Development of Methods Acquiring Real Time Very High Resolution Agricultural Spatial Information Using Unmanned Aerial Vehicle

Abstract

There is a need for high resolution spatial information to provide quality agricultural spatial information for better monitoring and management of farm activities to increase production and sustainable agricultural economic development. The Unmanned Aerial Vehicles are able to capture very high resolution spatial data that can be transformed into useful geospatial information, databases and digital maps. However, Unmanned Aerial Vehicle methods of acquiring spatial data are yet to be developed. The objective of this study was to develop methods of acquiring real time high resolution agricultural spatial data using Unmanned Aerial Vehicle. A qualitative case study research approach, and data collection method were used to achieve the objective. A ground truth data was carried out to eliminate errors. Unmanned Aerial Vehicle data acquisition system and data processing methods were developed. These methods could be used for better farm management and reduce the cost of inputs like fertilizers.

A Strategic Analytics Using Convolutional Neural Networks for Weed Identification in Sugar Beet Fields

“…It has two dimensions for a grayscale image. The color is represented by a third dimension of depth, 3 to represent the fundamental colors [Red, Green, and Blue] (Bolo et al, 2019).…”