighboring governorates of Syria in Jordan. The social impacts were represented by increasing crime rates and drugs. Refugees also have impacts and pressure on clean water, energy and environment. However, the respondents reported some positive impacts of refugees including providing market with highly-skilled and low-waged labors that makes the Jordanian market more competitive. The study concluded with some suggested recommendations that may alleviate the negative impacts of refugees on Jordan and adapt with the crisis.

The aim of this study was to examine the extent to which Katara Cultural Village enhances the image of Qatar, based on reviewers’ posts on TripAdvisor. It also sought to analyze the current situation of Katara from the managers’ perspective. A total of 2,342 comments about Katara on the TripAdvisor website were analyzed using content analysis. Three focus group meetings with eight divisional managers in Katara were also conducted and analyzed using thematic analysis. The results show a high level of overall satisfaction among TripAdvisor reviewers from different nationalities and backgrounds. A word frequency count presents Katara positively as a good destination for cultural experience, with amazing and attractive features. According to the comments, Katara contributes to enhancing the image of Qatar and Qatari culture worldwide. The Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis based on the focus group meetings with managers provided a clear and in-depth understanding of Katara’s current strengths, weaknesses, opportunities, and threats. This analysis can be important to planners and policy makers in Katara in developing and adopting suitable policies and strategies.

This study aims to evaluate tourists' reviews of gastronomy tourism expressed in Google reviews according to the CAC model (Cognitive, Affective, and Conative), and to examine the inter-correlations between CAC model components. The study was applied to traditional restaurants in Amman downtown. The research then extracts the main themes from the textual reviews as well as a sentiment score of an affective image of traditional Amman downtown restaurants. The results of machine learning experiments suggest that the proposed approach can identify traditional restaurant reviews in Amman downtown into CAC model components. The results also show that the Random Forest algorithm performed best in the cognitive and cognitive dimensions, whereas the Neural Network algorithm performed best in the affective dimension. ML classifier revealed that most of the reviews were classified as cognitive (such as the type of food, and services) while the remaining reviews were classified as affective (such as pleasure and arousal) and conative (such as intention to recommend, and positive word of mouth) respectively. The highest probability of the cognitive components was the traditional food topic reflecting the unique image of Jordanian traditional food. Affective images formed by users were mainly positive emotions, indicating that the destination image spread well.