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Potential utilization of satellite remote sensing for field-based agricultural studies

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SPRINGER
DOI: 10.1186/s40538-021-00253-4

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Satellite remote-sensing; Drought stress; Land-use map; Evapotranspiration; Deforestation; PALSAR

资金

  1. [3710473400-1]

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Using satellite remote-sensing in agriculture is valuable for monitoring plant and soil conditions and providing decision-making support to farmers. However, beginners may struggle to select the most suitable tool or index due to challenges such as terminology specificity, sensor differences, interpretation of imaginary data, and multidisciplinary topics. This work aims to provide basic knowledge and advancements in utilizing remote-sensing for agricultural purposes.
Using satellite remote-sensing is a useful approach for agriculture to monitor plant and soil conditions and provide decision-making support to farmers. Recently, several types of tools and indices by the satellite remote-sensing have been developed for monitoring drought stress, changes in land uses, and crop-soil water relations. Although these techniques are powerful tools, especially in developing countries and regions where precise data of crop evaluation and yield statistics are not accessible, it is quite difficult for beginners to select the most suitable tool or index for their objectives. Major difficulties are in the specificity of the terminology, differences among the sensors (e.g., active vs. passive sensors), interpretation of imaginary data, and multidisciplinary topics. This work offers non-expert readers basic knowledge of remote-sensing use in agriculture, presenting advancements in the field and future insights. We review different sensors that are frequently used, such as optical sensors and synthetic aperture radar, as well as the following different purposes for using remote-sensing in agriculture: drought stress detection, monitoring land use in tropical regions (e.g., deforestation), and estimating water balance evapotranspiration in emerging and developing countries. Additionally, the integrated approach of remote-sensing data into the crop simulation model, which can provide a more holistic view of the plant and field status over cropping season, is described for the field-based studies.

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