Name: FILIPE DE MORAES
Publication date: 29/05/2020
Advisor:
Name |
Role |
|---|---|
| MARCELO BARRETO DA SILVA | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| EDNEY LEANDRO DA VITÓRIA | Co advisor * |
| MARCELO BARRETO DA SILVA | Advisor * |
| RONEY PIGNATON DA SILVA | External Examiner * |
Summary: MORAES, Filipe de M.Sc; Federal University of Espírito Santo; Use and Validation of Unmanned Air Vehicle in Agricultural Remote Sensing; Advisor: Marcelo Barreto da Silva. Co-supervisor: Edney Leandro da Vitória
The study on the Use of Uants in agriculture has been growing exponentially, in the last year alone it grew by 31%. The objective of the present work was to analyze, and direct the use of UAVs in the agricultural and remote sensing context, the study was divided into 4 captures. In the first chapter, a bibliometric review was developed on the topic Remote sensing with the use of unmanned aerial vehicles in agriculture, through the scopus database, were selected and evaluated statistically, WHERE 280 publications on the researched topic were found. Brazil has a small number of researches considering its area and agricultural potential, this justifies the intensification and direction of studies in the area of remote sensing with unmanned aircraft in agriculture. The second chapter aimed to evaluate the UAV models and the ideal times for mapping in the same conditions as the DJI Phantom 4 pro and Mavic 2 Pro experiment which provides the best results and at what time the flight planning should be done, so that you get the best result at the time of the mapping. The treatments were differentiated by the flight height and RPAS used, there were 2 RPAS, 4 flight heights explored and 4 repetitions in each height, totaling 32 flights. The flights were made automatically by the Dronedeploy application, the variables evaluated were variables evaluated: time, number of photos, total error and surface resolution. Considering all the information, the Mavic 2 pro above 80 meters is superior to the Phantom 4 pro for mapping activity under the conditions of this study. Except for the number of photos registered. The third chapter aimed to compare and establish the correlation between the measurement in the field, of data referring to the coffee crop and the data estimated through the use of UAVs equipped with a RGB wavelength camera, native to the same, in the crop of Coffea canphore. The work in the experimental area of Coffea Canephora was developed in the experimental farm of the Federal University of Espírito Santo, campus São Mateus. The data were collected in an experimental Conilon coffee crop submitted to different water depths since its implantation. Mapping procedures, orthophoto assembly and processing by supervised classification were used, and through this procedure that differentiates the surface patterns, the estimate was evaluated in relation to the measurement made in the field. UAV can be considered a low cost tool, easy to operate and images are also easily processed and analyzed, which reduces the response time for any possible treatment and also makes field operations more sustainable.
