Análise cienciométrica do sensoriamento remoto de macrófitas aquáticas em reservatórios

Abstract

The main objective of this study was to carry out a scientometric analysis of the use of remote sensing to determine aquatic macrophytes in reservoirs. For this review, scientific articles published in electronic media were researched. The search was limited to the Coordenação de Aperfeiçoamento Pessoal de Nível Superior (CAPES), Scientific Electronic Library Online (SCIELO) and SCOPUS databases. The keywords used in the study were: macrophytes; remote sensing; reservoir. The inclusion criterion was: (i) complete scientific articles published in Portuguese, English and Spanish; (ii) scientific articles containing the keywords. The exclusion criteria were: (i) incomplete scientific articles, published in languages other than Portuguese, English and Spanish; (ii) scientific articles that did not contain the 3 keywords. The scarcity of studies on remote sensing of macrophytes in reservoirs in the databases consulted led to the search being expanded to include the keyword: aquatic plants. Twenty scientific articles were found, but at the time of selection for the scientometric analysis, twelve articles published between 1999 and 2020 were chosen, with a gap between 2000 and 2007. As a result, all the articles in this analysis used remote sensing as a method of monitoring aquatic plants, 75% of which sought to monitor the growth and characteristics (mainly the species) of macrophytes in order to develop strategies to contain excessive plant growth, which could therefore compromise water quality or fishing and navigation practices. One study also used monitoring to identify the depth of submerged macrophytes and 16% of the articles limited themselves to describing the characteristics of existing methodologies for monitoring this type of vegetation. With the small number of specific articles, and in view of the specific nature of the behavior of aquatic macrophytes in reservoirs, there is a clear need to produce more studies that focus on more assertive measurements.