Geoscience and Remote Sensing on Horticulture as Support for Management and Planning

The importance of horticulture around the large cities, called green belt (GB), or proximity food production area is related to its contribution to the provision of food as well as its role on social, cultural and ecological aspects. Geoscience and Remote sensing (GRS) are tools that should aid in gathering and updating the information to develop science-based management plans of this areas. Recently, the improvement in terms of spatial, temporal and radiometric resolutions has changed the performance and the approach to the horticulture remote sensing. In this work, we make a brief review on the literature exploring the use of GRS techniques in horticulture, and future trends in order to exploit the available techniques for efficient crop management in the way to improve territorial planning and management. Specifically we found a lack of academic production in this area. In addition we examine the importance of this landscape areas from different points of view (food security, health, ecology, etc.). A systematic revision of published studies on remote sensing on horticulture including different platforms, sensors and methodologies are briefly presented. Finally some aspect related with future trends are discussed.Fil: Marinelli, María Victoria. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Scavuzzo, Matías. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; ArgentinaFil: Giobellina, Beatriz. Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Cordoba. Estacion Experimental Agropecuaria Manfredi. Agencia de Extension Rural Cordoba.; ArgentinaFil: Scavuzzo, Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentin

Geoscience and remote sensing on horticulture as support for management and planning

The importance of horticulture around the large cities, called green belt (GB), or proximity food production area is related to its contribution to the provision of food as well as its role on social, cultural and ecological aspects. Geoscience and Remote sensing (GRS) are tools that should aid in gathering and updating the information to develop science-based management plans of this areas. Recently, the improvement in terms of spatial, temporal and radiometric resolutions has changed the performance and the approach to the horticulture remote sensing. In this work, we make a brief review on the literature exploring the use of GRS techniques in horticulture, and future trends in order to exploit the available techniques for efficient crop management in the way to improve territorial planning and management. Specifically we found a lack of academic production in this area. In addition we examine the importance of this landscape areas from different points of view (food security, health, ecology, etc.). A systematic revision of published studies on remote sensing on horticulture including different platforms, sensors and methodologies are briefly presented. Finally some aspect related with future trends are discussed.EEA ManfrediFil: Marinelli, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); ArgentinaFil: Marinelli, María Victoria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Agencia de Extensión Rural Córdoba; ArgentinaFil: Marinelli, María Victoria. Comisión Nacional de Actividades Espaciales (CONAE). Instituto de altos estudios espaciales "Mario Gulich"; ArgentinaFil: Marinelli, María Victoria. Universidad Nacional de Córdoba. Instituto de altos estudios espaciales "Mario Gulich"; ArgentinaFil: Scavuzzo, Carlos Matías. Universidad Nacional de Córdoba Facultad de Ciencias Médicas. Escuela de Nutrición; ArgentinaFil: Giobellina, Beatriz Liliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Observatorio de Agricultura Urbana, Periurbana y Agroecología (O-AUPA); ArgentinaFil: Scavuzzo, Carlos Marcelo. Comisión Nacional de Actividades Espaciales (CONAE); Argentin

Geomatic tools for water management in a community irrigation system, Cruz del Eje, Córdoba

An integral and efficient management of water for irrigation requires the adoption of new technologies to respond to the challenges imposed by the agricultural sector, in particular to stabilize production through the adequate use of water resources. In this sense, it is vital to characterize and know the amount of area which is under irrigation in such agricultural systems. In this paper we show the use of satellite information data in a GIS environment with the objective of characterizing the productive areas under irrigation in Cruz del Eje, Córdoba, Argentina in 3 types: A) irrigation region B) irrigable area and C) actually irrigated area. Multitemporal image indices and segmentation were used for this characterization and then maps of these 3 types of agricultural land cover were generated. Additionally, we present simple satellite images processing and classification procedures to increase the knowledge about the land cover over this irrigated area. Finally, we discuss how this geographically explicit information generated could be useful for the decision-making process on current irrigated areas and on the potential of productive systems through community irrigation systems.Fil: Marinelli, María Victoria. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mari, Nicolás. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentin

A new Approach to Segmentation of Remote Sensing Images with Hidden Markov Models

In this work, we present a new segmentation algorithm for remote sensing images based on two-dimensional Hidden Markov Models (2D-HMM). In contrast to most 2D-HMM approaches, we do not use Viterbi Training, instead we propose to propagate the state probabilities through the image. Therefore, we denote our algorithm Complete Enumeration Propagation (CEP). To evaluate the performance of CEP, we compare it to the standard 2D-HMM approach called Path Constrained Viterbi Training (PCVT). As both algorithms are not restricted to a certain emission probability, we evaluate the performance of seven probability functions, namely Gamma, Generalized Extreme Value, inverse Gaussian, Logistic, Nakagami, Normal and Weibull. The experimental results show that our approach outperforms PCVT and other benchmark algorithms. Furthermore, we show that the choice of the probability distribution is crucial for many segmentation tasks.http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6868456Fil: Baumgartner, Josef. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Investigación Matemática Aplicada a Control; Argentina.Fil: Scavuzzo, Marcelo. Comision Nacional de Actividades Espaciales; Argentina.Fil: Rodriguez Rivero, Cristian. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Investigación Matemática Aplicada a Control; Argentina.Fil: Pucheta, Julián. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Investigación Matemática Aplicada a Control; Argentina.Sistemas de Automatización y Contro

Interaction between spatial and temporal scales for entomological field data: Analysis of Aedes Aegypti oviposition series

Background In Argentina, Aedes aegypti represents an important public health threat, since it is the vector responsible for the transmission of dengue, chikungunya, zika and yellow fever. Mundo Sano Foundation has been carrying out periodic surveys of immature vector stages in several cities of northern Argentina. The main tool to mitigate their spread is through vector control. The identification of vector "hot spots" is an important key to design preventive program tools. Geostatistical techniques such as spatial autocorrelation (SAC) and kriging interpolation can be used to predict vector abundance in unsampled areas using data obtained from monitored sites. The knowledge of the spatial autocorrelation of vector abundance is fundamental and it can also be used to design disease surveillance strategies: To determine the characteristics of chemical control; to select ovitrap placement (distance between samples); and to determine the optimum sample size, among others. It is important to analyze the effect of the variation of the scale in the observed phenomenon. Methods This paper analyzes a two years series of weekly oviposition data from 25 ovitraps distributed in the urban area of a small city (104 measurements were collected for each ovitrap). We aim to understand how the relationship between sites measurements varies considering its relative location in the city, for different temporal sampling frequency or temporal resolution (TR). Different similarity measures between curves and graphic representations of these relationships, are explored. Among these, an innovative use of polar graphs -a tool commonly used to detect changes in satellite images- is examined. We evaluate variograms and SAC for multitemporal data (oviposition curves) at each TR. Results Similarity between curves does not show spatial continuity in relation to the spatial arrangement of ovitraps, may be due to the effect of processes that are only observable at the microhabitat scale or due to sociodemographic factors. As the temporal resolution is greater in a given area, a greater number of ovitraps are needed to capture the spatial heterogeneity of the abundance of the vector. At the maximum TR analyzed, the minimum distance of spatial correlations was set at 1000 m. This has implications on the quantity of ovitraps per area unit required in the field in order to obtain a good description of the population dynamics of Ae. aegypti at the peridomestic level. Conclusion The results would indicate that when varying the time scale of analysis, the spatial scale should be modified accordingly to adapt to the new data structure. The ability to predict ecological phenomena depends on the relationships between spatial and temporal scales. The approach and innovative statistical tools described in this study, based on empirical data from a field study, may be used by different Ae. aegypti monitoring and control programs in order to design and implement tailor-made interventions. It would allows to support not only the selection of field samples, and to obtain data interpolation parameters, but also to contribute to the development of vector abundance models.Fil: Lanfri, Sofía. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Espinosa, Manuel. Fundación Mundo Sano; ArgentinaFil: Lanfri, Mario. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Periago, Maria Victoria. Fundación Mundo Sano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Abril, Marcelo. Fundación Mundo Sano; ArgentinaFil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentin

Operational satellite-based temporal modelling of Aedes population in Argentina

Aedes aegypti is a vector for Chikungunya, Dengue and Zika viruses in Latin America and is therefore a large public health problem for the region. For this reason, several inter-institutional and multidisciplinary efforts have been made to support vector control actions through the use of geospatial technologies. This study presents the development of an operational system for the application of free access to remotely sensed products capable of assessing the oviposition activity of Ae. aegypti in all of Argentina?s northern region with the specific aim to improve the current Argentine National Dengue risk system. Temporal modelling implemented includes remotely sensed variables like the normalized difference vegetation index, the normalized difference water index, day and night land surface temperature and precipitation data available from NASA?s tropical rainfall measuring mission and global precipitation measurement. As a training data set, four years of weekly mosquito oviposition data from four different cities in Argentina were used. A series of satellite-generated variables was built, downloading and resampling the these products both spatially and temporally. From an initial set of 41 variables chosen based on the correlation between these products and the oviposition series, a subset of 11 variables were preserved to develop temporal forecasting models of oviposition using a lineal multivariate method in the four cities. Subsequently, a general model was generated using data from the cities. Finally, in order to obtain a model that could be broadly used, an extrapolation method using the concept of environmental distance was developed. Although the system was oriented towards the surveillance of dengue fever, the methodology could also be applied to other relevant vector-borne diseases as well as other geographical regions in Latin America.Fil: Espinosa, Manuel. Fundación Mundo Sano; ArgentinaFil: Di Fino, Eliana Marina Alvarez. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Abril, Marcelo. Fundación Mundo Sano; ArgentinaFil: Lanfri, Mario. Centro Espacial Teófilo Tabanera; ArgentinaFil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; ArgentinaFil: Scavuzzo, Carlos Marcelo. Centro Espacial Teófilo Tabanera; Argentin

Explorando o uso de ferramentas de sensoriamento remoto e tecnologias geoespaciais aplicadas ao problema multidimensional da segurança alimentar

[Objetivo] El objetivo de este estudio fue analizar qué papel pueden jugar las tecnologías de teledetección para estudiar los factores multidimensionales que influyen en la seguridad alimentaria y nutricional (SAN), en Córdoba Argentina. [Metodología] El área de estudio comprende la ciudad de Córdoba, Argentina. Se obtuvieron datos epidemiológicos de la prevalencia de bajo peso, sobrepeso y obesidad (malnutrición) durante el 2013 de 23 centros de atención primaria de la ciudad. Se exploraron las condiciones ambientales de los centros en un radio de 1000 m. Se clasificaron imágenes SPOT 5, se utilizaron características espectrales y espaciales y se evidencia cómo una clasificación no supervisada puede dar información para describir la dimensión social y el acceso económico a los alimentos. Se realizó una regresión lineal multivariante para examinar la relación entre la prevalencia de malnutrición y las variables ambientales y espaciales, derivadas de las imágenes SPOT. [Resultados] Los resultados de la clasificación no supervisada de imágenes muestran la diferencia en el patrón espectral-espacial de los barrios, evidencian cómo una simple clasificación de imágenes de satélite puede convertirse en una herramienta de discriminación útil. Se obtienen análisis de regresión múltiple con R2 ajustados de 0,70 y 0,6435 respectivamente para desnutrición, y sobrepeso y obesidad. A partir de los modelos obtenidos, se construyen mapas continuos de prevalencia. [Conclusiones] El método propuesto en este trabajo puede discriminar socialmente diferentes áreas relacionadas con la SAN. Es innovador y necesario aprovechar las herramientas de teledetección y las tecnologías geoespaciales, en nuestra región, aplicadas a la SAN.The aim of this study was to analyze which role remote sensing technologies can play to study multidimensional factors influencing the Food and Nutrition Security (FNS), in Córdoba Argentina. The study area includes the city of Córdoba, Argentina. Epidemiological data on the prevalence of underweight, overweight, and obesity (malnutrition) in 2013 were obtained from 23 primary health care centers in the city. The environmental conditions of the surroundings of the health centers were explored within a radius of 1000m. SPOT 5 images were classified using spectral and spatial features and we show how a non-supervised classification can give information to describe the social dimension and economic access to food. In addition, a multivariate stepwise linear regression was performed to examine the relation between the prevalence of malnutrition and the environmental and spatial variables, derived from the SPOT image, proposed. The results of the unsupervised image classification show the difference in the spectral-spatial pattern of neighborhoods showing how a simple satellite image classification can become a useful discrimination tool. Multiple regression analyses with adjusted R2 of 0.70 and 0.6435 respectively are obtained for undernutrition, and overweight, and obesity. On the basis of the obtained models, continuous maps of prevalence are built. [Conclusions] The method proposed in this work can discriminate socially different areas related to FNS. It is innovative and necessary to take advantage of remote sensing tools and geospatial technologies, in our region, applied to FNS.[Objetivo] O objetivo deste estudo foi analisar o papel que as tecnologias de sensoriamento remoto podem desempenhar no estudo dos fatores multidimensionais que influenciam a segurança alimentar e nutricional (SAN) em Córdoba, Argentina. [Metodologia] A área de estudo compreende a cidade de Córdoba, Argentina. Dados epidemiológicos sobre a prevalência de baixo peso, sobrepeso e obesidade (desnutrição) durante 2013 foram obtidos de 23 centros de atenção primária à saúde da cidade. As condições ambientais dos locais foram exploradas dentro de um raio de 1000 m. As imagens do SPOT 5 foram classificadas e as características espectrais e espaciais utilizadas, e o que se mostra é como uma classificação sem supervisão pode fornecer informações para descrever a dimensão social e o acesso econômico aos alimentos. A regressão linear multivariada foi realizada para examinar a relação entre a prevalência da desnutrição e as variáveis ambientais e espaciais derivadas das imagens de SPOT. [Resultados] Os resultados da classificação da imagem não supervisionada mostram a diferença no padrão espectralespacial dos bairros, evidenciando como uma simples classificação da imagem de satélite pode se tornar uma ferramenta útil de discriminação. São obtidas as análises de regressão múltipla com R2 ajustado de 0,70 e 0,6435 respectivamente para desnutrição, sobrepeso e obesidade. Os mapas de prevalência contínua são construídos a partir dos modelos obtidos. [Conclusões] O método proposto neste trabalho pode discriminar socialmente diferentes áreas relacionadas à SAN. É inovador e necessário tirar proveito de ferramentas de sensoriamento remoto e tecnologias geoespaciais, em nossa região, aplicadas à SAN.Fil: Alvarez Di Fino, Eliana Marina. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Campero, Micaela Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Scavuzzo, Carlos Marcelo. Universidad Nacional de Córdoba; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Defagó, María Daniela. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; Argentin

Spatial patterns of high Aedes Aegypti oviposition activity in northwestern Argentina

Background: In Argentina, dengue has affected mainly the Northern provinces, including Salta. The objective of this study was to analyze the spatial patterns of high Aedes aegypti oviposition activity in San Ramo´n de la Nueva Ora´n, northwestern Argentina. The location of clusters as hot spot areas should help control programs to identify priority areas and allocate their resources more effectively. Methodology: Oviposition activity was detected in Ora´n City (Salta province) using ovitraps, weekly replaced (October 2005–2007). Spatial autocorrelation was measured with Moran’s Index and depicted through cluster maps to identify hot spots. Total egg numbers were spatially interpolated and a classified map with Ae. aegypti high oviposition activity areas was performed. Potential breeding and resting (PBR) sites were geo-referenced. A logistic regression analysis of interpolated egg numbers and PBR location was performed to generate a predictive mapping of mosquito oviposition activity. Principal Findings: Both cluster maps and predictive map were consistent, identifying in central and southern areas of the city high Ae. aegypti oviposition activity. A logistic regression model was successfully developed to predict Ae. aegypti oviposition activity based on distance to PBR sites, with tire dumps having the strongest association with mosquito oviposition activity. A predictive map reflecting probability of oviposition activity was produced. The predictive map delimitated an area of maximum probability of Ae. aegypti oviposition activity in the south of Ora´n city where tire dumps predominate. The overall fit of the model was acceptable (ROC = 0.77), obtaining 99% of sensitivity and 75.29% of specificity. Conclusions: Distance to tire dumps is inversely associated with high mosquito activity, allowing us to identify hot spots. These methodologies are useful for prevention, surveillance, and control of tropical vector borne diseases and might assist National Health Ministry to focus resources more effectively.Fil: Estallo, Elizabet Lilia. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Más, Guillermo. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Vergara Cid, Carolina. Universidad Nacional de Cordoba. Facultad de Medicina. Instituto de Virologia "Dr. J.M. Vanella". Laboratorio de Arbovirus; ArgentinaFil: Lanfri, Mario Alberto. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Ludueña Almeida, Francisco. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Introini, María Virginia. Ministerio de Salud de la Nación; ArgentinaFil: Zaidenberg, Mario. Ministerio de Salud de la Nación; ArgentinaFil: Almiron, Walter Ricardo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentin

Geomática aplicada a un sistema de alerta temprana

En el presente trabajo se plantea una Infraestructura Informática para dar soporte a la prevención y el control estratégico del vector del dengue en Argentina por parte del Ministerio de Salud de la Nación. La misma es parte de un complejo Sistema de Alerta Temprana (SAT) y es llevado a cabo por la Comisión Nacional de Actividades Espaciales (CONAE) bajo los estándares de la European Spatial Agency (ESA). La arquitectura, diseño, metodología y codificación pretenden ser componentes re-utilizables en cualquier infraestructura informática de soporte a SATs. En su desarrollo se utiliza Open Source Software (OSS) y Patrones de Diseño (Design Patterns) garantizando una herramienta tecnológica además de re-utilizable, flexible, mantenible y robusta. En este documento se describen los requerimientos establecidos por el Ministerio de Salud de la Nación y se plantea la arquitectura y diseño del sistema a partir de los mismos. Además, se realiza un análisis de las tecnologías OSS integradas en el desarrollo y la codificación. Finalmente se describe la funcionalidad obtenida y se muestra la infraestructura con un caso en particular.Sociedad Argentina de Informática e Investigación Operativ