Web and MATLAB-Based Platform for UAV Flight Management and Multispectral Image Processing

Sensors (Basel). 2022 Jun 2;22(11):4243. doi: 10.3390/s22114243.


The deployment of any UAV application in precision agriculture involves the development of several tasks, such as path planning and route optimization, images acquisition, handling emergencies, and mission validation, to cite a few. UAVs applications are also subject to common constraints, such as weather conditions, zonal restrictions, and so forth. The development of such applications requires the advanced software integration of different utilities, and this situation may frighten and dissuade undertaking projects in the field of precision agriculture. This paper proposes the development of a Web and MATLAB-based application that integrates several services in the same environment. The first group of services deals with UAV mission creation and management. It provides several pieces of flight conditions information, such as weather conditions, the KP index, air navigation maps, or aeronautical information services including notices to Airmen (NOTAM). The second group deals with route planning and converts selected field areas on the map to an UAV optimized route, handling sub-routes for long journeys. The third group deals with multispectral image processing and vegetation indexes calculation and visualizations. From a software development point of view, the app integrates several monolithic and independent programs around the MATLAB Runtime package with an automated and transparent data flow. Its main feature consists in designing a plethora of executable MATLAB programs, especially for the route planning and optimization of UAVs, images processing and vegetation indexes calculations, and running them remotely.

Keywords: MATLAB®; multispectral image processing; precision agriculture (PA); remote sensing (RS); unmanned aerial vehicle (UAV); web programming.

MeSH terms

  • Agriculture* / methods
  • Data Collection
  • Image Processing, Computer-Assisted
  • Remote Sensing Technology* / methods

Grant support

The APC is partially funded by Universidad Europea de Madrid, and is also partially funded by the Universidad Francisco de Vitoria within the UFV2022-45 “Automatic creation of 3D meshes of objects, buildings, and scenery using drones”.