Abstract
Precision Agriculture (PA) offers a sustainable management solution to meet the increasingly high demand for food and fiber while keeping the environment safe.
Crop management (from sowing to harvesting) is an important component of the agricultural value chain and needs apt decisions by the farmers. This whole process is dynamic in nature and geospatial technologies assist in identifying the dynamics such as variabilities in soil, weather, water, and crop performance. Such technologies in combination with IoT guide farmers not only to identify these yield-limiting factors but also to provide support in making optimal decisions. This chapter describes a state-of-the-art conceptual system of PA while presenting practical examples of using geospatial technologies for PA. The development in the field of remote sensing and GIS has enabled us to acquire field-scale data and convert that information into knowledge. Now the farmers and extension workers can be enabled to acquire that knowledge without the need of running complex algorithms and acquire data as that is done through big data analytics in a cloud environment. When it comes to using digital technologies, agricultural stakeholders prefer using drones, GPS, and satellite-based remote sensing data. However, for large-scale adoption of PA-enabling technologies, we need to reduce the cost of such technologies (through government support or cooperative farming) and improve the infrastructure, especially network connectivity. We conclude that using geospatial technologies in combination with IoT and cloud computing not only enhances a paddock’s productivity but also contributes to environmental sustainability.
Crop management (from sowing to harvesting) is an important component of the agricultural value chain and needs apt decisions by the farmers. This whole process is dynamic in nature and geospatial technologies assist in identifying the dynamics such as variabilities in soil, weather, water, and crop performance. Such technologies in combination with IoT guide farmers not only to identify these yield-limiting factors but also to provide support in making optimal decisions. This chapter describes a state-of-the-art conceptual system of PA while presenting practical examples of using geospatial technologies for PA. The development in the field of remote sensing and GIS has enabled us to acquire field-scale data and convert that information into knowledge. Now the farmers and extension workers can be enabled to acquire that knowledge without the need of running complex algorithms and acquire data as that is done through big data analytics in a cloud environment. When it comes to using digital technologies, agricultural stakeholders prefer using drones, GPS, and satellite-based remote sensing data. However, for large-scale adoption of PA-enabling technologies, we need to reduce the cost of such technologies (through government support or cooperative farming) and improve the infrastructure, especially network connectivity. We conclude that using geospatial technologies in combination with IoT and cloud computing not only enhances a paddock’s productivity but also contributes to environmental sustainability.
Original language | English |
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Title of host publication | Precision Agriculture |
Subtitle of host publication | Evolution, insights and emerging trends |
Editors | Qamar Zaman |
Place of Publication | London |
Publisher | Academic Press |
Chapter | 5 |
Pages | 71 - 83 |
Number of pages | 290 |
Edition | 1st |
ISBN (Electronic) | 9780443189531 |
ISBN (Print) | 9780443189531 |
DOIs | |
Publication status | Published - Jun 2023 |