Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans...Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans, such as dengue, yellow fever, chikungunya, West Nile virus, encephalitis and malaria, among many others that are less common. In terms of morbidity and mortality caused by vector-borne diseases, mosquitoes are the most dangerous animals for humanity and, although they also play a role in the ecosystem as a food source for other organisms, their importance for public health cannot be overlooked. As highly efficient vectors, they put more than three billion people at risk, mainly in tropical and subtropical regions as well as in Europe, since heat waves and flooding are becoming more frequent and severe, and summers are getting longer and warmer, accelerating mosquito development, biting rates, and the incubation of the pathogens within their bodies. Female mosquitoes bite to acquire proteins for the development of their ovaries and eggs and, in the process, acquire pathogens and/or parasites from one vertebrate host and transmit them to another, usually after a short period of replication. Three of their four life stages are lived in still freshwater, so it is crucial to understand their range of action when they reach adulthood and leave the water, in order to plan and implement local prevention measures. A set of georeferenced abundance data collected in mainland Portugal over seven years was linked to cartographed water bodies in a geographic information system to estimate the distances at which Culex pipiens s.l. had a significant presence, with criteria based on the size of the catches. The result allows for an estimate of the fly range of those mosquitoes, which can be used to focus countermeasures.展开更多
An aerial photographic coverage acquired on two consecutive days in October 2021 with a ground resolution of 20 cm and a spectral resolution of 4 bands (red, green, blue and near infrared), allowed to distinguish most...An aerial photographic coverage acquired on two consecutive days in October 2021 with a ground resolution of 20 cm and a spectral resolution of 4 bands (red, green, blue and near infrared), allowed to distinguish most of the classes of interest present in the intertidal zone of the Sado estuary. We explored the possibilities of thematic classification in the powerful and complex software ArcGIS Pro;we presented the methodology used in a detailed way that allows others with minimal knowledge of GIS to reproduce the classification process without having to decipher the specifics of the software. The classification implemented used ground truth from four classes related to the macro-occupations of the area. In a first phase we explore the standard algorithms with object-based capabilities, like K-Nearest Neighbor, Random Trees Forest and Support Vector Machine, and in a second phase we proceed to test three deep learning classifiers that provide semantic segmentation: a U-Net configuration, a Pyramid Scene Parsing Network and DeepLabV3. The resulting classifications were quantitatively evaluated with a set of 500 control points in a test area of 37,500 × 12,500 pixels, using confusion matrices and resorting to Cohen’s kappa statistic and the concept of global accuracy, achieving a Kappa in the range [0.72, 0.81] and a global accuracy between 88.9% and 92.9%;the option U-Net had the most interesting results. This work establishes a methodology to provide a baseline for assessing future changes in the distribution of Sado estuarine habitats, which can be replicated in other wetland ecosystems for conservation and management purposes.展开更多
Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens s.l. collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic para...Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens s.l. collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters are evaluated. This work is one of the results of a long-term surveillance program of pernicious insects that act as vectors of various diseases;its focus is on the possibility of prevention that can be achieved with abundance data. The focus on Culex pipiens is justified by its abundance and its competence as a vector for numerous health issues. The cumulative distribution of monthly captures by each meteorological parameter allows to compute thresholds corresponding to mosquito massive presence related to 90% of the captures. Using the weather parameters measured in the network of weather stations across the country, a monthly average of each parameter of interest (temperature, humidity, etc.) is computed and an interpolation of the results is made to produce raster maps corresponding to each month. The previously obtained thresholds are applied to each map, producing spatial masks with the relevant zones for each parameter. The intersection of the various masks for each month shows the most densely populated area of Culex, and the ensemble allows us to observe the evolution of mosquito presence through the critical season, which is from May to October at these latitudes. In parallel, mosquito abundance data are related to physiographic parameters. The relative distribution of female mosquitoes across land cover types in each month allows identifying which classes and seasons are most relevant. Orthometric altitude related to the presence of 90% of the catches shows the limits reached by mosquitoes in each month. The results are applied to the previously obtained climate envelopes, delimiting critical areas where the level of risk of transmission of the pathogens for which Culex pipiens is a competent vector is high and countermeasures should be concentrated, allowing its planning, and targe展开更多
This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden...This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden on the coast becomes a problem, both because erosion makes the cliffs unstable and because pollution increases, making the fragile dune ecosystem difficult to preserve. It is becoming necessary to increase the control of access to beaches, even if it is not a popular measure for internal and external tourism. The methodology described can also be used to monitor maritime borders. The use of images acquired in the infrared range guarantees active surveillance both day and night, the main objective being to mimic the infrared cameras already installed in some critical areas along the coastline. Using a series of infrared photographs taken at low angles with a modified camera and appropriate filter, a recent deep learning algorithm with the right training can simultaneously detect and count whole people at close range and people almost completely submerged in the water, including partially visible targets, achieving a performance with F1 score of 0.945, with 97% of targets correctly identified. This implementation is possible with ordinary laptop computers and could contribute to more frequent and more extensive coverage in beach/border surveillance, using infrared cameras at regular intervals. It can be partially automated to send alerts to the authorities and/or the nearest lifeguards, thus increasing monitoring without relying on human resources.展开更多
文摘Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans, such as dengue, yellow fever, chikungunya, West Nile virus, encephalitis and malaria, among many others that are less common. In terms of morbidity and mortality caused by vector-borne diseases, mosquitoes are the most dangerous animals for humanity and, although they also play a role in the ecosystem as a food source for other organisms, their importance for public health cannot be overlooked. As highly efficient vectors, they put more than three billion people at risk, mainly in tropical and subtropical regions as well as in Europe, since heat waves and flooding are becoming more frequent and severe, and summers are getting longer and warmer, accelerating mosquito development, biting rates, and the incubation of the pathogens within their bodies. Female mosquitoes bite to acquire proteins for the development of their ovaries and eggs and, in the process, acquire pathogens and/or parasites from one vertebrate host and transmit them to another, usually after a short period of replication. Three of their four life stages are lived in still freshwater, so it is crucial to understand their range of action when they reach adulthood and leave the water, in order to plan and implement local prevention measures. A set of georeferenced abundance data collected in mainland Portugal over seven years was linked to cartographed water bodies in a geographic information system to estimate the distances at which Culex pipiens s.l. had a significant presence, with criteria based on the size of the catches. The result allows for an estimate of the fly range of those mosquitoes, which can be used to focus countermeasures.
文摘An aerial photographic coverage acquired on two consecutive days in October 2021 with a ground resolution of 20 cm and a spectral resolution of 4 bands (red, green, blue and near infrared), allowed to distinguish most of the classes of interest present in the intertidal zone of the Sado estuary. We explored the possibilities of thematic classification in the powerful and complex software ArcGIS Pro;we presented the methodology used in a detailed way that allows others with minimal knowledge of GIS to reproduce the classification process without having to decipher the specifics of the software. The classification implemented used ground truth from four classes related to the macro-occupations of the area. In a first phase we explore the standard algorithms with object-based capabilities, like K-Nearest Neighbor, Random Trees Forest and Support Vector Machine, and in a second phase we proceed to test three deep learning classifiers that provide semantic segmentation: a U-Net configuration, a Pyramid Scene Parsing Network and DeepLabV3. The resulting classifications were quantitatively evaluated with a set of 500 control points in a test area of 37,500 × 12,500 pixels, using confusion matrices and resorting to Cohen’s kappa statistic and the concept of global accuracy, achieving a Kappa in the range [0.72, 0.81] and a global accuracy between 88.9% and 92.9%;the option U-Net had the most interesting results. This work establishes a methodology to provide a baseline for assessing future changes in the distribution of Sado estuarine habitats, which can be replicated in other wetland ecosystems for conservation and management purposes.
文摘Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens s.l. collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters are evaluated. This work is one of the results of a long-term surveillance program of pernicious insects that act as vectors of various diseases;its focus is on the possibility of prevention that can be achieved with abundance data. The focus on Culex pipiens is justified by its abundance and its competence as a vector for numerous health issues. The cumulative distribution of monthly captures by each meteorological parameter allows to compute thresholds corresponding to mosquito massive presence related to 90% of the captures. Using the weather parameters measured in the network of weather stations across the country, a monthly average of each parameter of interest (temperature, humidity, etc.) is computed and an interpolation of the results is made to produce raster maps corresponding to each month. The previously obtained thresholds are applied to each map, producing spatial masks with the relevant zones for each parameter. The intersection of the various masks for each month shows the most densely populated area of Culex, and the ensemble allows us to observe the evolution of mosquito presence through the critical season, which is from May to October at these latitudes. In parallel, mosquito abundance data are related to physiographic parameters. The relative distribution of female mosquitoes across land cover types in each month allows identifying which classes and seasons are most relevant. Orthometric altitude related to the presence of 90% of the catches shows the limits reached by mosquitoes in each month. The results are applied to the previously obtained climate envelopes, delimiting critical areas where the level of risk of transmission of the pathogens for which Culex pipiens is a competent vector is high and countermeasures should be concentrated, allowing its planning, and targe
文摘This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden on the coast becomes a problem, both because erosion makes the cliffs unstable and because pollution increases, making the fragile dune ecosystem difficult to preserve. It is becoming necessary to increase the control of access to beaches, even if it is not a popular measure for internal and external tourism. The methodology described can also be used to monitor maritime borders. The use of images acquired in the infrared range guarantees active surveillance both day and night, the main objective being to mimic the infrared cameras already installed in some critical areas along the coastline. Using a series of infrared photographs taken at low angles with a modified camera and appropriate filter, a recent deep learning algorithm with the right training can simultaneously detect and count whole people at close range and people almost completely submerged in the water, including partially visible targets, achieving a performance with F1 score of 0.945, with 97% of targets correctly identified. This implementation is possible with ordinary laptop computers and could contribute to more frequent and more extensive coverage in beach/border surveillance, using infrared cameras at regular intervals. It can be partially automated to send alerts to the authorities and/or the nearest lifeguards, thus increasing monitoring without relying on human resources.
