Exploring the relationship between Landsat-8/OLI remote sensing reflectance and optically active components in the surface water at the UHE Maua/PR

The quality and quantity of water available for both economic growth and life sustainability is one of the major challenges for the sustainable development in the 21st century. This challenge requires research focused on the monitoring of time changes in water properties in several spatial scales. Satellite remote sensing has been applied as an alternative for providing information on optically active components, which act as indicators of water quality. Satellite remote sensing performance, however, varies from one aquatic system to another depending on several factors, such as size, depth, optical properties. This study, therefore, aims to explore the viability of applying remote sensing for monitoring the UHE Mauá reservoir, located in Paraná State. For that, an experiment was carried out to obtain water samples at 24 random samples distributed into the reservoir. Those samples were analyzed in laboratory and optically active components, namely, total suspended solids (TSS) and chlorophyll-a (Chl-a) concentration determined. Surface remote sensing reflectance provided by Landsat/OLI images almost concurrently to satellite overpass was computed for each sample in order to assess the best set of spectral bands and band combinations for estimating the concentrations of TSS and Chl-a. Results indicate that Chl-a was the optically active component spanning the widest range of variability in the Mauá reservoir and having the highest potential to be estimated using remote sensing OLI band 3 (green) explained more than 70 % in chlorophyll-a concentration. This paper is an extended version of Pereira et al. (2017), presented in XVIII Brazilian Symposium on GeoInformatics (GEOINFO 2017)

A floristic survey of angiosperm species occurring at three landscapes of the Central Amazon várzea, Brazil

The Amazonian floodplains harbor highly diverse wetland forests, with angiosperms adapted to survive extreme floods and droughts. About 14% of the Amazon Basin is covered by floodplains, which are fundamental to river productivity, biogeochemical cycling and trophic flow, and have been subject to human occupation since Pre-Colombian times. The botanical knowledge about these forests is still incomplete, and current forest degradation rates are much higher than the rate of new botanical surveys. Herein we report the results of three years of botanical surveys in floodplain forests of the Central Amazon. This checklist contains 432 tree species comprising 193 genera and 57 families. The most represented families are Fabaceae, Myrtaceae, Lauraceae, Sapotaceae, Annonaceae, and Moraceae representing 53% of the identified species. This checklist also documents the occurrence of approximately 236 species that have been rarely recorded as occurring in white-water floodplain forests

AVALIAÇÃO DA DINÂMICA DO USO E COBERTURA DA TERRA NA BACIA HIDROGRÁFICA DE CONTRIBUIÇÃO PARA O RESERVATÓRIO DE BARRA BONITA - SP

A interferência antrópica no ambiente ocorre de forma muito dinâmica e para acompanhá-la é preciso dispor de tecnologias eficientes, dentre as quais se destaca o sensoriamento remoto. Neste sentido, o presente estudo teve como propósito avaliar a dinâmica do uso e cobertura da terra na bacia hidrográfica de contribuição para o reservatório de Barra Bonita com aproximadamente 19.164,43 km2, situada no interior do Estado de São Paulo, mais especificamente, entre as coordenadas geográficas 21° 54\u27 20\u27\u27 e 23° 57\u27 26\u27\u27 Sul e 46° 39\u27 27\u27\u27 e 48° 34\u27 52\u27\u27 Oeste. Para tal foram utilizadas imagens dos sensores TM - Landsat 5 e ETM+ - Landsat7 referentes à 1990 e 2002, respectivamente. Estas imagens foram processadas utilizando o Spring 3.6 e aplicando uma classificação supervisionada. O classificador utilizado foi do tipo por regiões, sendo o método denominado Bhattacharya Distance com um limiar de aceitação de 90%. Desta forma foram obtidos os mapas de uso e cobertura da terra para 1990 e 2002, a partir dos quais foi possível calcular a área para 11 classes de uso e cobertura da terra e verificar as alterações ocorridas ao longo deste período. Utilizando o banco de dados SIDRA do IBGE foi possível obter dados de Produtividade Agrícola Municipal (PAM), de área plantada (em hectares), para culturas permanentes e temporárias da bacia em estudo, para os anos de 1990 a 2002. Os resultados desta fase foram importantes para confirmar as tendências observadas nos mapas de uso e cobertura da terra, obtidos em fase anterior. Neste trabalho foi possível identificar ainda locais próximos ao reservatório de Barra Bonita onde o uso inadequado da terra torna-se fonte de poluição difusa dos afluentes do reservatório de Barra Bonita. Estes locais foram georreferenciados em campo, fotografados e identificados no mosaico de imagens de 2002, fortalecendo a discussão dos resultados obtidos. Os resultados mostram que se trata de uma bacia bastante antropizada, onde medidas de planejamento devem ser tomadas no sentido de mitigar o processo de degradação ambiental

Mapeamento de potenciais florações de cianobactérias usando imagem Hyperion/EO-1 no estuário da Lagoa dos Patos

This paper proposes an approach for using remote sensing data for identification and mapping of cyanobacterial blooms; Methods: It uses two sets of spectra (empirical and theoretical) as reference to classify the areas of cyanobacteria blooms using a Hyperion image acquired over the Patos Lagoon, located in Rio Grande do Sul State, Brazil. To circumvent cyanobacteria misclassification due to suspended inorganic particle (SIP) scattering, pigment band ratios – phycocyanin (650/620 nm) and chlorophyll-a (700/680 nm) - were applied; Results: An area of 22.5 km2 prone to cyanobacterial blooms was mapped into 5 classes with chlorophyll-a concentration varying from 8 to 1,000 μg.L–1 using both, empirical and theoretical spectra; Conclusions: The results corroborate the general spectral features of cyanobacterial blooms and indicated that band ratios operation removed the areas affected by high concentrations of SIP.Este artigo apresenta um método de identificação e mapeamento de florações de cianobatérias utilizando imagem do sensor hiperespectral Hyperion/EO-1; Métodos: O método aplica dois conjuntos de curvas espectrais (uma empírica e outra teórica) como referência para classificar áreas potenciais de ocorrência de cianobactérias na Lagoa dos Patos localizada no Estado do Rio Grande do Sul Rio Grande, Brasil. De modo a evitar que partículas inorgânicas fossem indevidamente classificadas como cianobactérias devido ao espalhamento da radiação por partículas inorgânicas em suspensão (PIS) foi realizada a intersecção das áreas resultantes do cálculo da razão entre as bandas referentes às absorções pela ficocianina (650/620 nm) e clorofila-a (700/680 nm); Resultados: Uma área total de 22,5 km2 potencial na ocorrência de cianobactéria foi identificada e classificada em 5 classes de concentrações de clorofila-a variando entre 8 e 1000 μg.L–1 a partir dos conjuntos de espectros de referência – empírico e teórico – com 88% de similaridade entre eles; Conclusões: Os resultados corroboram as feições espectrais de florações de cianobactérias e indicam que as áreas afetadas pelo efeito de espalhamento pela presença de altas concentrações de PIS foram removidas pela metodologia aplicada

AVALIAÇÃO DE FUSÃO DE IMAGENS ÓPTICAS E MICROONDAS NO MAPEAMENTO DE MORFOLOGIAS LACUSTRES

Diferentes tipos de informação sobre os lagos da planície amazônica podem ser extraídas de imagens obtidas de sistemas sensores ópticos e de microondas. Enquanto imagens ópticas fornecem informações sobre as características físico-químicas dos alvos, as imagens de radar geram informações sobre as características dielétricas, a textura e a geometria dos alvos. A técnica de fusão dessas imagens pode então aumentar a separabilidade entre alvos em classificações numéricas e facilitar a interpretação visual das feições geomorfológicas. Este trabalho tem como objetivo avaliar o uso desta técnica no mapeamento das feições lacustres como contribuição à caracterização morfológica e genética dos lagos fluviais. Para isto, foram processadas, analisadas e avaliadas as imagens do TM-LANDSAT e do mosaico JERS-1/GRFM - Global Rainforest Mapping Project. Os resultados indicaram que a fusão dessas imagens é tecnicamente viável para a caracterização das morfologias lacustres

Monitoring Water Siltation Caused by Small-Scale Gold Mining in Amazonian Rivers Using Multi-Satellite Images

The small-scale mining techniques applied all over the Amazon river basin use water from streams, including digging and riverbed suctioning, rarely preventing environmental impacts or recovery of the impacted areas. As a consequence, thousands of tons of inorganic sediment (which can contain mercury) have been discharged directly into the rivers creating sediment plumes that travel hundreds of kilometers downstream with unknown consequences to the water quality and aquatic biota. We hypothesize that because of intensification of mining activities in the Brazilian Amazon, clear water rivers such as the Tapajós and Xingu rivers and its tributaries are becoming permanently turbid waters (so-called white waters in the Amazonian context). To investigate this hypothesis, satellite images have been used to monitor the sediment plume caused by gold mining in Amazonian rivers. Given the threat of intense water siltation of the Amazonian rivers combined with the technological capacity of detecting it from satellite images, the objective of this chapter is to inform the main activities carried out to develop a monitoring system for quantifying water siltation caused by small-scale gold mining (SSGM) in the Amazon rivers using multi-satellite data

Classificação da cobertura da terra na planície de inundação do Lago Grande de Curuai (Amazônia, Brasil) utilizando dados multisensor e fusão de imagens

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea

METODOLOGIA DE ANÁLISE DA DINÂMICA DE ÁREA E VOLUME INUNDÁVEL: O EXEMPLO DA VÁRZEA DO LAGO GRANDE DE CURUAI

Este artigo apresenta uma metodologia para processamento e utilização de dados batimétricos de alta resolução, coletados com o ecobatimetro - Lowrance- modelo 480M, em áreas inundáveis da planície do rio Amazonas. Imagens TM/Landsat foram utilizadas como suporte ao planejamento e execução do levantamento batimétrico. Um conjunto de 4600 km lineares de transectos gerados durante o levantamento, foi submetido a uma seqüência semi-automática de processamento, e o resultado integrado a uma base de dados georreferenciada. Um modelo de elevação digital com resolução horizontal de 15 metros e resolução vertical de 1 centímetro foi gerado para a planície. A dinâmica de área inundada e de volume de água armazenado na planície foi avaliada a partir destes dados. Modelos de regressão para estimativa de área inundada e de volume armazenado na planície, a partir no nível de água, foram construídos. Os resultados deste trabalho mostraram que a informação de nível de água e área inundada mapeada a partir de imagens são um bom "proxy" para a estimativa do volume de água armazenado na planície do Lago Grande de Curuai

COMPARING MODIS AND ETM+ IMAGE DATA FOR INLAND WATER STUDIES: SPATIAL RESOLUTION CONSTRAINTS

The objective of this paper is to compare the performance of medium spatial resolution (250 m and 500 m) Terra MODIS images to finer resolution Landsat ETM+ images. MODIS Terra images have high frequency of acquisition (1 day revisit at high latitudes) and that makes them more useful for inland water studies. Assessing the performance of ETM and MODIS to map relevant features for the functioning of aquatic systems is very important for fostering water resource remote sensing. To carry out the comparison, concurrent ETM+ and MODIS images were acquired over the Lago Grande de Curaui Lake. The images were georeferenced and resample to the 100 x 100 m ground resolution using a next neighbor algorithm to make the data comparable. The resampling rationale was making the digital processing easier, without changing the effective resolution properties of the original data. It was assumed that the improved MODIS radiometric resolution as compared to the ETM+.would make both data set comparable at a 100m x 100m resolution. In the next step, a series of tests were carry out in order to define the best approach to map aquatic system features such as lakes, islands, and levees in the study area. The tests indicated that the best approach was the segmentation of the shadow fraction derived from the application of the linear unmixing model to both ETM+ and MODIS images. The segmentation was then followed by the application of a non-supervised region classifier. The final classes were mapped into two categories: lakes (water) and island (land). The polygon distribution generated by the classification procedure was then statistically analyzed to assess the polygon size frequency of features mapped by each data set. The results showed that ETM+ and MODIS were able to recover the water surface area in the studied region with a difference of 11 %. The analyses of polygon distribution, however, showed that there were many polygons which were detected in MODIS image data, but not in ETM+ image data. This result suggests that the spectral and radiometric resolution improvements presented by MODIS image tend to compensate for the losses in spatial resolution. That is to say that under the boundary conditions adopted in this study, MODIS images performed better than degraded ETM+ images of 100m x 100m. This explains the small difference in performance presented by comparing two sensors with such large differences in nominal spatial resolution

Simulation of spectral bands of the MERIS sensor to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region

Nowadays, the monitoring of water is essential for the sustainability and better management of water resources. The use of remote sensing data is important, since it allows evaluation of dynamic problems in aquatic systems, such as the eutrophication of bodies of water and suspended sediment. The aim of this study was to estimate chlorophyll-a concentrations in a reservoir of the semi-arid region of Brazil using simulated orbital-sensor data, as an aid in the management of water resources. The study area corresponded to the Orós reservoir, in the State of Ceará, Brazil. Water samples for analysis of the chlorophyll-a and measurements of the spectral radiance of the aquatic system were collected from 20 points. The radiance was measured by spectroradiometer. The data were collected in June and August of 2011. The model using three bands of the MERIS sensor (7, 9 and 10) presented an R2 of 0.84. For the two-band model (7 and 9), the value of R2 was 0.85. The waters of the Orós reservoir were all classified as eutrophic. The main optically active component in modelling the shape of the spectra was chlorophyll-a. The models showed a mean absolute error (MAE) of 3.45 and 3.61 μg L-1 for the three- and two-band models respectively. The models displayed high coefficients of determination, i.e. the simulations show the feasibility of estimating chlorophyll-a concentration from the data of the MERIS orbital sensor