Methodology for Using Georeferenced Digital Maps to Manage the Canopy Height of Elephant Grass Genotypes

Abstract

Objective: The objective of this study was to develop a methodology to accurately report the average canopy height formed by elephant grass genotypes, without carrying out numerous field evaluations. Theoretical Framework: The research is based on the concepts of digital agriculture and photogrammetry for the potential use of remotely piloted aircraft (RPAs), which are low-altitude remote sensing platforms. These platforms, equipped with several high-precision sensors, can be used to obtain diverse information about elephant grass. Method: The methodology adopted for this research involves aerial mapping of elephant grass patches in the José Henrique Bruschi experimental area, Coronel Pachecho, MG – for data collection using a PRA. Photogrammetric processing of the aerial images, statistical analysis of the data and the maps generated were performed. Results and Discussion: According to the results obtained, it is clear that the height of elephant grass can be estimated well using precision GPS and ARP images. The correlation of 0.9 observed between the average heights obtained demonstrates that the methodology using ARP and precision GPS has the potential to replace or complement, efficiently and accurately, measurements using a graduated ruler. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied in the field of PRA use. Their use in agricultural systems is increasingly important in crop monitoring, being relevant to the environment and agriculture. Originality/Value: This study contributes to the literature by presenting a methodological proposal to accurately report the average canopy height of elephant grass genotypes. The relevance and value of this research are evidenced by showing that the proposed methodology was more representative than the average height obtained by the field method.

Code and data availability

The article describes UAV-based canopy height estimation of elephant grass genotypes, but contains no data availability statement, no public phenotype dataset, no deposited images or maps, and no author analysis code or repository. All URLs mentioned (Pix4D, Esri, Global Mapper, TechGeo, Sentera, Embrapa news) are for

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