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Advanced remote sensing technologies have undoubtedly revolutionized palm oil industry management by bringing business and environmental benefits on a single platform. It is evident from the ongoing trend that remote sensing using satellite and aerial data is able to provide precise and quick information for huge palm oil plantation areas using high-resolution image processing, which is also recognized by the certification agencies, i.e., the Roundtable on Sustainable Palm Oil (RSPO) and ISCC (International Sustainability and Carbon Certification). A substantial improvement in the palm oil industry could be attained by utilizing the latest Geo-information tools and technologies equipped with AI (Artificial Intelligence) algorithms and image processing, which could help to identify illegal deforestation, tree count, tree height, and the early detection of diseased leaves. This paper reviews some of the latest technologies equipped with remote sensing, AI, and image processing for managing the palm oil plantation. This manuscript also highlights how the distress in the current palm oil industry could be handled by mentioning some of the improvised monitoring systems for palm oil plantation that could in turn increase the yield of palm oil. It is evident from the proposed review that the accuracy of AI algorithms for palm oil detection depends on various factors such as the quality of the training data, the design of the neural network, and the type of detection task. In general, AI models have achieved high accuracy in detecting palm oil tree images, with some studies reporting accuracy levels up to 91%. However, it is important to note that accuracy can still be affected by factors such as variations in lighting conditions and image resolution. Nonetheless, with any AI model, the accuracy of algorithms for palm oil tree detection can be improved by collecting more diverse training data and fine-tuning the model. [ABSTRACT FROM AUTHOR]

Advanced remote sensing technologies have undoubtedly revolutionized palm oil industry management by bringing business and environmental benefits on a single platform. It is evident from the ongoing trend that remote sensing using satellite and aerial data is able to provide precise and quick information for huge palm oil plantation areas using high-resolution image processing, which is also recognized by the certification agencies, i.e., the Roundtable on Sustainable Palm Oil (RSPO) and ISCC (International Sustainability and Carbon Certification). A substantial improvement in the palm oil industry could be attained by utilizing the latest Geo-information tools and technologies equipped with AI (Artificial Intelligence) algorithms and image processing, which could help to identify illegal deforestation, tree count, tree height, and the early detection of diseased leaves. This paper reviews some of the latest technologies equipped with remote sensing, AI, and image processing for managing the palm oil plantation. This manuscript also highlights how the distress in the current palm oil industry could be handled by mentioning some of the improvised monitoring systems for palm oil plantation that could in turn increase the yield of palm oil. It is evident from the proposed review that the accuracy of AI algorithms for palm oil detection depends on various factors such as the quality of the training data, the design of the neural network, and the type of detection task. In general, AI models have achieved high accuracy in detecting palm oil tree images, with some studies reporting accuracy levels up to 91%. However, it is important to note that accuracy can still be affected by factors such as variations in lighting conditions and image resolution. Nonetheless, with any AI model, the accuracy of algorithms for palm oil tree detection can be improved by collecting more diverse training data and fine-tuning the model.

Incidence and prevalence rates of dengue have increased over the years, and the disease is quickly becoming cause for concern within the public health community. Globally, 128 countries and slightly under four billion people are at risk of contracting dengue. In Sri Lanka, more than half of dengue cases originate in Colombo, which in previous years, used a manual pen-and-paper data management system, which meant that it was not possible to obtain or provide up-to-date information about the severity and spread of dengue. In 2015, two versions of a mobile application called Mo-Buzz Dengue were developed and launched in Colombo, Sri Lanka in order to overcome the challenges of the traditional management system by capitalizing on the rising affordability and ubiquity of mobile phone technology. To keep up with the dynamic nature of disease outbreaks, real-time data need to be visualized in a manner which facilitates discerning and comprehending these patterns. Hence, we used health maps in Mo-Buzz to effectively present this information. The first version of Mo-Buzz was for public health inspectors (PHIs), digitized data management as well as provided educational materials. The second version of Mo-Buzz was a source of information for the general public, a crowdsourcing platform to provide information relating to dengue transmission, and for health authorities to alert users to dengue-specific developments in their area. This paper illustrates the design considerations of the Mo-Buzz disease surveillance system for the general public. A draft scaled-down version of the PHI system was used to obtain feedback and make incremental design enhancements. Additionally, similar health maps were evaluated in terms of capability and usability. These findings were applied to identify future enhancements to the health map of Mo-Buzz Dengue. [ABSTRACT FROM AUTHOR]

The allocation of medical resources is usually inappropriate in China because it is mainly based on the population of each administrative area. In real life, individual patients make choices based on numerous other factors, such as the quality of medical service, the service capacity of certain hospitals and their own income level. This study aims to reveal the differences between theoretical medical resource allocation and the actual medical treatment choices of liver cancer patients in Shenzhen, China, based on case data from 2010 to 2012. Two categories with six group maps are used to illustrate this situation, including independent charts and analytical method-based thematic maps. Meaningful conclusions are then proposed to improve medical resource allocation.

Background: Strategies to improve maternal health in low-income countries are increasingly embracing partnership approaches between public and private stakeholders in health. In Tanzania, such partnerships are a declared policy goal. However, implementation remains challenging as unfamiliarity between partners and insufficient recognition of private health providers prevail. This hinders cooperation and reflects the need to improve the evidence base of private sector contribution. Objective: To map and analyse the capacities of public and private hospitals to provide maternal health care in southern Tanzania and the population reached with these services. Design: A hospital questionnaire was applied in all 16 hospitals (public n=10; private faith-based n=6) in 12 districts of southern Tanzania. Areas of inquiry included selected maternal health service indicators (human resources, maternity/delivery beds), provider-fees for obstetric services and patient turnover (antenatal care, births). Spatial information was linked to the 2002 Population Census dataset and a geographic information system to map patient flows and socio-geographic characteristics of service recipients. Results: The contribution of faith-based organizations (FBOs) to hospital maternal health services is substantial. FBO hospitals are primarily located in rural areas and their patient composition places a higher emphasis on rural populations. Also, maternal health service capacity was more favourable in FBO hospitals. We approximated that 19.9% of deliveries in the study area were performed in hospitals and that the proportion of c-sections was 2.7%. Mapping of patient flows demonstrated that women often travelled far to seek hospital care and where catchment areas of public and FBO hospitals overlap. Conclusions: We conclude that the important contribution of FBOs to maternal health services and capacity as well as their emphasis on serving rural populations makes them promising partners in health programming. Inclusive partnerships could increase integration of FBOs into the public health care system and improve coordination and use of scarce resources.

The allocation of medical resources is usually inappropriate in China because it is mainly based on the population of each administrative area. In real life, individual patients make choices based on numerous other factors, such as the quality of medical service, the service capacity of certain hospitals and their own income level. This study aims to reveal the differences between theoretical medical resource allocation and the actual medical treatment choices of liver cancer patients in Shenzhen, China, based on case data from 2010 to 2012. Two categories with six group maps are used to illustrate this situation, including independent charts and analytical method-based thematic maps. Meaningful conclusions are then proposed to improve medical resource allocation. [ABSTRACT FROM AUTHOR]

Background: Strategies to improve maternal health in low-income countries are increasingly embracing partnership approaches between public and private stakeholders in health. In Tanzania, such partnerships are a declared policy goal. However, implementation remains challenging as unfamiliarity between partners and insufficient recognition of private health providers prevail. This hinders cooperation and reflects the need to improve the evidence base of private sector contribution. Objective: To map and analyse the capacities of public and private hospitals to provide maternal health care in southern Tanzania and the population reached with these services. Design: A hospital questionnaire was applied in all 16 hospitals (public n = 10; private faith-based n = 6) in 12 districts of southern Tanzania. Areas of inquiry included selected maternal health service indicators (human resources, maternity/delivery beds), provider-fees for obstetric services and patient turnover (antenatal care, births). Spatial information was linked to the 2002 Population Census dataset and a geographic information system to map patient flows and socio-geographic characteristics of service recipients. Results: The contribution of faith-based organizations (FBOs) to hospital maternal health services is substantial. FBO hospitals are primarily located in rural areas and their patient composition places a higher emphasis on rural populations. Also, maternal health service capacity was more favourable in FBO hospitals. We approximated that 19.9% of deliveries in the study area were performed in hospitals and that the proportion of c-sections was 2.7%. Mapping of patient flows demonstrated that women often travelled far to seek hospital care and where catchment areas of public and FBO hospitals overlap. Conclusions: We conclude that the important contribution of FBOs to maternal health services and capacity as well as their emphasis on serving rural populations makes them promising partners in health programming. Inclusive partnerships could increase integration of FBOs into the public health care system and improve coordination and use of scarce resources. [ABSTRACT FROM AUTHOR]

The design and development of a highly interactive web-based, GIS-enabled atlas is reported. The atlas is a prototype, designed as a model for implementation of atlases to support government cancer-control activities. This model integrates symbolisation and design principles from print cartography, interaction strategies from exploratory geovisualisation, and web-map/web-feature service advances from GIS. The atlas has been implemented using a client-server architecture. It makes use of two open-source GIS tools, PostGIS (as the system database) and GeoServer (to connect the database to the client mapping application). The client mapping application has been built in Macromedia Flash. The entire client-server architecture is described, then direct primary emphasis is focused on the client mapping application. For this component of the system, the interface design strategy is detailed, the approach taken to implement this strategy in Flash is documented, and the mechanisms developed to build dynamic links from the client to the underlying database through the server are outlined. Features of the atlas are presented through a prototypical use scenario for a target user. [ABSTRACT FROM AUTHOR]

This article seeks to recover the origins of health geography, from the production of the first disease maps to the incorporation of new spatial analysis techniques in the last decades. This evolution has also been accompanied by a profound review of paradigms, theories and methods, with a greater emphasis on the relationship between man and the environment, and with approaches that relate socio-spatial structure to health problems at the various scales where they manifest themselves. The current health geography is confronted with the need to articulate the association between the health-disease process and the disease-care binomial, in search of equity, prevention of diseases and diseases and health promotion.