Abstract

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

Highlights

  • Remote sensing (RS) through Unmanned Aerial Vehicles (UAVs), is a new topic of research in the civil field, and an alternative to conventional platforms, for the acquisition of data with infinite possibilities

  • We focus on developing a solution for the monitoring of agave crops, taking advantage of the opportunity to obtain a high spatial resolution, which is provided through low-cost UAVs

  • We proposed a methodology for agave crop monitoring

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Summary

Introduction

Remote sensing (RS) through Unmanned Aerial Vehicles (UAVs), is a new topic of research in the civil field, and an alternative to conventional platforms, for the acquisition of data with infinite possibilities. The support provided to agriculture through UAVs can be used to create alternatives with greater versatility and low cost. UAV technology in conjunction with other disciplines and fields of research are generating new applications in agriculture, such as crop identification, monitoring and mapping of cultivated areas, pest detection, crop yield estimation and prediction of anomalies. Monitoring crops through UAV can be a good tool for decision-making, management and planning of public policies in the agriculture. UAV allows for obtaining reliable data but in a more economical way

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