Mehmet Emre YAZICI
Independent Consultant, Aerospace Industry
The concept of Precision Agriculture (or precision farming) has been around since the 1960s when the United States’ Secretary of Agriculture, Earl Butz, introduced a system called “grid planting”. Grid planting is a planting pattern in which farms are divided into squares and plants are positioned in rows inside each square. This method allowed farmers to have more control over their land and to make the most out of their resources.[1]
Within the framework of the UN’s Sustainable Development Goals (SDGs) for 2030, specifically under Goal #2 (End hunger, achieve food security and improved nutrition, and promote sustainable agriculture), it is aimed to double the agricultural productivity and incomes of small-scale food producers (farmers/ fishers) to ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding, and other disasters and that progressively improve land and soil quality.
To achieve that goal, world needs to increase food production by almost 50 percent by 2050 to feed a population of nine billion, yet resources such as land and water are becoming more and more scarcer.[2]
This is why agriculture must look beyond grid planting and make use of emerging technologies while implementing precision farming practices.
Farmers are no alien to the use of leading-edge technology in farming. Agricultural aircraft have been in use for this purpose since the 1920s. Remote sensed data from satellites have been used increasingly for years to assess crop distribution, extent, and health from the sky.
Today, Precision Farming collects multiple sensor data, both in the air and on the ground, to improve farm productivity through mapping spatial variability in the field. Existing technology can collect very high-resolution imagery below the cloud level, with much more detail than the satellite imagery usually available. They bring in cost advantages against aircraft, especially in small areas. They also are easy to use. They are called: Drones!
At the most basic level, drones permit farmers to obtain a birds-eye-view of their crops, allowing them to detect subtle changes that cannot be readily identified by “crop scouts” at ground level. Multispectral and hyperspectral aerial imagery collected by drones help in creating Normalized Difference Vegetation Index (NDVI) maps, which can differentiate soil from grass or forest, detect plants under stress, and differentiate between crops and crop stages. There are strong correlations between crop yield and NDVI data measured at certain crop stages. Hence tracking the crop growth at key stages help to provide an accurate estimate of the crop yield and also to address issues early.
