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Desafíos, perspectivas y horizontes de la integración en América Latina y el Caribe.-- ( Becas de investigación [recurso electrónico] ): actualidad del pensamiento de Ruy Mauro Marini

Autores/as: Maribel Aponte Garcia ; Diego Martín Giller ; Martha Moncada Paredes ; Yasmín Rada Aragol ; Juan Cristóbal Cárdenas Castro

978-9-87722-330-9 (en línea)

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Institución detectada	Año de publicación	Navegá	Descargá	Solicitá
No requiere	2017	JSTOR

Cobertura temática: Ciencia política

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Desagregación de datos de microondas pasivas y activas para la estimación de humedad superficial del suelo en áreas de llanura de la región Pampeana

Autores/as: Gabriel Agustín García ; Virginia Venturini ; Héctor Del Valle ; Walter Sione ; Marcelo Scavuzzo ; Marc Thibeault ; Leticia Rodríguez

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Institución detectada	Año de publicación	Navegá	Descargá	Solicitá
No requiere	2018	Biblioteca Virtual de la Universidad Nacional del Litoral (SNRD)

Cobertura temática: Ciencias de la computación e información

Resumen disponible

Soil moisture (SM) is a state variable that influences the redistribution of water within the hydrological cycle. For decades, its estimation has been studied on a regional scale to solve hydrological, meteorological, agronomic and climatological problems. In this sense, remote sensing provides instantaneously observations of this variable on a large scale. Microwaves have allowed the development of different methodologies to obtain SM maps taking advantage of the complementary information provided by both active and passive microwave sensors. In this context, the thesis objective is to develop a procedure to estimate SM under moderate vegetation cover in plain areas, introducing the disaggregation of passive microwave information, radar and hydro-meteorological variables in the water balance. For this, two study areas were selected and a model was developed based on the water balance equation that represents the processes that influence in SM variability. The model takes into account water input and output processes of the soil system, and represents them with different hydro-environmental variables and radar data. For the resolution of the balance equation, multiple linear regression and multilayer perceptron statistical methodologies were selected. The resulting models were obtained with precipitation, air temperature and relative humidity observations and with radar data from the Sentinel-1 satellite mission. Based on the partial results obtained, the same methodologies and assumptions were applied to disaggregate SM SMAP product.

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