Open AccessPrototype and Method for Crops Analysis in the Visible and Infrared Spectrum from a Multirotor Air Vehicle
Author(s) -
Julian Andres Bolaños,
Liseth Viviana Campo Arcos,
Jaime Muñoz
Publication year - 2020
Publication title -
revista ingenierías universidad de medellín/revista ingenierías universidad de medellín
Language(s) - English
Resource type - Journals
eISSN - 2248-4094
pISSN - 1692-3324
DOI - 10.22395/rium.v19n37a14
Subject(s) - normalized difference vegetation index , multirotor , agricultural engineering , remote sensing , vegetation index , agriculture , index (typography) , precision agriculture , quality (philosophy) , vegetation (pathology) , rotor (electric) , computer science , environmental science , crop , leaf area index , agronomy , engineering , geography , forestry , medicine , mechanical engineering , philosophy , archaeology , epistemology , pathology , aerospace engineering , world wide web , biology
Plant health has a direct impact on the quality and quantity of agricultural products. Due to this fact, farmers must monitor crop conditions frequently. However, the current tools for achieving this are complex and inaccessible. Therefore, this article proposes a method for the characterization of crops that allows to monitor the plants using photographs in the visible and infrared spectrum acquired from a multi-rotor air vehicle, using low-cost cameras and free use tools for designing a prototype of processing information. The characterization is performed by identifying the normalized difference vegetation index (NDVI) in the photographic mosaics of the crops. This index provides information about plant health: Consequently, it is calculated and represented on a NDVI map, where the status of a crop is analyzed. The highest values of NDVI represent healthy plants, and the lowest do so for plants with problems, water, or others. The proposed ethod allows the monitoring of crops in a temporary and spatial form, letting a producer to adopt measures that help the optimization of resources.