Precision Agriculture and Unmanned Aerial Vehicles (UAVs)

Abstract

Farming in developing countries is majorly dependent on the traditional knowledge of farmers, with unscientific agricultural practices commonly implemented, leading to low productivity and degradation of resources. Moreover, mechanization has not been integral to farming, and thus managing a farm is a time-consuming and labor-intensive process. Consequently, precision agriculture (PA) offers great opportunities for improvement. Using geographic information and communication technology (Geo-ICTs) principles, PA offers the opportunity for a farmer to apply the right amount of treatment at the right time and at the right location in the farm. However, in order to collect timely high-resolution data, drone-based sensing and image interpretation is required. These high-resolution images can give detailed information about the soil and crop condition, which can be used for farm management purposes. Leaf area index, normalized difference vegetation index, photochemical reflectance index, crop water stress index, and other such vegetation indices can provide important information on crop health. Temporal changes in these indices can give vital information about changes in health and canopy structure of the crop over time, which can be related to its biophysical and biochemical stress. These stresses may have occurred due to insufficient soil nutrient, inappropriate soil moisture, or pest attack. Through UAV-based PA, stressed areas can be identified in real time, and some corrective measures can also be carried out (e.g., fertilizer and pesticide spraying). Moreover, the advantages and different approaches to integrate the UAV data in the crop models are also described.