Research on remote sensing methodologies acquired by aerial surveys for precision agriculture and forest management

• Grant number: 21/05962-1
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Duration: February 01, 2022 - January 31, 2024
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Cesar Antonio Francisco
• Grantee: Cesar Antonio Francisco
• Host Company: Engemap Engenharia, Mapeamento e Aerolevantamento Ltda
• CNAE: Atividades técnicas relacionadas à arquitetura e engenharia
• City: Assis
• Associated scholarship(s): 23/02430-4 - Research on remote sensing methodologies acquired by aerial surveys for Precision Agriculture and Forest Management., BP.TT; 22/11522-7 - Research on remote sensing methodologies acquired by aerial surveys for Precision Agriculture and Forest Management., BP.TT; 22/02066-8 - Research on remote sensing methodologies acquired by aerial surveys for Precision Agriculture and Forest Management., BP.TT

Abstract

Agriculture and forest management 4.0 is an analogy to Industry 4.0, as a result of the digital transformation of agribusiness through the massive collection of data to assist in decision making. Behind the agricultural and forestry operational activities of large groups and national and foreign companies there is a growing demand for remote sensing data that are basic inputs for the analysis of agriculture and precision forest management activities. This demand is more evident in Brazil, where both sectors together accounted for more than 20% of the Brazilian GDP in 2019.The more precise the scale of spatial and temporal data acquisition, the more assertive the information of the operation will be. Currently, data are used in an isolated and limited way, with low integration, mostly coming from multispectral sensors. In contrast, in recent years, there has been a strong focus on mapping companies in increasing the speed of data delivery to the customer. Factors like uploading field data to the cloud, automatic alignment of scans, product automation and delivery via the browser mean that end users are getting their data faster. With the push for digital twin, there is now more interest in complete coverage of buildings and assets using a variety of integrated technologies, in particular LiDAR. There are technologies that enable the integration of LiDAR and multispectral scanner sensors applied in Precision Agriculture and Forest Management. However, data acquisition in the same area is rare practiced with the use of LiDAR and multispectral technology in conventional ARPs for large-scale mapping. Therefore, it is the general objective of this project to carry out applied research for the acquisition and analysis of high precision remote sensing data obtained through manned and unmanned aerial surveys with LiDAR and Multispectral technology, as well as to develop an integrated solution for acquisition, processing and three-dimensional data analysis of relief and vegetation structures. Specifically, the proposed research project seeks to deepen the comparison of methods of acquisition and use of LiDAR and Multispectral remote sensing data obtained by manned and unmanned aerial surveys to be applied in agriculture and precision forest management activities during the planning phases, execution and harvesting of plantations. Through this project it will be possible to enter the Agribusiness and Forestry market as a provider of remote sensing data solution by aerial surveys for applications in agriculture projects and precision forest management. This will make it possible to deepen the knowledge in applications aimed at the agricultural and forestry departments of companies that produce in large areas and that today, through existing technologies, present bottlenecks in relation to the productive capacity of data from remote sensing by drones, and that due to due to the low capacity to cover areas, they require teams and equipment internally, or hiring different companies to carry out the data acquisition work. (AU)