{"title":"Scope of GIS in Dental Public Health – A Review","authors":"","doi":"10.4018/ijagr.298295","DOIUrl":"https://doi.org/10.4018/ijagr.298295","url":null,"abstract":"The spatial variations affecting oral health can be determined by using the evolving technology, Geographical Information System (GIS). The present article aims to review various GIS applications in dental public health and to critically examine the strengths, limitations and challenges of utilising GIS in dental public health. GIS has helped in many areas like spatial patterning of dental services, effects of interventions and contextual level influences on oral health. Still, there are few limitations with GIS like limited availability of spatial data, highly dependent on the amount and quality of data for different regions, wide variation of GIS software applications, cost of software, hardware and training. The strategic opportunities for its use should be maximized for the mutual benefit of researchers, practitioners, decision makers, and our communities.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42800420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying Spatio-temporal Clustering of the COVID-19 Patterns Using Spatial Statistics","authors":"A. Hoang, T. T. Nguyen","doi":"10.4018/ijagr.297517","DOIUrl":"https://doi.org/10.4018/ijagr.297517","url":null,"abstract":"An outbreak of the COVID-19 pandemic caused by the SARS CoV 2 has profoundly affected the world. This study aimed to identify the spatio-temporal clustering of COVID-19 patterns using spatial statistics. Local Moran’s I spatial statistic and Moran scatterplot were first used to identify high-high and low-low clusters and low-high and high-low outliers of COVID-19 cases. Getis-Ord’s〖 G〗_i^* statistic was then applied to detect hotspots and coldspots. We finally illustrated the used method by using a dataset of 10,742 locally transmitted cases in four COVID-19 waves in 63 prefecture-level cities/provinces in Vietnam. The results showed that significant low-high spatial outliers of COVID-19 cases were first detected in the north-eastern region in the first wave and in the central region in the second wave. Whereas, spatial clustering of high-high, low-high and high-low was mainly found in the north-eastern region in the last two waves. It can be concluded that spatial statistics are of great help in understanding the spatial clustering of COVID-19 patterns.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46153745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessment of Drought using Earth Observation Data and Cloud Computing in Morocco for 2010-2020","authors":"","doi":"10.4018/ijagr.298260","DOIUrl":"https://doi.org/10.4018/ijagr.298260","url":null,"abstract":"Drought is an extreme event that has hit several countries in the world including Morocco. The aim of this research was to assess drought in Morocco with a view to providing information for planning and management of droughts. For this, three drought indices were chosen: Combined Drought Indicator (CDI), Soil Moisture Agricultural Drought Index (SMADI), and Microwave Integrated Drought Index (MIDI). Drought monitor was done during the growing seasons of 2010-2020 using Earth Observation data and cloud computing with the mapping of the drought indices and their inter-comparing via Pearson correlation. The main drought events were tracked and drought characteristics analyzed. Seven drought years were tracked for regions of cereal production. CDI and MIDI were very well correlated, whereas SMADI showed poor correlation with CDI and MIDI. Validation of results was done by comparing our results with another study for the 2015-2016 drought event and comparing yearly precipitation with the long-term average. An Earth Engine App of the three indices was published to make public drought maps.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42224232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NEIGHBORHOOD CHANGE IN CHICAGO AND ITS SUBURBS, 1990 – 2019","authors":"","doi":"10.4018/ijagr.298297","DOIUrl":"https://doi.org/10.4018/ijagr.298297","url":null,"abstract":"This research empirically examines neighborhood change, as measured by change in per capita income, for 335 Chicago neighborhoods and suburbs for the period 1990 to 2019. Its purpose is to examine the factors associated with neighborhood change in a metropolitan region anchored by a shrinking central city. Using Geographically Weighted Regression, this research analyzes the spatially varying impacts of explanatory variables commonly found in the urban resurgence literature such as race, ethnicity, education, and nativity. The results show that the areas experiencing the highest change in per capita income were the northern neighborhoods of Chicago as well certain suburbs on the suburban fringe, Conversely, decline in per capita income occurred in the inner-ring suburbs, particularly those to the south and west of Chicago. The results further show that some minority neighborhoods in Chicago experienced income ascent relative to the rest of the metropolitan area, which challenges the findings of some previous studies and provides insights for community and suburban planners.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42704473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Integrated Approach to Geovisualize Epidemiological Data","authors":"","doi":"10.4018/ijagr.298296","DOIUrl":"https://doi.org/10.4018/ijagr.298296","url":null,"abstract":"Today, geovisualization is frequently and effectively used to communicate and present geographic information. Indeed, By using dynamic and interactive tools, geovisualization makes it possible to catalyse the transition from raw data to informative data transmitted to the user via a graphic representation, such as the map or 3D visualization. In this paper we presents an integration system based on a methodological approach dedicated to geovisualization of epidemiological data integrating GIS and anamorphic maps :cartograms. The main objective is to explore raw data, structure it, and translate it into interpretable information. This work is part of an approach to assist in the analysis and exploration of data on tuberculosis in the city of Oran. The objective is to produce epidemiological maps in a form adapted to the perceived reality. This deformation of space is constructed by a mathematical model based on Gastner Newman's algorithm and Bertin's graphic semiology.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41336394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Perceived Role of Communities and Government Officials in Solid Waste Management in Ghana, West Africa.","authors":"","doi":"10.4018/ijagr.295863","DOIUrl":"https://doi.org/10.4018/ijagr.295863","url":null,"abstract":"This study examined the role of community members and government officials in sustainable solid waste management and identified options to improve waste management in Ghana. Mixed-methods approach was used in research design, data collection, and analysis. Data was collected from 81 community members drawn from three areas (Kanda, Asylum Down, and Nima) in the Accra Metropolitan Area, and four government officials. Data sets were analyzed using manual transcription, coding and Microsoft excel. The study revealed that communities are actively involved in managing waste. However, education and enforcement measures have not been effective due to political interference and a lack of resources. Furthermore, the study found that greater support from local government and stakeholders is needed in managing waste. The study recommends educating community members and integrating waste pickers into Ghana’s waste management stream to reduce the costs involved in SSWM and gain social and environmental benefits..","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45375536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of lithology using Sentinel-2A through an ensemble of machine learning algorithms","authors":"","doi":"10.4018/ijagr.297524","DOIUrl":"https://doi.org/10.4018/ijagr.297524","url":null,"abstract":"Remotely sensed data has become an effective, operative and applicable tool that provide critical support for geological surveys and studies by reducing the costs and increasing the precision. Advances in remote-sensing data analysis methods, like machine learning algorithms, allow for easy and impartial geological mapping. This study aims to carry out a rigorous comparison of the performance of three supervised classification methods: Random Forest, k-Nearest Neighbor and maximum likelihood using remote sensing data and additional information in Souk El Had N’Befourna region. The enhancement of remote sensing geological classification by using geomorphometric features, principal component analysis, gray level co-occurrence matrix (GLCM) and multispectral data of the Sentinel-2A imagery was highlighted. The Random Forest algorithm showed reliable results and discriminated limestone, dolomite, conglomerate, sandstone and rhyolite, silt and Alluvium, ignimbrite, granodiorite, Lutite, granite, and quartzite. The best overall accuracy (~91%) was achieved by Random Forest algorithm.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41760938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatiotemporal Trace of Human Behaviors and Responses Pertaining to Winter Storm Dylan","authors":"Seungil Yum","doi":"10.4018/ijagr.304891","DOIUrl":"https://doi.org/10.4018/ijagr.304891","url":null,"abstract":"This study highlights how Winter storm Dylan plays a significant role in human behaviors and responses according to a multitude of periods, geographical scales, census regions, sociodemograhpic, and regional characteristics. This study finds that people show different behaviors and responses according to periods, states, and regional characteristics. Second, tweets are relatively uploaded across the US states during the winter storm week, compared to the pre-winter storm and post-winter storm weeks. Third, regions play an important role in displacements. Minnesota and Massachusetts exhibit 5.1 and 1.8 times more displacements than Montana. Fourth, while total employment is negatively associated with displacements, jobs per household and regional diversity are positively associated with them. The dense business areas show 0.4 times less displacements than the thin business areas, and places that have many workers per household and high regional diversity show 2.3 and 1.6 times more displacements than the other places.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44312485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bakul Budhiraja, P. Pathak, Girish Agarwal, R. Sengupta
{"title":"Satellite and Ground Estimates of Surface and Canopy-Layer Urban Heat Island","authors":"Bakul Budhiraja, P. Pathak, Girish Agarwal, R. Sengupta","doi":"10.4018/ijagr.2021100101","DOIUrl":"https://doi.org/10.4018/ijagr.2021100101","url":null,"abstract":"The urban heat island (UHI) effect is one of the prominent impacts of urbanization that affects human health and energy consumption. As the data is limited and inconsistent, UHI comparative studies between UHIUCL and UHISurf on the seasonal scale are limited. The use of only daytime summer imagery reporting “Inverted UHI” undermines the holistic view of the phenomenon. Therefore, this study analyses the seasonal patterns for UHISurf and UHIUCL in three climate zones (Delhi, Pune, and Montreal). The three cities experience a high traditional night-time UHIUCL (Delhi 7°C, Pune 6°C, Montreal 1.89°C). Landsat captures a prominent daytime UHISurf (15°C) in Montreal with temperate climate and daytime inverted UHISurf (-4°C) for Delhi in summer. Seasonally, the night-time UHI is prominent in summer and monsoon for Delhi, summer and spring for Pune, and summer for Montreal. Due to UHI effect, the heatwaves can be more intense in semi-arid and tropical cities than temperate cities.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42537418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Combination Technique for Land Cover Classification of Optical Multispectral Images","authors":"Keerti Kulkarni, Vijaya P. A.","doi":"10.4018/ijagr.2021100102","DOIUrl":"https://doi.org/10.4018/ijagr.2021100102","url":null,"abstract":"The need for efficient planning of the land is exponentially increasing because of the unplanned human activities, especially in the urban areas. A land cover map gives a detailed report on temporal dynamics of a given geographical area. The land cover map can be obtained by using machine learning classifiers on the raw satellite images. In this work, the authors propose a combination method for the land cover classification. This method combines the outputs of two classifiers, namely, random forests (RF) and support vector machines (SVM), using Dempster-Shafer combination theory (DSCT), also called the theory of evidence. This combination is possible because of the inherent uncertainties associated with the output of each classifier. The experimental results indicate an improved accuracy (89.6%, kappa = 0.86 as versus accuracy of RF [87.31%, kappa = 0.83] and SVM [82.144%, kappa = 0.76]). The results are validated using the normalized difference vegetation index (NDVI), and the overall accuracy (OA) has been used as a comparison basis.","PeriodicalId":43062,"journal":{"name":"International Journal of Applied Geospatial Research","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41717009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}