What are the best practices for using remote sensing data in precision agriculture?
Remote sensing is a powerful tool for precision agriculture, which aims to optimize crop production and resource efficiency by monitoring and managing spatial variability within fields. Remote sensing data can provide valuable information on crop health, soil moisture, nutrient status, pest and disease infestation, and yield potential. However, to use remote sensing data effectively, you need to follow some best practices that ensure data quality, accuracy, and relevance for your specific goals and context. In this article, we will discuss six best practices for using remote sensing data in precision agriculture.
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Suresh YerolkarPeople First | Creating Abundance | Quality Matters | CSM? | 15x Community Top Voice | QA Engineering | Quality…
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Darío Alejandro ávila Brice?oLatam Sales Account Executive at Planet | Geocientífico | Imágenes satelitales | GIS | Agtech
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Sirapoom PeanusahaPhD Candidate in Biosystems Engineering | Precision Agriculture & Remote Sensing | Data Scientist | Postdoc & Data…