KEYWORDS: Earth observing sensors, Landsat, Remote sensing, Data modeling, New and emerging technologies, System integration, Control systems, Infrared sensors, Thermal modeling, Visual analytics
The aim of this study was to analyze the LST on pasture areas with different systems of production and management based on survey with farmers and remote sensing data during four development cycles (2013-2017). The study was carried out on western Sao Paulo state, Brazil, which is known as its traditional pastureland areas. We analyzed different type of production system such as extensive, semi-extensive and intensive pasture. The band 10 from Landsat 8 Thermal Infrared Sensor (TIRS) was used to retrieve the LST, and to verify the inter-seasonal productivity variation in function of management and temperature we calculated Net Primary Production - NPP. By the survey and visual analysis, we could classify the pasture areas as degraded and non-degraded area. For this classification, only pasture in degradation or maintenance phase was identified. Degraded pasture in the first or second cycle was recovered after proper management. However, the inverse effect was also verified, areas in maintenance became degraded pasture. It occurred not only because of the management practices but also because of extreme meteorological conditions. For those considered degraded pasture we verified an average temperature of 27°C - 29°C, and areas with the proper management the average temperature where 24°C - 26°C. On farms which were verified lost of productivity in function of degradation the temperature raised around 2°C. For this study, the use of remote sensing data to retrieve Land Surface Temperature shows to be an additional tool for monitoring pasture areas in function of management and productivity.
Agriculture is one of the most important markets in the world. For the agriculture production efficiency and cost reduction, the modern agriculture no longer exists in farm fields only, but expands quickly in information fields as well. The recent trend of agriculture is moving towards precision farming, which gives rise to great demands for IT supports. The future of precision agriculture is considered highly promising, and lots of solution packages will be developed to support farming activities during the entire farming cycle.
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