Thesis Diseño e implementación de un sistema de recolección y procesamiento de imágenes satelitales para la agricultura
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Date
2024-03
Authors
Journal Title
Journal ISSN
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Program
DEPARTAMENTO DE INFORMÁTICA. INGENIERÍA CIVIL INFORMÁTICA
Campus
Campus Casa Central Valparaíso
Abstract
Las técnicas tradicionales de percepción remota en la agricultura como imágenes fotográficas en tierra y el uso de aviones o de vuelos no tripulados, suelen entregar resultados de buena calidad, pero con un gran costo tanto monetario como de tiempo, además de no realizar una entrega continua. Para abordar este problema se propone la creación de un sistema automático de recolección y procesamiento de imágenes satelitales para ayudar a la toma de decisiones en la agricultura. Este sistema, es capaz de automáticamente generar imágenes tanto de índices de vegetación como de color real y estimar la evapotranspiración potencial en una área geográfica, a partir de una arquitectura de micro-servicios y en un ambiente en la nube por lo que resulta altamente escalable y garantiza una entrega continua.
Traditional remote sensing techniques in agriculture, such as ground-based photographic imagery and the use of aircraft or UAVs, usually deliver good quality results but at great cost, both in terms of money and time. Additionally, they do not provide continuous delivery. To address this problem, we propose the creation of an automatic system for collecting and processing satellite imagery to aid decision-making in the agriculture industry. This system is fully capable of automatically generating images of both vegetation indices and true color, as well as estimating the potential evapotranspiration in a geographic area. It is built based on a micro-services architecture and in a cloud environment, making it highly scalable and ensuring continuous delivery.
Traditional remote sensing techniques in agriculture, such as ground-based photographic imagery and the use of aircraft or UAVs, usually deliver good quality results but at great cost, both in terms of money and time. Additionally, they do not provide continuous delivery. To address this problem, we propose the creation of an automatic system for collecting and processing satellite imagery to aid decision-making in the agriculture industry. This system is fully capable of automatically generating images of both vegetation indices and true color, as well as estimating the potential evapotranspiration in a geographic area. It is built based on a micro-services architecture and in a cloud environment, making it highly scalable and ensuring continuous delivery.
Description
Keywords
Percepción remota, Imágenes satelitales, Agricultura, Computación en la nube