Local spatiotemporal modeling of house prices: a mixed model approach

The real estate market has long provided an active application area for spatial–temporal modeling and analysis and it is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics, but house prices tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be based on property values from previous years and in the spatial–temporal dimension, the properties on which current prices are based tend to be in close spatial proximity. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using ten years of house price data in Fife, Scotland (2003–2012), this research applies a mixed model approach, semiparametric geographically weighted regression (GWR), to explore, model, and analyze the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates that the mixed modeling technique provides better results than standard approaches to predicting house prices by accounting for spatiotemporal relationships at both global and local scales

Analysing the local geography of the relationship between residential property prices and its determinants

This paper analyses the local geography of the relationship between residential property prices and its determinants. A semiparametric geographically weighted regression (S-GWR) technique is employed to explore this relationship. Selling prices, structural and locational attributes data were collected from the database of the Department of Valuation and Services of Malaysia, selected maps and reports. The outcome of this paper shows a strong geographically varying relationship between residential property prices and its determinants in which the residential property price determinants have a positive impact on prices in some areas but negative or no impact on the others. The magnitude of the effect is also found to be geographically varied; the capitalisation in residential property prices is found greater in some areas but less or with no effect in some other parts of the areas. The use of S-GWR technique makes it possible to reveal such geographically varying relationships, thus leading to a better understanding of the relationship between residential property prices and its determinants

Modeling malaria cases associated with environmental risk factors in Ethiopia using geographically weighted regression

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesIn Ethiopia, still, malaria is killing and affecting a lot of people of any age group somewhere in the country at any time. However, due to limited research, little is known about the spatial patterns and correlated risk factors on the wards scale. In this research, we explored spatial patterns and evaluated related potential environmental risk factors in the distribution of malaria cases in Ethiopia in 2015 and 2016. Hot Spot Analysis (Getis-Ord Gi* statistic) was used to assess the clustering patterns of the disease. The ordinary least square (OLS), geographically weighted regression (GWR), and semiparametric geographically weighted regression (s-GWR) models were compared to describe the spatial association of potential environmental risk factors with malaria cases. Our results revealed a heterogeneous and highly clustered distribution of malaria cases in Ethiopia during the study period. The s-GWR model best explained the spatial correlation of potential risk factors with malaria cases and was used to produce predictive maps. The GWR model revealed that the relationship between malaria cases and elevation, temperature, precipitation, relative humidity, and normalized difference vegetation index (NDVI) varied significantly among the wards. During the study period, the s-GWR model provided a similar conclusion, except in the case of NDVI in 2015, and elevation and temperature in 2016, which were found to have a global relationship with malaria cases. Hence, precipitation and relative humidity exhibited a varying relationship with malaria cases among the wards in both years. This finding could be used in the formulation and execution of evidence-based malaria control and management program to allocate scare resources locally at the wards level. Moreover, these study results provide a scientific basis for malaria researchers in the country

Voter turnout in Portugal: a geographical perspective

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementThe decline of voter turnout in Portugal has been confirmed in the last legislative election of 2015. This fact, together with the unquestionable democratic value associated with the act of voting, leads to the discussion of the issue and emphasizes the need for additional investigation concerning the portuguese context. Particularly, it is crucial to identify the characteristics of citizens who vote, to better understand the phenomenon and think about solutions. This work aims to identify the most significant sociodemographic variables in explaining voter turnout in continental Portugal and describe the relationship between those variables and voter turnout, including the geographical variation existing across the municipalities. Data related to sociodemographic variables are provided from population census 2011, and turnout results concerns the legislative election of the same year. The chosen variables have been addressed in literature, both in meta-analyses studies and in country level empirical investigation. The analysis starts with the conventional Ordinary Least Squares (OLS), and continue with more spatially sensitive methods, namely Geographically Weighted Regression (GWR) and its semiparametric extension (SGWR). The final method, SGWR, enables the investigation of local variations in turnout values, simultaneously considering that its relationship with some variables might not vary over space. Results show that turnout is a complex process, influenced by a set of sociodemographic variables. While some variables affect turnout differently over the country (percentage of family cores with children aged less than 15, and percentage of owner-occupied houses), others affect it uniformly (percentage of graduated residents, percentage of classic families, and distance to Lisbon or Oporto – the nearest). This highlights the use of a semiparametric approach to better understand turnout and for further research on voting issues

A Geographical Perspective

Manoel, L., Costa, A. C., & Cabral, P. (2022). Voter Turnout in Portugal: A Geographical Perspective. Papers in Applied Geography, 8(1), 88-111. https://doi.org/10.1080/23754931.2021.1958251The decline of voter turnout in Portugal was confirmed in the legislative election of 2015. The unquestionable democratic value associated with the act of voting, leads to the discussion of this issue, and emphasizes the need for additional investigation. Particularly, it is crucial to identify the characteristics of citizens who vote, to better understand the phenomenon and think about solutions. This work identified the most significant sociodemographic variables in explaining voter turnout in continental Portugal and described the relationship between those variables and voter turnout, including the geographical variation existing across the municipalities. A Semiparametric Geographically Weighted Regression (SGWR) model enabled the investigation of local variations in turnout values, simultaneously considering that its relationship with some variables might vary over space. Results show that turnout is influenced by a set of sociodemographic variables. While some variables affect turnout differently over the country (percentage of family cores with children aged less than 15, and percentage of owner-occupied houses), others affect it uniformly (percentage of graduated residents, percentage of classic families, and distance to Lisbon or Oporto–the nearest). These results suggest the use of a semiparametric approach to better understand turnout and for further research on voting issues.authorsversionpublishe

マルチスケールの視点からみた中国における都市開発と人口移動の関係に関する研究

Development is the main problem facing cities in the world today. Urban development is inseparable from the support of labor. The population movement between regions provides a guarantee for the sustainable development of the city. Therefore, the interactive relationship between urban development and population mobility needs more in-depth research. This research combines official statistics and emerging big data to study the interactive relationship between urban development and population mobility from the macro, meso and micro levels. In addition, with the help of exploratory spatial data analysis methods, the spatial effects between urban development and population mobility can be captured, including spatial dependence and spatial heterogeneity. The use of spatial econometric models reveals the driving forces that affect population mobility. The results of the empirical analysis can provide a theoretical reference for the future development of China’s urbanization.北九州市立大

PEMODELAN KEJADIAN GIZI BURUK PADA BALITA DI SURABAYA BERDASARKAN PENDEKATAN REGRESI SPASIAL SEMIPARAMETRIK

Masalah gizi buruk pada balita di Surabaya menjadi perhatian khusus untuk ditangani secara serius karena hampir semua kecamatan di Surabaya ditemukan kasus balita gizi buruk. Dalam penelitian ini akan dikembangkan model prediksi seberapa besar kejadian gizi buruk balita di setiap kecamatan di Surabaya berdasarkan faktor-faktor yang mempengaruhinya dengan mempertimbangkan aspek lokasi geografis (spasial) menggunakan metode regresi spasial semiparametrik dan selanjutnya dilakukan validasi model untuk mendapatkan model prediksi yang terbaik dengan membandingkan nilai AIC dan R2 dari model yang terbentuk. Hasil pemodelan kejadian gizi buruk balita di Surabaya berdasarkan fungsi pembobot Fixed Gaussian memiliki nilai AIC terkecil dan R2 tertinggi, sehingga model terbaik yang digunakan dalam penelitian ini yaitu model regresi spasial semiparametrik berdasarkan pembobot Fixed Gaussian dengan ketepatan prediksi sebesar 85%. Faktor-faktor yang berpengaruh secara lokal adalah prosentase rumah tangga yang mendapat akses air bersih (X1), prosentase rumah tangga miskin (X3), rasio jumlah tenaga kesehatan dengan jumlah balita (X4), prosentase bayi tidak mendapat ASI eksklusif (X5), dan prosentase ibu hamil mendapat tablet Fe (X6). Sedangkan prosentase Bayi Berat Lahir Rendah (BBLR) (X2) berpengaruh secara global. Kata kunci: Gizi Buruk pada Balita, Regresi Spasial Semiparametri

The Temporal Dimension of Tourist Attraction

Tourist attractions are vital sub-elements in the tourism system. Despite drawing considerable attention in the tourism literature, most studies suffer from a lack of in-depth analysis of the theoretical foundation. This research aims to analyze the temporal nature of tourist attraction, thereby linking the cognitive and organizational perspective of tourist attraction classification by its temporal dimension. From the organizational perspective of tourist attraction classification, a further purpose is to classify tourist attractions regarding their temporal dimension. This paper shows the organizational influence of time regarding when and how long an attraction occurs. The cognitive and organizational perspective typologies of tourist attractions are linked by a common unit of measurement: time. With regard to their temporal dimension, tourist attractions are classified as STA - Stationary attraction and SEA - Seasonal attractions. This study contributes to the literature by providing an insight into the temporal dimension of tourist attractions and the understanding of the cognitive and organizational perspective and their interconnection within tourist attraction typology. The defined framework can be applied in the comparison and evaluation of tourist attractions providing the basis for further discussion on the nature of tourist attractions

中国と日本における都市発展及びその環境への影響の総合評価に関する研究

This study mainly focused on the spatial effect on city development. Spatial analysis was conducted to explore the characteristics and correlates of city development, and its impact on environment for cities in China and Japan. The issue of city development was investigated from multiple perspectives. The history of urban development process in China and Japan was summarized, and the correlates with urban development were compared. Meanwhile, the urban heat island of cities in China and Japan were compared北九州市立大

Examining the Determinants of Location Attributes and their Effect on Hotel Pricing in the Period of the Covid-19 Pandemic in an Emerging Market

The emergence of COVID-19 and the consequent travel restrictions have led to a decrease in the patronage of hotel services in nearly all economies in the world. In this circumstance, location attributes have become even more important in hotel pricing and investment decision-making. It is even more interesting to see how this plays out in emerging economies such as Ghana. The study assesses the effect of location attributes on hotel pricing during the COVID-19 pandemic period in Tamale. A sequential mixed research design including Mixed Spatial Hedonic Price Approach, Exploratory Factor Analysis and key informant interviews was employed. A sample of 815 tourists and 163 hotels was used. Hotel class, road accessibility, age of building, and hotel rate are the key determinants of hotel pricing. Among these, the hotel class showed more significance in influencing pricing decisions in the COVID-19 period. The models show that the hotel class with positive coefficients are located outside the city centre of Tamale. This has resulted in increased Yield To Maturity because the hotels located outside the city centre received more clients, with grade one hotels showing a huge net income and good post-COVID-19 investment drive. The results show that potential hotel investors should consider hotel class as a major entry decision factor during and after periods of the pandemic