Evaluation of classification algorithms in the Google Earth Engine platform for the identification and change detection of rural and periurban buildings from very high-resolution images

[EN] Building change detection based on remote sensing imagery is a key task for land management and planning e.g., detection of illegal settlements, updating land records and disaster response. Under the post- classification comparison approach, this research aimed to evaluate the feasibility of several classification algorithms to identify and capture buildings and their change between two time steps using very-high resolution images (<1 m/pixel) across rural areas and urban/rural perimeter boundaries. Through an App implemented on the Google Earth Engine (GEE) platform, we selected two study areas in Colombia with different images and input data. In total, eight traditional classification algorithms, three unsupervised (K-means, X-Means y Cascade K-Means) and five supervised (Random Forest, Support Vector Machine, Naive Bayes, GMO maximum Entropy and Minimum distance) available at GEE were trained. Additionally, a deep neural network named Feature Pyramid Networks (FPN) was added and trained using a pre-trained model, EfficientNetB3 model. Three evaluation zones per study area were proposed to quantify the performance of the algorithms through the Intersection over Union (IoU) metric. This metric, with a range between 0 and 1, represents the degree of overlapping between two regions, where the higher agreement the higher IoU values. The results indicate that the models configured with the FPN network have the best performance followed by the traditional supervised algorithms. The performance differences were specific to the study area. For the rural area, the best FPN configuration obtained an IoU averaged for both time steps of 0.4, being this four times higher than the best supervised model, Support Vector Machines using a linear kernel with an average IoU of 0.1. Regarding the setting of urban/rural perimeter boundaries, this difference was less marked, having an average IoU of 0.53 in comparison to 0.38 obtained by the best supervised classification model, in this case Random Forest. The results are relevant for institutions tracking the dynamics of building areas from cloud computing platfo future assessments of classifiers in likewise platforms in other contexts.[ES] La detección de cambios de áreas construidas basada en datos de teledetección es una importante herramienta para el ordenamiento y la administración del territorio p.e.: la identificación de construcciones ilegales, la actualización de registros catastrales y la atención de desastres. Bajo el enfoque de comparación post-clasificación, la presente investigación tuvo como objetivo evaluar la funcionalidad de varios algoritmos de clasificación para identificar y capturar las construcciones y su cambio entre dos fechas de análisis usando imágenes de alta resolución (<1 m/píxel) en ámbitos rurales y límites del perímetro urbano municipal. La anterior evaluación fue llevada a cabo a través de una aplicación desarrollada mediante la plataforma Google Earth Engine (GEE), donde se alojaron y analizaron diferentes imágenes y datos de entrada sobre dos áreas de estudio en Colombia. En total, ocho algoritmos de clasificación tradicional, tres no supervisados (K-means, X-Means y Cascade K-Means) y cinco supervisados (Random Forest, Support Vector Machine, Naive Bayes, GMO maximum Entropy y Minimum distance) fueron entrenados empleando GEE. Adicionalmente, se entrenó una red neuronal profunda denominada Feature Pyramid Networks (FPN) sobre la cual se aplicó la estrategia de modelos preentrenados, usando pesos del modelo EfficientNetB3. Por cada una de las dos áreas de estudio, tres zonas de evaluación fueron propuestas para cuantificar la funcionalidad de los algoritmos mediante la métrica Intersection over Union (IoU). Esta métrica representa la evaluación de la superposición de dos regiones y tiene un rango de valores de 0 a 1, donde a mayor coincidencia de las imágenes mayor es el valor de IoU. Los resultados indican que los modelos configurados con la red FPN tienen la mejor funcionalidad, seguido de los algoritmos tradicionales supervisados. Las diferencias de la funcionalidad fueron específicas por área de estudio. Para el ámbito rural, la mejor configuración de FPN obtuvo un IoU promedio entre ambas fechas de 0,4, es decir, cuatro veces el mejor modelo supervisado, correspondiente al Support Vector Machine de kernel Lineal con un IoU de 0,1. Respecto al área de límites del perímetro urbano municipal, esta diferencia fue menos marcada, con un IoU promedio de 0,53 en comparación con el 0,38 derivado del mejor modelo de clasificación supervisada, que en este caso fue Random Forest. Los resultados de esta investigación son relevantes para entidades responsables del seguimiento de las dinámicas de las áreas construidas a partir de plataformas de procesamiento en la nube como GEE, estableciendo una línea base para futuros estudios evaluando la funcionalidad de los clasificadores disponibles en otros contextos.Los autores agradecen a las Subdirecciones de Catastro, y Geografía y Cartografía del IGAC. Esta investigación hace parte de la licencia del programa GEO-GEE administrada por la Subdirección de Geografía y Cartografía. Se agradece igualmente al equipo de EODataScience por su soporte constante en los desarrollos técnicos de esta investigación.Coca-Castro, A.; Zaraza-Aguilera, MA.; Benavides-Miranda, YT.; Montilla-Montilla, YM.; Posada-Fandiño, HB.; Avendaño-Gomez, AL.; Hernández-Hamon, HA.... (2021). Evaluación de algoritmos de clasificación en la plataforma Google Earth Engine para la identificación y detección de cambios de construcciones rurales y periurbanas a partir de imágenes de alta resolución. Revista de Teledetección. 0(58):71-88. http://hdl.handle.net/10251/169765OJS718805

Central nervous system involvement in systemic lupus erythematosus: data from the Spanish Society of Rheumatology Lupus Register (RELESSER)

Objectives: To analyze the prevalence, incidence, survival and contribution on mortality of major central nervous system (CNS) involvement in systemic lupus erythematosus (SLE). Methods: Patients fulfilling the SLE 1997 ACR classification criteria from the multicentre, retrospective RELESSER-TRANS (Spanish Society of Rheumatology Lupus Register) were included. Prevalence, incidence and survival rates of major CNS neuropsychiatric (NP)-SLE as a group and the individual NP manifestations cere-brovascular disease (CVD), seizure, psychosis, organic brain syndrome and transverse myelitis were calculated. Furthermore, the contribution of these manifestations on mortality was analysed in Cox regression models adjusted for confounders. Results: A total of 3591 SLE patients were included. Of them, 412 (11.5%) developed a total of 522 major CNS NP-SLE manifestations. 61 patients (12%) with major CNS NP-SLE died. The annual mortality rate for patients with and without ever major CNS NP-SLE was 10.8% vs 3.8%, respectively. Individually, CVD (14%) and organic brain syndrome (15.5%) showed the highest mortality rates. The 10% mortality rate for patients with and without ever major CNS NP-SLE was reached after 12.3 vs 22.8 years, respectively. CVD (9.8 years) and organic brain syndrome (7.1 years) reached the 10% mortality rate earlier than other major CNS NP-SLE manifestations. Major CNS NP-SLE (HR 1.85, 1.29-2.67) and more specifically CVD (HR 2.17, 1.41-3.33) and organic brain syndrome (HR 2.11, 1.19-3.74) accounted as independent prognostic factors for poor survival. Conclusion: The presentation of major CNS NP-SLE during the disease course contributes to a higher mortality, which may differ depending on the individual NP manifestation. CVD and organic brain syndrome are associated with the highest mortality rates.Pathophysiology and treatment of rheumatic disease

Pure Membranous Lupus Nephritis: Description of a Cohort of 150 Patients and Review of the Literature

Objectives The course and long-term outcome of pure membranous lupus nephritis (MLN) are little understood. The aims of this study are to evaluate the clinical features, course, outcome and prognostic indicators in pure MLN and to determine the impact of ethnicity and the type of health insurance on the course and prognosis of pure MLN. Methods We conducted a retrospective review of medical records of 150 patients with pure MLN from Spain and the USA. Results Mean age was 34.2±12.5 and 80% were women. Sixty-eight percent of patients had nephrotic syndrome at diagnosis. The average serum creatinine was 0.98±0.78mg/dl. Six percent of patients died and 5.3% developed end-stage renal disease (ESRD). ESRD was predicted by male sex, hypertension, dyslipidemia, high basal 24h-proteinuria, high basal serum creatinine and a low basal creatinine clearance. Age, cardiac insufficiency, peripheral artheriopathy, hemodialysis and not having received mycophenolate mofetil or antimalarials for MLN predicted death. Conclusions Pure MLN frequently presents with nephrotic syndrome, high proteinuria and normal serum creatinine. Its prognosis is favourable in maintaining renal function although proteinuria usually persists over time. Baseline cardiovascular disease and not having a health insurance are related with poor prognosis

Seguimiento de las guías españolas para el manejo del asma por el médico de atención primaria: un estudio observacional ambispectivo

Objetivo Evaluar el grado de seguimiento de las recomendaciones de las versiones de la Guía española para el manejo del asma (GEMA 2009 y 2015) y su repercusión en el control de la enfermedad. Material y métodos Estudio observacional y ambispectivo realizado entre septiembre del 2015 y abril del 2016, en el que participaron 314 médicos de atención primaria y 2.864 pacientes. Resultados Utilizando datos retrospectivos, 81 de los 314 médicos (25, 8% [IC del 95%, 21, 3 a 30, 9]) comunicaron seguir las recomendaciones de la GEMA 2009. Al inicio del estudio, 88 de los 314 médicos (28, 0% [IC del 95%, 23, 4 a 33, 2]) seguían las recomendaciones de la GEMA 2015. El tener un asma mal controlada (OR 0, 19, IC del 95%, 0, 13 a 0, 28) y presentar un asma persistente grave al inicio del estudio (OR 0, 20, IC del 95%, 0, 12 a 0, 34) se asociaron negativamente con tener un asma bien controlada al final del seguimiento. Por el contrario, el seguimiento de las recomendaciones de la GEMA 2015 se asoció de manera positiva con una mayor posibilidad de que el paciente tuviera un asma bien controlada al final del periodo de seguimiento (OR 1, 70, IC del 95%, 1, 40 a 2, 06). Conclusiones El escaso seguimiento de las guías clínicas para el manejo del asma constituye un problema común entre los médicos de atención primaria. Un seguimiento de estas guías se asocia con un control mejor del asma. Existe la necesidad de actuaciones que puedan mejorar el seguimiento por parte de los médicos de atención primaria de las guías para el manejo del asma. Objective: To assess the degree of compliance with the recommendations of the 2009 and 2015 versions of the Spanish guidelines for managing asthma (Guía Española para el Manejo del Asma [GEMA]) and the effect of this compliance on controlling the disease. Material and methods: We conducted an observational ambispective study between September 2015 and April 2016 in which 314 primary care physicians and 2864 patients participated. Results: Using retrospective data, we found that 81 of the 314 physicians (25.8%; 95% CI 21.3–30.9) stated that they complied with the GEMA2009 recommendations. At the start of the study, 88 of the 314 physicians (28.0%; 95% CI 23.4–33.2) complied with the GEMA2015 recommendations. Poorly controlled asthma (OR, 0.19; 95% CI 0.13–0.28) and persistent severe asthma at the start of the study (OR, 0.20; 95% CI 0.12–0.34) were negatively associated with having well-controlled asthma by the end of the follow-up. In contrast, compliance with the GEMA2015 recommendations was positively associated with a greater likelihood that the patient would have well-controlled asthma by the end of the follow-up (OR, 1.70; 95% CI 1.40–2.06). Conclusions: Low compliance with the clinical guidelines for managing asthma is a common problem among primary care physicians. Compliance with these guidelines is associated with better asthma control. Actions need to be taken to improve primary care physician compliance with the asthma management guidelines

Describing basketball scores using probability distributions

This thesis presents a study on the 1997-2001 Philippine Basketball Association scores. Each of the scores can be presented by its ending and point spread. This paper aims to formulate a gambling strategy for betting in ending using the given data as a model. With the aid of software, distributions will be fitted on the 1997-2001 data and will be interpreted. Results showed that the endings of the 1997-2001 PBA scores are uniformly distributed. For the point spread, an empirical distribution based on the relative frequencies of the point spread of the 1997-2001 PBA scores were devised, since it was proven that the data can be used as a model to predict future outcomes. Using ending and the concept of maturity of chances, the endings (4,5), (5,1) and (7, 8) are deemed favorable. On the other hand, based on point spread and the concept of immaturity of chances, the endings corresponding to a point spread of 6 are deemed favorable. These endings are: (0,4), (1, 5), (2, 6), (3, 7), (4, 8), (5, 9), (6,0), (7, 1), (8, 2) and (9, 3)

An Animation- Versus Text-Based Computer-Tailored Game Intervention to Prevent Alcohol Consumption and Binge Drinking in Adolescents: Study Protocol

The purpose of this paper is to describe the protocol for the design, implementation, and evaluation of an animation- versus text-based computer tailoring game intervention aimed at preventing alcohol consumption and binge drinking (BD) in adolescents. A cluster-randomized controlled trial (CRCT) is carried out in students aged 14–19 enrolled in 24 high schools from Andalusia (Spain), which are randomized either to experimental (EC-1, EC-2) or waiting-list control conditions (CC). EC-1 receives an online intervention (Alerta Alcohol) with personalized health advice, using textual feedback and several gamification techniques. EC-2 receives an improved version (Alerta Alcohol 2.0) using animated videos and new gamification strategies. Both programs consist of nine sessions (seven taking place at high school and two at home): session 1 or baseline, sessions 2 and 3 that provide tailored advice based on the I-Change Model; sessions 4, 5, 7, and 8 are booster sessions, and sessions 6 and 9 are follow-up questionnaires at six and twelve months. The CC completes the baseline and the evaluation questionnaires. The primary outcome is BD within 30 days before post-test evaluations, and as secondary outcomes we assess other patterns of alcohol use. The findings should help the development of future alcohol drinking prevention interventions in adolescents