Geospatial
Applications in Agriculture have been boosted by the general advancement of technology in the past few decades. GIS in agriculture is all about analyzing the land, visualizing field data on a map, and putting those data to work. Powered by GIS, precision farming enables informed decisions and actions through which farmers get the most out of each acre without damaging the environment.
Speaking of tools, geospatial technology in agriculture relies on satellites, aircraft, drones, and sensors. These tools are used to make images and connect them with maps and non-visualized data. As a result, you get a map featuring crop position and health status, topography, soil type, fertilization, and similar information.
There are several applications of geoinformatics in agriculture. Let’s have a look at some of them. From this article, you’ll learn about the following applications and use of GIS in agriculture:
• Crop yield prediction
• Crop health monitoring
• Livestock monitoring
• Insect and pest control
• Irrigation control
• Flooding, erosion, and drought control
• Farming automation
Crop yield prediction involves using Convolutional Neural Networks (ConvNets or CNNs) to identify the productivity of a crop. Developers train this algorithm by feeding it images of crops whose yield is already known to find productivity patterns. Crop health monitoring involves using satellite images and input information to assess environmental conditions across the field, such as humidity, air temperature, surface conditions, and others. Livestock monitoring involves tracking the movement of specific animals to help farmers find them on a farm and monitor their health, fertility, and nutrition. Insect and pest control involves using images to assess crop infestation, as well as remote sensing to check the temperature of crops. Irrigation control involves aircraft and satellites equipped with high-resolution cameras to take images and calculate the water stress in each crop. Flooding, erosion, and drought control involve using GIS and remote sensing to identify flood-susceptible areas and check land for susceptibility for soil erosion. Lastly, farming automation involves using GIS solutions to equip machines with task maps and help unskilled workers do their job more efficiently.
Overall, Geospatial Applications in Agriculture are essential for improving food security and increasing agricultural production. By using GIS, precision farming, and automated farming machines, the agricultural industry can feed the world, cut food prices, and save the planet.
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