Geotechnologies and Artificial Intelligence as a Tool of Riparian Forest Management

Abstract

Geotechnologies are important tools for natural resource management in the face of urgent questions and answers demanded by society. They are able to offer a range of mechanisms that, through technique and science, enable the understanding of the starting points through location, dimension, acquisition and processing. For this purpose, the use of Artificial Intelligence (AI) techniques has helped in the manipulation of data ascending from the extensive volume of information generated, as well as the improvement of computational systems. The objective of this paper was to verify the relationship between geotechnologies with emphasis on Remote Sensing (RS) in the management of natural resources, such as riparian forest Permanent Preservation Areas (PPAs) and the use of Artificial Intelligence (AI). For this, a quali-quantitative and descriptive work hereby presented has been considered in the research: Science Direct, Resergate, Scielo and Google Scholar, with emphasis on articles published in journals in both English and Portuguese languages between 2018 and 2020, and explored in the first half of 2021. The summation of the two databases enabled the following results: 07 articles (2018), 15 articles (2019), 32 articles (2020), dissertations (50), articles in proceedings (01), chapters (02), e-books (07), articles in symposia (03), pages without access (13), theses (25), monographs (20), totaling 162 works. The data also revealed little publication on the theme, especially in Portuguese, of articles related to the use of artificial intelligence. However, the use of AI has presented itself as an important tool in research allied to remote sensing and GIS software. Therefore, it was not possible to verify the existence of studies of riparian forest APP using artificial intelligence, indicating a relevant research gap in this area. Thus, it is suggested in future researches the increase of applications of artificial intelligence directed to the study of riparian forest APP associated with geotechnologies.