Recently, the Poti river mouth region has experienced environmental impacts that resulted in a change of landscape in its dry season, highlighting the eutrophication and proliferation of phytoplankton, algae, cyanobacteria and aquatic plants. Considering the aspects related to water-quality monitoring in the semiarid region of Brazil from remote sensing, this study aimed to evaluate the performance of Sentinel-2A satellite data in the retrieval of chlorophyll-a concentration in Poti River in Teresina, Piaui, Brazil. The chlorophyll-a concentration retrieval and mapping methodology involved the study of the water surface reflectance in Sentinel-2A images and their correlation with the chlorophyll-a data collected in situ during the years 2016 and 2017. The results generated by the Chl-1, Ha et al. (2017), Chl-2, Page et al. (2018), and Chl-3, Kuhn et al. (2019) equations show the need for calibrating the algorithms used for the Poti River water components. However, the empirical algorithm Chl-2 shows a correlation has been established to identify the spatiotemporal variation of chlorophyll-a concentration along the Poti River broadly and not punctually. The spatial distribution of this pigment in maps derived from Sentinel-2A is consistent with the pattern of occurrence determined by the in situ data. Therefore, the MSI sensor proved to be a tool suitable for the retrieval and monitoring of chlorophyll-a concentration along the Poti River.

A Realidade Aumentada (RA) é uma tecnologia com novo paradigma de interface com os usuários que vem crescendo em importância na apresentação de produtos cartográficos. A visualização de elementos naturais é incorporada à representação estática terrestre em um ambiente digital interativo. Essa transformação provoca mudanças na forma como os usuários percebem os produtos cartográficos que antes eram apresentados em meios analógicos. O uso da Realidade Aumentada potencializa a apresentação de produtos cartográficos tridimensionais dinâmicos, e permite ampliar o aspecto cognitivo de usuários não especialistas em contato com documentos cartográficos. A tecnologia remonta a década de 1960, e nos dias atuais tem se expandido em diversas funcionalidades em vários setores. O artigo discute a incorporação da Realidade Aumentada na construção do modelo 3D do campus da Universidade Federal de Pernambuco. Tal modelo foi utilizado em experimento aplicado a usuários não especialistas, tendo-se como eixos de avaliação: aspecto territorial, interpretação de elementos, e aspecto comunicativo. Os resultados do experimento mostram que o processo de ensino-aprendizagem na área da cartografia é um campo fértil para atuação da RA, tornando-se um ponto de partida para a elaboração de uma base cartográfica aumentada.Palavras-chave: Visualização Cartográfica; Interatividade, Modelagem 3D. Abstract:Augmented reality (AR) is a technology with new user interface paradigm that is growing in importance in the presentation of cartographic products. The display of natural elements is incorporated into the static terrestrial representation in an interactive digital environment. This 791 A realidade aumentada... Bol. Ciênc. Geod., sec. Artigos, Curitiba, v. 22, n o 4, p.790 -806, out -dez, 2016.

The urban expansion of Teresina has caused environmental impacts on the Poti River due to the occurrence of eutrophication and proliferation of aquatic plants in the dry season of the year. Considering the characteristics related to water-quality monitoring in the Northeast region of Brazil, from remote sensing, this study aimed to evaluate the performance of semi-empirical algorithms in Sentinel-2 data in the detection and mapping of eutrophication and aquatic plants in the river Poti in Teresina, Piaui, Brazil. The eutrophication detection methodology involved the study of the reflectance of the water surface in the Sentinel-2 images and the respective correlation within situ data of chlorophyll-a, using the MCI, MPH and NDCI indexes. The NDCI index showed superior one-off performance than the MCI and MPH indexes. In this sense, with the NDCI, the spatio-temporal variation of eutrophication in the Poti River was identified broadly and no longer specific. In relation to aquatic plants, the NDVI index proved to be appropriate for the detection and mapping of water hyacinths, demonstrating the location of the areas covered by aquatic plants. At the beginning of proliferation, the maximum expansion rate of 854.7% was evaluated. At the end of the dry period, there was a peak of covered area of 570,145.6 m² and a production of 6,408.4 tons of fresh biomass from water hyacinths. Therefore, in both cases, it was found that the MSI sensor was suitable for the detection, mapping and monitoring of eutrophication and aquatic plants in the Poti River.