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This article presents the findings from a study on Land Use and Land Cover (LULC) predictions for Pathumthani province in 2028 and 2038. Utilizing Landsat satellite imagery data from 2013, 2018, and 2023, and employing the Cellular Authomata – Artificial Neural Network (CA-ANN) algorithm in MOLUSCE plugin in QGIS, the study simulated future LULC trends. The predictor variables used in the analysis are distance from main roads, distance sky train stations, distance from universities, and distance from markets. The overall accuracy and kappa coefficient of the prediction model validate its reliability for forecasting LULC changes. The results illustrate evolving urban landscapes and environmental dynamics, with vegetation predominating in the eastern and western regions of Pathumthani in 2028, while built-up areas concentrate along major transportation routes. By 2038, these trends persist, with notable expansion of built-up areas, particularly in Muang Pathumthani, Khlong Luang, and Lam Luk Ka districts. Significant urbanization is observed in Muang Pathumthani along the Chao Phraya River, driven by proximity to Nonthaburi. Lam Luk Ka experiences substantial development, supported by infrastructure and connectivity to Bangkok, while Thanyaburi sees urbanization along the Rangsit-Nakornnayok road. Khlong Luang emerges as an urban expansion hub, influenced by Highway No.1 and industrial estates. The study underscores the complex interplay of infrastructure, demographics, and environmental factors, emphasizing the need for sustainable planning to address future challenges. [ABSTRACT FROM AUTHOR]

Generative Adversarial Networks widely known as GANs, are deep learning models that has gained a lot of popularity in the last few years due to their promising nature. One of their major applications can be found in the healthcare sector for various purposes like image reconstruction, image enhancement, image segmentation, image processing, image analysis etc. The objective of this paper is to bring forward some of the recent research on the application of GANs in the health care domain during 2017 – 2022. A total of 168 papers were screened out of which 77 relevant to the present study were finalized for this study. Bibliometric analysis was also performed on these documents, to obtain an overall picture of Generative Adversarial Networks (GANs) in the healthcare domain. This analysis is expected to help the future researcher and developers in targeting the areas of the healthcare sector which are likely to grow in the coming future using GANs algorithms. [ABSTRACT FROM AUTHOR]

Health sector has emerged a major area where GIS and other geoinformatics tools are being increasingly applied. Health sector and experts of disease control and spatial epidemiology are keen to use GIS to see the geographic extent of their work and disease patterns, trends and risk zones so that they can provide best services in limited resources and can have a bigger picture of the disease spread and outbreak. This module is part of the GeoS4S project co-funded under ERASMUS + by European Union. This module presents the application of GIS for disease surveillance and establishing its' causative factors using various type of strong and rich repertoire of geospatial tools of analysis. This paper presents an overview of the lessons, hands on exercises and assignments that will help the students to attain the objectives of the learning of this new are of application of GIS. The course is prepared considering its scope as online material for slef-learning but it may very well be used direct teaching in traditional class room setting in an institution. [ABSTRACT FROM AUTHOR]

Many positioning systems designed to determine or track a user's location have been proposed many years. There are three categories: global location systems, wide-area location systems based on cellular networks and indoor location system. Global position system (GPS) receives signals from multiple satellites and employs a triangulation process to determine physical location. The limitation is inefficient for indoor use or in urban areas where high building shield the satellite signals. Wide-area location systems based on cellular involves measuring the signal strength; the angle of signal arrival and/or the time difference of signal arrive and is highly limited by the cell size. Several approaches have been proposed for indoor location sensing; such as infrared sensing, radio frequency, ultrasonic, and scene capture analysis. Each of these methods has their own advantages and disadvantages. Some are expensive to implement, while others are not very accurate. A wireless local-area network (WLAN) based positioning system has distinct advantages over all other system. Due to it is an economical solution because the WLAN network usually exists already as part of the communications infrastructure. Notebook computers, personal digital assistants (PDA), or the other mobile device equipped with WLAN capability, the position system can be implemented in software. The WLAN covered the large area compared with other types of indoor positioning systems. The system used an underlying wireless data network, such as the IEEE 802.11 wireless network, to estimate user location has gained attention recently, for indoor applications and do not require additional hardware for user location determination. [ABSTRACT FROM AUTHOR]

The objective of this study was to utilize the space-time permutation scan statistic and GIS for investigating and visualizing the spatial diffusion of diarrhea outbreaks in Chiang Mai province, Thailand. A space-time retrospective analysis was conducted to detect the outbreak signals of diarrhea from 1 November 2003 to 31 October 2006, in order to include all confirmed diarrhea cases of patient less than five years of age. A total of 37,536 diarrhea cases were reported in Chiang Mai from November 1, 2003 to October 31, 2006. In the study, period had more village outbreak and the diarrhea incidence was so high. The strongest signals of outbreak (13 villages) was on 17 January 2006 (cool season) and occurred to the conurbations of Mac Chaem district (Chang Khoeng and Tha Pha sub-districts), which is located about 100 km to the south-west of Chiang Mai City. This signal had 44 cases observed over 8 days when 2.98 were expected (relative risk = 14.79). The weaker signal was on 29 June 2005 (begin of rainy season) that were located in southern Chiang Mai (Chore Thong district), there had 16 cases observed over 11 days when 1.21 were expected theoretically (relative risk = 13.24). The daily spatial spread or diffusion of diarrhea outbreak from the first day to the end day of incidence (17-24 January 2006) in the study site of Mac Chaem district was follow a pattern of contagious diffusion. They spread outward from a village of origin (Ban Rai), with high incidence to nearby villages, which related to the area of high population densities, within the urban and agricultural areas along the main course of Mae Chaem River. [ABSTRACT FROM AUTHOR]

In 2009, the fatal outbreak of H1N1 influenza A became one of the most serious global concerns since mid-April. Within two months, the outbreak spectrum surged to pandemic. After one year, H1N1 caused at least 18,000 deaths in more than 200 countries worldwide. However, with timely collaborative responses among various organizations worldwide, the spread of the disease was finally brought back to normal. Swift action and cooperation through sharing relevant and comprehensive information played a crucial role for decision makers to issue pertinent measures and guidelines for preparedness and response. By deploying web-based technology and geographic information systems (GIS), these planning and intervention processes were achieved more economically and effectively. [ABSTRACT FROM AUTHOR]

Geographic Information System (GIS) techniques are used to develop the risk zone map of Dengue Fever (DF)/Dengue Haemorrhagic Fever (DHF) in Chachoengsao province, Thailand. The risk zonation index is derived using the Analytical Hierarchy Process (AHP). The medical database considered for the study was referenced to the geographical and meteorological data layers. Based on this analysis, potential areas were categorized as very high, high, moderately high, moderately low, low, and very low risk categories. The model used in this study provided valuable information to prepare DF/DHF risk zones for decision support to mitigate the epidemic. Factor weights used in AHP were evaluated and found to be acceptable as the consistency ratio (CR) was 0.031, which was < 0.1. Spatial modelling included a huge database about physical-environment, climatic, and demographic factors. Approximately, 74.96% people lived in very high, high, and moderately high risk zones. The most at risk zone was shown to be Mueang Chachoengsao district with a population of 142,485 or 22.34% of total population. The results from AHP based DF/DHF risk zonation gave useful information on different levels of disease risk areas. The methodology is general and can he applied in other application fields, such as disease outbreak during natural disaster. [ABSTRACT FROM AUTHOR]

The Chi River always faces floods and water shortage problems in the rainy season and subsequent dry season, respectively. The Royal Thai Government emphasizes on construction of floodwater retention reservoirs to store more water along the Chi River. This water is to be used mainly for agriculture in the subsequent dry season. A methodology was developed to identify potential floodwater retention zones using the Analytical Hierarchical Process and GIS-based data. They were surface water, drainage density, landform, land use, soil drainage, salt crust, geological formation, lineament density, vegetation index, and groundwater yield. The result was the potential water retention zones map, which was categorized as excellent, good, moderate, poor and very poor classes. The map was validated with a field survey of floodwater retention site. The results agreed with the field check. The hydrodynamic model (MIKE11) was employed to simulate diversion of discharges from the Chi River into retention reservoirs. The results of simulation revealed that the proposed reservoir (Kud Dok) could retain floodwater at the maximum storage capacity of 8.13 million m³ for return periods of 3, 5, 8 and 25 years. [ABSTRACT FROM AUTHOR]

This investigation is aimed in contribute the concepts and methods of the innovative development and application of Geographical Information System (GIS) and Remote Sensing regarding Malaria prevalence. Kanchanaburi province, Thailand is chosen 0.3 study area. The input data are based on the geospatial factors including climatic aspects, physical environment, and statistical record of Malaria cases. Afterwards data preprocessing needs to be carried out. Malaria cases map and information value (i-value) approach will he used in order to identify the relation between physical and social factors, and also statistical analysis will be carried out so as to define the relation of climatic factor. The final output based on those approaches is a Malaria risk map which is classified into three classes including high risk level, moderate risk level and low risk level. This study also develops the model based on i-values which are formed as thematic layers in GIS database and are computed using different map analysis techniques, for example, map crossing. [ABSTRACT FROM AUTHOR]

Quantitative analysis morphometric parameters such as stream length, drainage density (DD), bifurcation ratio (Rb), slope, shape factors are good indicators for morphological evolution of a basin. Relationships of these parameters with structure, lithology and geomorphology are enhancing the factors which control the erosion behavior of the area and further use for proper management and development programs. In this study LANDSAT ETM+ data is used for DIP techniques such as NDVI and lineaments enhancement, and GIS techniques to extract different models. In this study the Dashtgol basin which is a watershed overlooking the reservoir of the great Shahid Abasspour dam in the south west Iran has selected to evaluate geomorphic factors. This basin is located within the ZFB. It exhibits complex geological and geomorphic configuration. The information from remotely sensed and ground truth data are analysed in GIS environment. Further, the study, area is divided in 10 hydrologic divisions. The results show that the maximum erosion belongs to the sixth hydrologic division (27.5 t/h per year) and the minimum erosion belongs to second hydrologic division (14.8 t/h per year). Geologic interpretation and geomorphic analysis in GIS environment on the Sabzab river profile shows that the tectonic process is a factor to increase the rates of sedimentation and erosion in the study area. [ABSTRACT FROM AUTHOR]

A Geographic Information System based Decision Support System (GIS based DSS) was developed for evaluating the optimal erosion management (which includes soil and water conservation: SWC and crop management system: CMS) alternatives watershed based upon the multi-objectives such as greatest physical effectiveness, cost-benefit return and social benefit acceptance. The system has been developed by integrating the decision element models: erosion model (Universal Soil Loss Equation: USLE, Modified USLE: MUSLE, Potential Nutrient Loss Model), economic model (Cost-Benefit Analysis: CBA), and social benefit model (Net Benefit Index: NBI), with a SWC knowledge based system (SWC-KBS) and multi-objectives optimization approach, into one system, using Arc-View GIS and Visual Basic programming. The application was tested in the Huai Talupkup small watershed, Thailand, an area of 1,550 ha. The selected optimal erosion management for 10 land class units (LCUs), which were based upon the similarity of land management regime which include a variety of terrace practices and suitable crop management systems. The selected optimal erosion management from the system, using a discount rate of 8 % and a project lifetime of 10 years, was found to have a net present value (NPV) of about 9.52 million Thai baht, erosion (soil loss) could be reduced about 78 % while the social net benefit index increased by 47 %from current conditions. The system proposed in this research enables quick review of results for different erosion management alternatives using preference criteria settings, which might not be possible with a dispersed analytical systems computation. It is suggested that this system can be applied to other watersheds for evaluating and enhancing the accuracy in effective decision-making in the optimal erosion management at the small watershed level. [ABSTRACT FROM AUTHOR]