Mapping skips in sugarcane fields using object-bas... - BV FAPESP
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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Mapping skips in sugarcane fields using object-based analysis of unmanned aerial vehicle (UAV) images

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Author(s):
Wachholz de Souza, Carlos Henrique [1] ; Camargo Lamparelli, Rubens Augusto [2] ; Rocha, Jansle Vieira [1] ; Graziano Magalhaes, Paulo Sergio [1, 2]
Total Authors: 4
Affiliation:
[1] Univ Estadual Campinas, Sch Agr Engn, BR-13083875 Campinas, SP - Brazil
[2] Univ Estadual Campinas, Interdisciplinary Ctr Energy Planning, BR-13083896 Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 143, p. 49-56, DEC 2017.
Web of Science Citations: 13
Abstract

The use of unmanned aerial vehicles (UAVs) as remote sensing platforms has tremendous potential for describing detailed site-specific features of crops, especially in early post-emergence, which was not possible previously with satellite images. This article describes an object-based image analysis (OBIA) procedure for UAV images, designed to map and extract information about skips in sugarcane planting rows. The procedure consists of three consecutive phases: (1) identification of sugarcane planting rows, (2) identification of the existent sugarcane within the crop rows, and (3) skip extraction and creation of field-extent crop maps. Results based on experimental fields achieved skip rates of between 2.29% and 10.66%, indicating a planting operation with excellent and good quality, respectively. The relationship of estimated versus observed skip length had a coefficient of determination of 0.97, which was confirmed by the value of the enhanced Wilmott concordance coefficient of 0.92, indicating good agreement. The OBIA procedure allowed a high level of automation and adaptability, and it provided useful information for decision making, agricultural monitoring, and the reduction of operational costs. (AU)

FAPESP's process: 12/50048-7 - Methodology to use UAVs in monitoring sugarcane for precision agriculture purposes
Grantee:Jansle Vieira Rocha
Support Opportunities: Research Grants - Research Partnership for Technological Innovation - PITE