Measurement capacity of geometry parameters in coffee fields by lidar sensor LiDAR

• Grant number: 16/16100-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2016
• End date: June 30, 2017
• Field of knowledge: Agronomical Sciences - Agricultural Engineering
• Principal Investigator: José Paulo Molin
• Grantee: Felippe Hoffmann Silva Karp
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

The spatial and temporal variability are two basic and renowned concepts of precision agriculture (PA). Many studies and alternatives on the application of PA arose due to the increasing of properties and intensification of production. The LiDAR technology (Light Detection and Ranging) is one of these alternatives. This technology has its base on sensors, which can estimate distance between the sensor and the object, through the time between emission and reception of a laser that the sensor emits. The use of terrestrial LiDAR expressed the need for the development of studies for its application in agriculture. Latest studies pursued to evaluate important culture geometric parameters of perennial and / or tree crops such as canopy volume and height. Studies of LiDAR application in agriculture already exists for viticulture, citrus and other fruit crops. However, there are no studies that check if the use of LiDAR technology works properly in coffee culture, also a perennial crop, sized tree and with a high value added product. Thus, the objective of this study is to evaluate the potential of LiDAR technology in getting the coffee geometric parameters for PA application. The development of the research will carry collections under controlled conditions to evaluate the errors generated in data collection and analysis of the presence of variability in a commercial area of Arabica coffee. The analysis of the datum from the collection under controlled conditions will compare the volume measurements, area, height and width of the actual objects with those obtained from the readings by LiDAR sensor system. As for the collection in the commercial area of coffee, the study will apply descriptive statistics, analysis of datum distribution via histogram and a geostatistical analysis, evaluating the spatial variability present in the area.