Supervised classification of riparian forest areas of influence in the Goitá and Tapacurá dams through Spring

• Autor(a) principal: Zamora, Valentin Rubén Orcón
• Data de Publicação: 2020
• Outros Autores: Cruz, Adiel Felipe da Silva, Andrade, Antonio Ricardo Santos de, Silva, Edijailson Gonçalves da, Andrade, Emylle Kerolayne Palmeira de, Silva, Jéssica Dayana de Souza, Silva, Edes Torres da
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/9947
• topic: Bacia hidrográfica; Detecção de mudanças; Imagem de satélite; Pixel; Sensoriamento remoto.; Watershed; Change detection; Satellite image; Pixel; Remote sensing.; Cuenca hidrográfica; Detección de câmbios; Imagen satelital; Pixel; Sensoriación remota.

Nowadays, the riparian forests have been degraded by anthropic activities, contributing to silting, contamination and degradation of the environment. Law Nº 12,651 provides for the existence of a minimum area of preservation around water bodies, requiring spatial and temporal monitoring. This monitoring can be done through multiple GIS (Geographic Information Systems) applications available to evaluate the exchange rates in the coverage, including SPRING. In this sense, the objective of the study was to evaluate the performance of the SPRING software in the mapping and supervised classification of the areas under influence of the Goitá and Tapacurá reservoirs, using IKONOS and Google Earth images for the years 2009 and 2019. To carry out the classification, two areas of influence of the riparian forest surrounding the two dams located in the Capibaribe river basin were defined. Six land use and occupation classes were defined. The classification was performed using the maximum likelihood method, comparing the pixels of the image one to one, with a 99% rating threshold. The results determined the existence of 2,2975 km2 of riparian forest in the Goitá dam, presenting greater change in the area of sugar cane with an increase of 4.01%. For the Tapacurá dam, 1,8858 km2 of riparian forest was determined, with a greater change in the area of pastures with an increase of 8.43%. Both areas showed substantial increments in the Mata class (Goitá: 23.41% and Tapacurá: 17.83%). The use of the SPRING software allowed the supervised classification of the riparian forest in these dams, determining six important coverages.