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The Amazon Basin is the largest on the planet, and its aquatic ecosystems affect and are affected by the Earth’s processes. Specifically, Amazon aquatic ecosystems have been subjected to severe anthropogenic impacts due to deforestation, mining, dam construction, and widespread agribusiness expansion. Therefore, the monitoring of these impacts has become crucial for conservation plans and environmental legislation enforcement. However, its continental dimensions, the high variability of Amazonian water mass constituents, and cloud cover frequency impose a challenge for developing accurate satellite algorithms for water quality retrieval such as chlorophyll-a concentration (Chl-a), which is a proxy for the trophic state. This study presents the first application of the hybrid semi-analytical algorithm (HSAA) for Chl-a retrieval using a Sentinel-3 OLCI sensor over five Amazonian floodplain lakes. Inherent and apparent optical properties (IOPs and AOPs), as well as limnological data, were collected at 94 sampling stations during four field campaigns along hydrological years spanning from 2015 to 2017 and used to parameterize the hybrid SAA to retrieve Chl-a in highly turbid Amazonian waters. We implemented a re-parametrizing approach, called the generalized stacked constraints model to the Amazonian waters (GSCMLAFW), and used it to decompose the total absorption αt(λ) into the absorption coefficients of detritus, CDOM, and phytoplankton (αphy(λ)). The estimated GSCMLAFWαphy(λ) achieved errors lower than 24% at the visible bands and 70% at NIR. The performance of HSAA-based Chl-a retrieval was validated with in situ measurements of Chl-a concentration, and then it was compared to literature Chl-a algorithms. The results showed a smaller mean absolute percentage error (MAPE) for HSAA Chl-a retrieval (36.93%) than empirical Rrs models (73.39%) using a 3-band algorithm, which confirms the better performance of the semi-analytical approach. Last, the calibrated HSAA model was used to estimate the Chl-a concentration in OLCI images acquired during 2017 and 2019 field campaigns, and the results demonstrated reasonable errors (MAPE = 57%) and indicated the potential of OLCI bands for Chl-a estimation. Therefore, the outcomes of this study support the advance of semi-analytical models in highly turbid waters and highlight the importance of re-parameterization with GSCM and the applicability of HSAA in Sentinel-3 OLCI data.

ABSTRACT Remote-sensing data are essential to evaluate dynamic processes such as eutrophication and increases in the concentration of suspended sediments in continental aquatic systems. The aim of this study, therefore, was to develop models to estimate chlorophyll-a concentrations from remote-sensing data in continental waters of the Brazilian semi-arid region. The study area corresponds to the Orós reservoir, located in the state of Ceará. The models were developed based on measurements taken at 20 sampling points. Water samples were collected from the reservoir to i) analyse the chlorophyll-a, electrical conductivity, pH and turbidity; ii) take optical measurements in situ of water transparency and spectral radiance. Radiance measurements were carried out using an ASD FieldSpec®3 Hi-Res spectroradiometer. The spectral data were later transformed into reflectance values and used to test the performance of several models found in the literature for estimating chlorophyll-a. The results showed that for the three-band model, the maximum value for the coefficient of determination (R2), of 0.88, was obtained using the λ1 = 660 nm, λ2 = 690 nm and λ3 = 717 nm spectral bands. The model employing two spectral bands presented the best performance (R2 = 0.87) in the λ1 = 660 nm and λ2 = 690 nm bands. An absolute mean error of 5.35 and 5.00 µg L-1 was found for the three- and two-band models respectively. The developed models are reliable, showing that chlorophyll-a concentrations can be quantified from remote-sensing field data with a high degree of accuracy.

This study assessed sunglint effects in airborne high spatial and high spectral resolution images acquired by the SpecTIR sensor under different view-illumination geometries over the Brazilian Ibitinga reservoir (Case II waters). These effects were corrected using the Goodman et al. (2008) and the Kutser et al. (2009) methods, and a variant that used the continuum removal technique to calculate the oxygen absorption band depth. The performance of each method to removing sunglint effects was evaluated by a quantitative analysis of pre- and post-sunglint correction reflectance values (residual reflectance images). Furthermore, the analysis was supported by inspection of the reflectance differences along transects placed over homogeneous masses of waters or over specific portions of the scenes affected and non-affected by sunglint. Results showed that the algorithm of Goodman et al. (2008) produced better results than the other two methods, as it approached to zero the amplitude of the reflectance values between homogenous water masses free and contaminated by sunglint. The Kutser et al. (2009) method had also good performance, except for the most contaminated sunglint portions of the scenes. When the continuum removal technique was incorporated to the Kutser et al. (2009) method, results varied with the scene and were more sensitive to atmospheric correction artifacts and instrumental signal-to-noise ratio.

In 2023, an intense drought impacted the Amazon basin triggered by climate change and a strong El Niño event, with the Negro River reaching its lowest water level in 120 years. However, the spatiotemporal open water extent (OWE) during this drought remains unclear. This study comprehensively evaluates OWE variability in the central Amazon using Sentinel-1 synthetic aperture radar (SAR) data since 2017. Monthly OWE masks were generated through an empirical threshold classification with accuracy >95%. Overall, the central Amazon experienced a reduction of ∼8% in OWE in the 2023 dry season months (November and December) when compared to monthly-average. However, reductions of up to 80% in OWE were observed in several specific lakes. Our analysis underscores the unprecedented severity of the 2023/2024 drought on rivers and floodplains. Utilizing SAR remote sensing technologies, this study emphasizes the urgent need for proactive conservation measures to safeguard the Amazon’s ecological integrity amid escalating environmental challenges. Monthly water masks from January/2017 to September/2024 are available here: https://doi.org/10.5281/zenodo.12751783 .

Nanosatellites and CubeSats were first developed for educational purposes. However, their low cost and short development cycle made nanosatellite constellations an affordable option for observing the Earth by remote sensing, increasing the frequency of high-resolution imagery, which is fundamental for studying and monitoring dynamic processes. In this sense, although still incipient, nanosatellite applications and proposed Earth observation missions are steadily growing in number and scientific fields. There are several initiatives from universities, space agencies and private companies to launch new nanosatellite missions. These initiatives are actively investigating new technologies to improve image quality and studying ways to increase acquisition frequency through the launch of larger constellations. So far, the private sector is leading the development of new missions, with proposals ranging from 12 to more than one thousand nanosatellite constellations. Furthermore, new nanosatellite missions have been proposed to tackle specific applications, such as natural disasters, or to test improvements on nanosatellite spatial, temporal and radiometric resolution. The unprecedented combination of high spatial and temporal resolution from nanosatellite constellations associated with improvement efforts in sensor quality is promising and may represent a trend to replace the era of large satellites for smaller and cheaper nanosatellites. This article first reports on the development and new nanosatellite missions of space agencies, universities and private companies. Then a systematic review of published articles using the most successful private constellation (PlanetScope and Doves) is presented and the principal papers are discussed.

The composition of phytoplankton and the concentration of pigments in their cells make their absorption and specific absorption coefficients key parameters for bio-optical modeling. This study investigated whether the multispectral vertical diffuse attenuation coefficient of downward irradiance (Kd) gradients could be a good framework for accessing phytoplankton genera. In situ measurements of remote sensing reflectance (Rrs), obtained in an Amazon Floodplain Lake (Lago Grande do Curuai), were used to invert Kd, focusing on Sentinel-3/Ocean and Land Color Instrument (OLCI) sensor bands. After that, an analysis based on the organization of three-way tables (STATICO) was applied to evaluate the relationships between phytoplankton genera and Kd at different OLCI bands. Our results indicate that phytoplankton genera are organized according to their ability to use light intensity and different spectral ranges of visible light (400 to 700 nm). As the light availability changes seasonally, the structure of phytoplankton changes as well. Some genera, such as Microcystis, are adapted to low light intensity at 550–650 nm, therefore high values of Kd in this range would indicate the dominance of Microcysts. Other genera, such as Aulacoseira, are highly adapted to harvesting blue-green light with higher intensity and probably grow in lakes with lower concentrations of colored dissolved organic matter that highly absorbs blue light (405–498). These findings are an important step to describing phytoplankton communities using orbital data in tropical freshwater floodplains. Furthermore, this approach can be used with biodiversity indexes to access phytoplankton diversity in these environments.

ABSTRACT In a particular region within western Amazonia, Amazonian manatees (Trichechus inunguis) live in a floodplain environment that becomes inhospitable for them during the annual low-water season. To flee from it, they undergo a dangerous migration to a refuge while water levels are dropping fast. Our aim was to better understand the role of depth variation in this migratory process. We analyzed the sole tracking data on wild manatees (n=10 males), 30 years of Landsat images, a 14-year hydrograph and a 3-D bathymetric model. Migratory routes contained shallower segments, here called 'migratory bottlenecks', which dried out at the end of most lowering-water seasons, blocking the passage to the refuge. Manatees began migrating just in time to traverse the bottlenecks furthest away, suggesting they fine-tuned their departure so as to maximize time within the foraging home range without compromising safety. They apparently achieved this by estimating depth at the bottlenecks. Moreover, a bottleneck was created in >15 years, illustrating the environment's dynamism and the challenge this imposes upon manatees. Our results are probably generalizable to most of the species' range. We contend manatees possess an updatable cognitive map of their environment and are behaviorally plastic. Current dam-building plans, if implemented, would create more bottlenecks and make flooding less predictable, increasing manatee mortality from unsuccessful migrations. It would also partition the species into small populations, each prone to short-term extinction. The natural outcome would be the second species-level collapse. Economic growth should not come at the expense of the extinction of the iconic manatee.

Due to increasing algae bloom occurrence and water degradation on a global scale, there is a demand for water quality monitoring systems based on remote sensing imagery. This paper describes the scientific, theoretical, and methodological background for creating a cloud-computing interface on Google Earth Engine (GEE) which allows end-users to access algae bloom related products with high spatial (30 m) and temporal (~5 day) resolution. The proposed methodology uses Sentinel-2 images corrected for atmospheric and sun-glint effects to generate an image collection of the Normalized Difference Chlorophyll-a Index (NDCI) for the entire time-series. NDCI is used to estimate both Chl-a concentration, based on a non-linear fitting model, and Trophic State Index (TSI), based on a tree-decision model classification into five classes. Once the Chl-a and TSI algorithms had been calibrated and validated they were implemented in GEE as an Earth Engine App, entitled Algae Bloom Monitoring Application (AlgaeMAp). AlgaeMAp is the first online platform built within the GEE platform that offers high spatial resolution of water quality parameters. The App benefits from the huge processing capability of GEE that allows any user with internet access to easily extract detailed spatial (30 m) and long temporal Chl-a and TSI information (from August 2015 and with images every 5 days) throughout the most important reservoirs in the State of São Paulo/Brazil. The application will be adapted to extend to other relevant areas in Latin America.

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. = O monitoramento da água nos dias atuais é essencial para a sustentabilidade e para a melhor gestão dos recursos hídricos. O uso de dados de sensoriamento remoto é relevante, uma vez que permite a avaliação de problemas dinâmicos em sistemas aquáticos, tais como a eutrofização de corpos de água e dos sedimentos em suspensão. Objetivou-se estimar as concentrações de clorofila-a em reservatório da região semiárida do Brasil, usando dados simulados de sensor orbital, como suporte à gestão dos recursos hídricos. A área de estudo corresponde ao açude Orós, no estado do Ceará. As amostras de água para análise da clorofila-a e as medições da radiância espectral do sistema aquático foram coletadas em 20 pontos. As medidas de radiância foram realizadas utilizando um espectrorradiômetro. Os dados foram coletados nos meses de junho e agosto de 2011. O modelo usando três bandas (7, 9 e 10) do sensor MERIS apresentou R2 igual a 0,84. Para o modelo de duas bandas (7 e 9), o valor de R2 foi de 0,85. As águas do reservatório Orós foram todas classificadas como eutróficas. O principal componente opticamente ativo modelando a forma dos espectros foi clorofila-a. Os modelos apresentaram um erro médio absoluto (EMA) de 3,45 e 3,61 μg L-1, respectivamente, para os modelos de três e de duas bandas. Os modelos apresentaram coeficientes de determinação altos, ou seja, as simulações mostram a viabilidade de se estimar as concentrações de clorofila-a a partir dos dados do sensor orbital MERIS.

ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.

The diffuse attenuation coefficient of downwelling irradiance (Kd) is an essential parameter for inland waters research by remotely sensing the water transparency. Lately, Kd semi-analytical algorithms substituted the empirical algorithms widely employed. The purpose of this research was to reparametrize a semi-analytical algorithm to estimate Kd and then apply it to a Sentinel-2 MSI time-series (2017–2019) for the Três Marias reservoir, Brazil. The results for the Kd semi-analytical reparametrization achieved good accuracies, reaching mean absolute percentage errors (MAPE) for bands B2, B3 and B4 (492, 560 and 665 nm), lower than 21% when derived from in-situ remote sensing reflectance (Rrs), while for MSI Data, a derived MAPE of 12% and 38% for B2 and B3, respectively. After the application of the algorithm to Sentinel-2 images time-series, seasonal patterns were observed in the results, showing high Kd values at 492 nm during the rainy periods, mainly in the tributary mouths, possibly due to an increase in the surface runoff and inflows and outflow rates in the reservoir watershed.

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).

We determined the filtered tree species pool of Amazonian wetland forests, based on confirmed occurrence records, to better understand how tree diversity in wetland environments compares to tree diversity in the entire Amazon region. The tree species pool was determined using data from two main sources: 1) a compilation of published tree species lists plus one unpublished list of our own, derived from tree plot inventories and floristic surveys; 2) queries on botanical collections that include Amazonian flora, curated by herbaria and available through the SpeciesLink digital biodiversity database. We applied taxonomic name resolution and determined sample-based species accumulation curves for both datasets, to estimate sampling effort and predict the expected species richness using Chao's analytical estimators. We report a total of 3 615 valid tree species occurring in Amazonian wetland forests. After surveying almost 70 years of research efforts to inventory the diversity of Amazonian wetland trees, we found that 74% these records were registered in published species lists (2 688 tree species). Tree species richness estimates predicted from either single dataset underestimated the total pooled species richness recorded as occurring in Amazonian wetlands, with only 41% of the species shared by both datasets. The filtered tree species pool of Amazonian wetland forests comprises 53% of the 6 727 tree species taxonomically confirmed for the Amazonian tree flora to date. This large proportion is likely to be the result of significant species interchange among forest habitats within the Amazon region, as well as in situ speciation processes due to strong ecological filtering. The provided tree species pool raises the number of tree species previously reported as occurring in Amazonian wetlands by a factor of 3.2.

This work proposes a trophic state index based on the remote sensing retrieval of chlorophyll-α concentration. For that, in situ Bidirectional Reflectance Factor (BRF) data acquired in the Ibitinga reservoir were resampled to match Landsat/TM spectral simulated bands (TM_sim bands) and used to run linear correlation with concurrent measurements of chlorophyll-α concentration. Monte Carlo simulation was then applied to select the most suitable model relating chlorophyll-α concentration and simulated TM/Landsat reflectance. TM4_sim/TM3_sim ratio provided the best model with a R2 value of 0.78. The model was then inverted to create a look-up-table (LUT) relating TM4_sim/TM3_sim ratio intervals to chlorophyll-α concentration trophic state classes covering the entire range measured in the reservoir. Atmospheric corrected Landsat TM images converted to surface reflectance were then used to generate a TM4/TM3 ratio image. The ratio image frequency distribution encompassed the range of TM4_sim/TM3_sim ratio indicating agreement between in situ and satellite data and supporting the use of satellite data to map chlorophyll- concentration trophic state distribution in the reservoir. Based on that, the LUT was applied to a Landsat/TM ratio image to map the spatial distribution of chlorophyll- trophic state classes in Ibitinga reservoir. Despite the stochastic selection of TM4_sim/TM3_sim ratio as the best input variable for modeling the chlorophyll-α concentration, it has a physical basis: high concentration of phytoplankton increases the reflectance in the near-infrared (TM4) and decreases the reflectance in the red (TM3). The band ratio, therefore, enhances the relationship between chlorophyll- concentration and remotely sensed reflectance.

AIM: This paper describes an experiment carried out to evaluate in vivo fluorescence (IVF) as an alternative method for chlorophyll-a estimation in optically complex aquatic environment (Amazon floodplain lakes) METHODS: The experiment consisted of collecting in situ measurements at 26 sampling stations distributed throughout Curuai floodplain lakes. For each sampling station the following parameters were measured: temperature, turbidity, depth, Secchi depth, chlorophyll-a (Chl-a) concentration, total suspended solids (TSS) and dissolved organic carbon (DOC), concurrently with several transects of IVF. Two methods were tested for quantifying the fluorescence measurement to be used as input for the chlorophyll-a estimates: instantaneous IFV and average IVF. Global and regional models were tested and assessed by analyzing optically active components (Chl-a, DOC and TSS) of the water. RESULTS: Regardless of fluorescence estimating method, the results indicate that it was not possible to fit a global model for estimating Chl-a from IVF for all the lakes in the Curuai floodplain. Regional models provided contrasting results according to the concentration of optically active components. The best results were observed for aquatic systems with a single dominant component homogenously distributed throughout the lake. The results highlight the influence of the ratios Chl-a/TSS, Chl-a/DOC and Phaephytin/Chl-a in the relationship between IVF and chlorophyll concentration. CONCLUSIONS: It was not possible to develop a global model to account for the entire region of Curuai floodplain. The search for regional models provided insights on the main factors affecting the relationship between IVF and Chl-a concentration. Nevertheless this work reinforces the great potential of fluorometry technique, since even with a small number of samples it was possible to set a good model in the main lake of the Curuai floodplain. In spite the fact that this is not an accurate method, it is very useful for assessing the chlorophyll spatial distribution with relatively low cost. These possibilities are very interesting in the execution of field missions in the Amazon region.OBJETIVO: Este trabalho descreve os experimentos realizados para avaliar as medidas de fluorescência in vivo (IVF) em um ambiente aquático opticamente complexo (planície de inundação amazônica), como método alternativo para a quantificação da clorofila-a na água. MÉTODOS: Foram coletados parâmetros de qualidade da água em 26 estações amostrais distribuídas em diversos lagos da planície de inundação de Curuai: temperatura, pH, turbidez, condutividade, profundidade, transparência ao disco de Secchi, concentração de clorofila-a (Chl-a), total de sólidos em suspensão (TSS) e carbono orgânico dissolvido (DOC) simultaneamente a quilômetros de transectos de IVF. Dois métodos de determinação do valor de fluorescência foram testados para o ajuste de modelos de estimativa da concentração de clorofila: fluorescência instantânea e fluorescência média. Também foram testados um modelo global e modelos regionais, os quais foram analisados em termos dos componentes opticamente ativos na água (Chl-a, DOC e TSS). RESULTADOS: Os resultados indicam que independentemente do método de estimativa de fluorescência empregado, não foi possível ajustar um modelo global para a planície de Curuai. Os modelos regionais apresentaram resultados contrastantes, de acordo com a concentração dos componentes opticamente ativos. Melhores resultados foram observados nos sistemas aquáticos com um único componente dominante, distribuído homogeneamente pelo respectivo lago. Os resultados destacam a influência das razões Chl-a/TSS, Chl-a/DOC e Feofitina/Chl-a no ajuste entre a IVF e a Chl-a. CONCLUSÕES: Não foi possível ajustar um modelo global para a planície de Curuai através de medidas de IVF. Entretanto, a busca por modelos regionais forneceu informações sobre os principais fatores que afetam a relação entre a IVF e a Chl-a. Dessa forma, este trabalho reforça o grande potencial da fluorometria, pois mesmo com um baixo número de amostras foi possível estabelecer um bom modelo no principal lago da planície. Ainda que a técnica não possa ser considerada extremamente precisa, ela é útil para avaliar o padrão de variação espacial da clorofila, com baixo custo. Estas possibilidades são muito interessantes na realização de missões de campo na bacia amazônica.

AIM: Water temperature plays an important role in ecological functioning and in controlling the biogeochemical processes of the aquatic system. Conventional water quality monitoring is expensive and time consuming. It is particularly challenging for large water bodies. Conversely, remote sensing can be considered a powerful tool to assess important properties of aquatic systems because it provides synoptic and frequent data acquisition over large areas. The objective of this study was to analyze time series of surface water temperature and heat flux to advance the understanding of temporal variations in a hydroelectric reservoir. METHOD: MODIS water-surface temperature (WST) level 2, 1 km nominal resolution data (MOD11L2, version 5) were used. All available clear-sky MODIS/Terra images from 2003 to 2008 were used, resulting in a total of 786 daytime and 473 nighttime images. Time series of surface water temperature was obtained computing the monthly mean in a 3×3 window of three reservoir selected sites: 1) near the dam, 2) at the centre of the reservoir and 3) in the confluence of the rivers. In-situ meteorological data from 2003 to 2008 were used to calculate surface energy budget time series. Cross-wavelet, coherence and phase analysis were carried out to compute the correlation between daytime and nighttime surface water temperatures and the computed heat fluxes. RESULTS: The monthly mean of the day-time WST shows lager variability than the night-time WST. All time series (daytime and nighttime) have a cyclical pattern, passing for a minimum (June - July) and a maximum (December and January). Fourier and the Wavelet Analysis were applied to analyze this cyclical pattern. The daytime time series, presents peaks in 4.5, 6 12 and 36 months and the nighttime WST shows the highest spectral density at 12, 6, 3 and 2 months. The multiple regression analysis shows that for daytime WST, the heat flux terms explain 89% of the annual variation (RMS = 0.89 °C, p < 0.0013). For nighttime, the heat flux terms explain 94% (RMS = 0.53 °C, p < 0.0002). CONCLUSION: The daytime WST and shortwave radiation presents a good agreement for periods of 6 (with shortwave retarded) and 12 months (with shortwave advanced); For nighttime WST and longwave the good agreement is present for 1, 3, 6 and 12 months, all with longwave advanced in relation to WST.OBJETIVO: A temperatura da água possui uma importante função ecológica e no controle de processos biogeoquímicos em um corpo d'água. O monitoramento convencional da qualidade da água geralmente é dispendioso e que consome muito tempo. Este é um problema particularmente interessante quando se esta estudando grandes áreas. Entretanto, ferramentas como o sensoriamento remoto pode ser considerado adequado no estudo destas áreas. O objetivo deste estudo foi analisar séries temporais de temperatura da água e dos fluxos de calor para melhorar o entendimento de suas variações temporais em reservatório hidrelétricos. MÉTODO: Neste trabalho, dados do sensor MODIS/Terra de temperatura da superfície da água (TSA) nível 2, 1 km de resolução nominal (MOD11L2, versão 5) foram utilizados. Todas as imagens, livres de nuvem, do MODIS/Terra de 2003 a 2008 foram utilizadas, resultando em 786 imagens tomadas durante o dia e 473 durante a noite. As séries temporais de temperatura da superfície da água foram obtidas por meio de médias mensais e janelas de 3×3 pixels em três áreas distintas do reservatório: 1) próximo a barragem, 2) região central do reservatório e 3) na confluência dos rios. Dados meteorológicos foram utilizados para a estimativa do balanço de calor no reservatório para os anos de 2003 a 2008. Uma análise de correlação entre as séries temporais de temperatura da água estimadas durante o dia e noite com os fluxos de calor. Os fluxos mais bem correlacionados foram verificados quanto sua ciclicidade com a variação de temperatura, por meio do uso do algoritmo de wavelet cruzada, coerência e fase. RESULTADOS: A média mensal de TSA diurna mostrou uma maior variabilidade se comparada com a série temporal de TSA noturna. Além disto, apresentam um ciclo sazonal bem marcado, passando por um mínimo durante os meses de Junho e Julho e um máximo nos meses de Dezembro e Janeiro. Para analisar este padrão, uma análise de Fourier e de Wavelet foi realizada. As séries temporais de TSA diurnas mostraram variabilidades cíclicas em 4,5, 6, 12 e 36 meses e para as noturnas em 2, 3, 6 e 12. A análise de correlação mostrou que os fluxos de calor correlacionados com a TSA diurna explicam 89% (RMS = 0.89 °C, p < 0.0013) e noturna 94% (RMS = 0.53 °C, p < 0.0002). CONCLUSÃO: A série temporal de TSA diurna e a radiação de onda curta apresentam picos de variabilidade centradas em 6 meses (com certo atraso de variabilidade por parte da radiação de onda curta) e 12 meses (com variabilidade avançada por parte da radiação de onda curta). Para a série temporal de TSA noturna, existe concordância com a radiação de onda longa nos períodos de 1, 3, 6 e 12 meses.

AIM: This paper examines the effect of the extreme water level change in 2009 on the structure and diversity of the phytoplankton communities in lakes of the Lower Amazon Floodplain, and compares it to phytoplankton community structure data reported in the literature for 2002 and 2003 high water periods, closer to the normal hydrological conditions. METHODS: Sub-surface integrated water samples for phytoplankton and chlorophyll-a analyses were collected during high and low water phases in 2009. Water temperature (°C), pH, turbidity (NTU) and electrical conductivity (µS.m-1) were measured, and the Shannon diversity index was calculated. RESULTS: The results showed striking differences in taxonomic composition between phases (high and low) and also between normal (2002 and 2003) and extreme (2009) hydrological conditions, all related to the flood pulse intensity. CONCLUSIONS: Extreme water level fluctuations can result in shifts in phytoplankton community structure and diversity. This work represents a valuable contribution to phytoplankton research since presents the community structure under extreme hydrological events in the Amazon floodplain.OBJETIVO: Esse trabalho investiga o efeito da extrema variação da mudança do nível da água em 2009 na estrutura e diversidade das comunidades de fitoplâncton nos lagos da planície de inundação do Baixo Amazonas,e compara estes resultados à estrutura da comunidade de fitoplâncton reportada na literatura para os períodos de água alta em 2002 e 2003, próximos a condições hidrológicas normais. MÉTODOS: Amostras de água da sub-superfície foram coletadas para a análise de fitoplâncton e clorofila-a nos períodos de água alta e baixa em 2009. Temperatura da água (°C), pH, turbidez (NTU) e condutividade elétrica (µS.m-1) foram medidas, e o índice de diversidade de Shannon calculado. RESULTADOS: Os resultados revelaram diferenças marcantes na composição taxonômica entre fases da inundação (alta e baixa) e também entre eventos hidrológicos normais (2002 e 3003) e extremos (2009), todos relacionados com a intensidade do pulso de inundação. CONCLUSÕES: Flutuações extremas do nível da água podem resultar em alterações na estrutura da comunidade e na diversidade. Esse trabalho é uma contribuição valiosa a pesquisa em fitoplâncton, pois apresenta a estrutura da comunidade sob condições hidrológicas extremas na planície de inundação Amazônica.

AIM: This paper examines the spatial and temporal variation of limnological characteristics of floodplain lakes in the Solimões and Japurá confluence, an undisturbed region - the Mamirauá Sustainable Development Reserve (MSDR); METHODS: We analyzed surface temperature, conductivity, pH, dissolved oxygen, turbidity and transparency, and surface water samples were collected for determination of suspended inorganic and organic matter, chlorophyll-a, pheophytin, total nitrogen, total phosphorus, organic and inorganic carbon, in two phases of the hydrograph stage, 2009 high water phase, 2008, 2009 and 2010 low water phases; RESULTS: The results showed that the studied water bodies have high variability in all measured variables: a) between hydrograph phases; b) among main rivers; and c) between opposite margins of Japurá River; CONCLUSIONS: This shows the remarkable influence of the flood pulse and the primary water source on the limnology of this system. The monitoring of physical and chemical limnological variables in Mamirauá will serve as future reference for comparison with disturbed areas, such as the Lower Amazon, and as a baseline for modeling the effects of climate change and anthropogenic influences on Amazon aquatic ecosystem.OBJETIVO: Esse trabalho investiga a variação temporal e espacial de algumas características limnológicas dos lagos da planície de inundação da região de confluência dos Rios Japurá e Solimões, onde está localizada a Reserva de Desenvolvimento Sustentável Mamirauá (RDSM); MÉTODOS: Analisaram-se temperatura, condutividade, pH, oxigênio dissolvido, turbidez e transparência da água em três profundidades (superfície, Secchi e no limite da zona fótica) e coletadas amostras de água na superfície para a determinação de material orgânico e inorgânico em suspensão, clorofila-a, feofitina, nitrogênio e fósforo total, carbono orgânico e inorgânico dissolvido, em duas fases da hidrógrafa, água alta em 2009, e água baixa em 2008, 2009 e 2010; RESULTADOS: Os resultados mostraram que as variáveis medidas possuem uma alta variabilidade nos corpos d'água na região de estudo: a) entre as fases da hidrógrafas; b) entre os rios principais; e c) entre as margens opostas do Rio Japurá, mostrando a importância do pulso de inundação na variação dos parâmetros físicos e químicos e ainda a em relação ao rio principal de alimentação; CONCLUSÕES: O monitoramento dos parâmetros físicos e químicos em Mamirauá servirá como futura referência para comparação com outras regiões menos preservadas, como o Baixo Amazonas, e ainda como linha de base para modelos sobre efeitos das mudanças climáticas e influências antropogênicas no ecossistema aquático Amazônico.

Although mining plays an important role for the economy of the Amazon, little is known about its attributes such as area, type, scale, and current status as well as socio/environmental impacts. Therefore, we first propose a low time-consuming and high detection accuracy method for mapping the current mining areas within 13 regions of the Brazilian Amazon using Sentinel-2 images. Then, integrating the maps in a GIS (Geography Information System) environment, mining attributes for each region were further assessed with the aid of the DNPM (National Department for Mineral Production) database. Detection of the mining area was conducted in five main steps. (a) MSI (MultiSpectral Instrument)/Sentinel-2A (S2A) image selection; (b) definition of land-use classes and training samples; (c) supervised classification; (d) vector editing for quality control; and (e) validation with high-resolution RapidEye images (Kappa = 0.70). Mining areas derived from validated S2A classification totals 1084.7 km2 in the regions analyzed. Small-scale mining comprises up to 64% of total mining area detected comprises mostly gold (617.8 km2), followed by tin mining (73.0 km2). The remaining 36% is comprised by industrial mining such as iron (47.8), copper (55.5) and manganese (8.9 km2) in Carajás, bauxite in Trombetas (78.4) and Rio Capim (48.5 km2). Given recent events of mining impacts, the large extension of mining areas detected raises a concern regarding its socio-environmental impacts for the Amazonian ecosystems and for local communities.

Water composition undergoes complex spatial and temporal variations throughout the central Amazon floodplain. This study analyzed the spectral mixtures of the optically active substances (OASs) in water with spaceborne hyperspectral images. The test site was located upstream the confluence of Amazon (white water) and Tapajós (clear-water) rivers, where two Hyperion images were acquired from the Earth Observing One (EO-1) satellite. The first image was acquired on September 16, 2001, during the falling water period of the Amazon River. The second image was acquired on June 23, 2005, at the end of the high water period. The images were pre-processed to remove stripes of anomalous pixels, convert radiance-calibrated data to surface reflectance, mask land, clouds and macrophytes targets, and spectral subset the data within the range of 457-885nm. A sequential procedure with the techniques Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and n-dimensional visualization of the MNF feature space was employed to select end-members from both images. A single set of end-members was gathered to represent the following spectrally unique OASs: clear-water; dissolved organic matter; suspended sediments; and phytoplankton. The Linear Spectral Unmixing algorithm was applied to each Hyperion image in order to map the spatial distribution of these constituents, in terms of sub-pixel fractional abundances. Results showed three patterns of changes in the water quality from high to falling flood periods: decrease of suspended inorganic matter concentration in the Amazon River; increase of suspended inorganic matter and phytoplankton concentrations in varzea lakes; and increase of phytoplankton concentration in the Tapajós River.

Water composition undergoes complex spatial and temporal variations throughout the central Amazon floodplain. This study analyzed the spectral mixtures of the optically active substances (OASs) in water with spaceborne hyperspectral images. The test site was located upstream the confluence of Amazon (white water) and Tapajós (clear-water) rivers, where two Hyperion images were acquired from the Earth Observing One (EO-1) satellite. The first image was acquired on September 16, 2001, during the falling water period of the Amazon River. The second image was acquired on June 23, 2005, at the end of the high water period. The images were pre-processed to remove stripes of anomalous pixels, convert radiance-calibrated data to surface reflectance, mask land, clouds and macrophytes targets, and spectral subset the data within the range of 457-885nm. A sequential procedure with the techniques Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and n-dimensional visualization of the MNF feature space was employed to select end-members from both images. A single set of end-members was gathered to represent the following spectrally unique OASs: clear-water; dissolved organic matter; suspended sediments; and phytoplankton. The Linear Spectral Unmixing algorithm was applied to each Hyperion image in order to map the spatial distribution of these constituents, in terms of sub-pixel fractional abundances. Results showed three patterns of changes in the water quality from high to falling flood periods: decrease of suspended inorganic matter concentration in the Amazon River; increase of suspended inorganic matter and phytoplankton concentrations in varzea lakes; and increase of phytoplankton concentration in the Tapajós River.

This paper presents a methodology for processing and applying high resolution bathymetric data acquired with a Lowrance-480M ecosounder in the Amazon floodplain supported by Landast/TM images for planning and executing the survey. 4600 km of transects were processed semi-automatically and integrated into a georeferenced database. A digital elevation model with 15 m horizontal resolution and 1 cm vertical resolution was generated for the floodplain. The changes in inundated area and volume of water on the floodplain were estimated. Regression models to predict flood area and water stored volume from water level were constructed. The results of this research show that water level and flooded area mapped from images are good enough for estimating water stored volume in the Lago Grande de Curuai.

A construção da hidroelétrica de Tucuruí, no sudeste do Estado do Pará, Brasil, em 1981, impôs grandes mudanças ambientais, desmatamentos e migração para a região. O objetivo deste trabalho é verificar a influência destas mudanças na ocorrência da malária no Município de Jacundá, Pará, Brasil, utilizando-se técnicas de sensoriamento remoto e sistemas de informações geográficas. Os parâmetros utilizados para a construção dos mapas foram: distância das estradas, classe agrossilvopastoril, distância de coleções hídricas (rios, igarapés e do reservatório) e da área urbana do município. Neste estudo, verificou-se o caráter epidêmico da malária a partir da construção da barragem de Tucuruí. Sugere-se que o padrão sazonal da incidência está relacionado com o período de maior estabilidade das margens do reservatório e ocorrência de áreas alagadas, além de maior exposição de trabalhadores na época de colheita na região. Foi observado que a distribuição dos casos está relacionada com as formas de uso e ocupação da terra, principalmente em áreas de maior influência das estradas, locais onde se concentra grande parte da população.Construction of the Tucuruí hydroelectric dam in Southeast Pará State, Brazil, in 1981, caused enormous environmental changes, deforestation, and human migration to the region. This study focuses on the influence of these changes and the appearance of malaria in the municipality of Jacundá, Pará, using remote sensing and geographic information systems. The variables used to construct maps were distances from roads, farming areas, rivers, the dam, streams, and the urban area. This study confirmed the elevation of malaria to the epidemic level since the construction of the Tucuruí dam. The study suggests that a seasonal pattern of malaria incidence is associated with the flooding season and exposure of workers during harvest. Malaria cases were related to the form of land occupation, especially in more densely populated areas.

O presente trabalho demonstra a aplicabilidade de imagens de sensoriamento remoto e de métodos de processamento de imagens digitais para definição de locais adequados à instalação de sistemas telemétricos de monitoramento de variáveis ambientais em sistemas aquáticos, localizados em regiões de difícil acesso. A técnica consiste essencialmente da aplicação de operações Booleanas entre mapas da pluma do Rio Amazonas e de zonas inundadas do Lago de Curuai em diferentes etapas do ciclo hidrológico. A localização exata para o sistema de monitoramento telemétrico será vital para o desenvolvimento de modelos de troca de gases traço entre a planície de inundação Amazônica e a atmosfera.The present work illustrates the application of remote sensing and image processing methods to define appropriate sites for installing buoy moored telemetric systems at the surface of Amazon floodplain lakes for long-term limnologic-micrometeorologic monitoring. The technique consists essentially of Boolean operations over Amazon plume maps and historic inundation of the Curuai Lake at distinct stages of the hydrologic cycle. The precise location for the long-term monitoring is vital to the development of models concerning air-water trace gas exchange in the Amazon floodplains.

Este artigo se propõe a apresentar exemplos de questões científicas que puderam ser respondidas no contexto do Projeto LBA (Large Sale Biosphere-Atmosphere Experiment in Amazonia) graças à contribuição de informações derivadas de sensoriamento remoto. Os métodos de sensoriamento remoto permitem integrar informações sobre os vários processos físicos e biológicos em diferentes escalas de tempo e espaço. Nesse artigo, são enfatizados aqueles avanços de conhecimento que jamais seriam alcançados sem a concorrência da informação derivada de sensoriamento.This paper aims to assess the contribution of remote sensing technology in addressing key questions raised by the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The answers to these questions foster the knowledge on the climatic, biogechemical and hydrologic functioning of the Amazon, as well as on the impact of human activities at regional and global scales. Remote sensing methods allow integrating information on several processes at different temporal and spatial scales. By doing so, it is possible to perceive hidden relations among processes and structures, enhancing their teleconnections. Key advances in the remote sensing science are summarized in this article, which is particularly focused on information that would not be possible to be retrieved without the concurrence of this technology.

Técnicas de sensoriamento remoto são fundamentais para o monitoramento das mudanças de uso da terra, principalmente em áreas extensas como a Amazônia. O mapeamento de uso da terra, geralmente é realizado por métodos de classificação manual ou digital pixel a pixel, os quais consomem muito tempo. Este estudo aborda a aplicação do modelo linear de mistura em uma imagem Landsat-TM segmentada para o mapeamento das classes de uso da terra na região do reservatório de Tucuruí-PA para os anos de 1996 e 2001.Remote sensing techniques are mandatory for monitoring land use changes in large areas such as the Amazon. Land use mapping is usually performed by both manual and digital pixel based classification methods which are cost and time-consuming. In this study an image segmentation approach is applied to unmix TM-Landsat images for mapping land use classes in Tucuruí-PA reservoir region to 1996 and 2001.

Artisanal and Small-scale Gold Mining (ASGM) within the Amazon region has created several environmental impacts, such as mercury contamination and changes in water quality due to increased siltation. This paper describes the effects of water siltation on the underwater light environment of rivers under different levels of gold mining activities in the Tapajós River Basin. Furthermore, it investigates possible impacts on the phytoplankton community. Two field campaigns were conducted in the Tapajós River Basin, during high water level and during low water level seasons, to measure Inherent and Apparent Optical Properties (IOPs, AOPs), including scattering (b) and absorption (a) coefficients and biogeochemical data (sediment content, pigments, and phytoplankton quantification). The biogeochemical data was separated into five classes according to the concentration of total suspended solids (TSS) ranging from 1.8 mg·L−1 to 113.6 mg·L−1. The in-water light environment varied among those classes due to a wide range of concentrations of inorganic TSS originated from different levels of mining activities. For tributaries with low or no influence of mining tailings (TSS up to 6.8 mg·L−1), waters are relatively more absorbent with b:a ratio of 0.8 at 440 nm and b660 magnitude of 2.1 m−1. With increased TSS loadings from mining operations (TSS over 100 mg·L−1), the scattering process prevails over absorption (b:a ratio of 10.0 at 440 nm), and b660 increases to 20.8 m−1. Non-impacted tributaries presented a critical depth for phytoplankton productivity of up to 6.0 m with available light evenly distributed throughout the spectra. Whereas for greatly impacted waters, attenuation of light was faster, reducing the critical depth to about 1.7 m, with most of the available light comprising of red wavelengths. Overall, a dominance of diatoms was observed for the upstream rivers, whereas cyanobacteria prevailed in the low section of the Tapajós River. The results suggest that the spatial and temporal distribution of phytoplankton in the Tapajós River Basin is not only a function of light availability, but rather depends on the interplay of factors, including flood pulse, water velocity, nutrient availability, and seasonal variation of incoming irradiance. Ongoing research indicates that the effects of mining tailings on the aquatic environment, described here, are occurring in several rivers within the Amazon River Basin.

Satellite data provide the only viable means for extensive monitoring of remote and large freshwater systems, such as the Amazon floodplain lakes. However, an accurate atmospheric correction is required to retrieve water constituents based on surface water reflectance ( R W ). In this paper, we assessed three atmospheric correction methods (Second Simulation of a Satellite Signal in the Solar Spectrum (6SV), ACOLITE and Sen2Cor) applied to an image acquired by the MultiSpectral Instrument (MSI) on-board of the European Space Agency’s Sentinel-2A platform using concurrent in-situ measurements over four Amazon floodplain lakes in Brazil. In addition, we evaluated the correction of forest adjacency effects based on the linear spectral unmixing model, and performed a temporal evaluation of atmospheric constituents from Multi-Angle Implementation of Atmospheric Correction (MAIAC) products. The validation of MAIAC aerosol optical depth (AOD) indicated satisfactory retrievals over the Amazon region, with a correlation coefficient (R) of ~0.7 and 0.85 for Terra and Aqua products, respectively. The seasonal distribution of the cloud cover and AOD revealed a contrast between the first and second half of the year in the study area. Furthermore, simulation of top-of-atmosphere (TOA) reflectance showed a critical contribution of atmospheric effects (>50%) to all spectral bands, especially the deep blue (92%–96%) and blue (84%–92%) bands. The atmospheric correction results of the visible bands illustrate the limitation of the methods over dark lakes ( R W < 1%), and better match of the R W shape compared with in-situ measurements over turbid lakes, although the accuracy varied depending on the spectral bands and methods. Particularly above 705 nm, R W was highly affected by Amazon forest adjacency, and the proposed adjacency effect correction minimized the spectral distortions in R W (RMSE < 0.006). Finally, an extensive validation of the methods is required for distinct inland water types and atmospheric conditions.

An innovative remote sensing approach that combines land-use change and water quality information is proposed in order to investigate if Artisanal and Small-scale Gold Mining (ASGM) area extension is associated with water siltation in the Tapajós River Basin (Brazil), containing the largest small-scale gold mining district in the world. Taking advantage of a 40-year period of the multi-satellite imagery archive, the objective of this paper is to build a normalized time-series in order to evaluate the influence of temporal mining expansion on the water siltation data (TSS, Total Suspended Solids concentration) derived from previous research. The methodological approach was set to deliver a full characterization of the ASGM expansion from its initial stages in the early 1970s to the present. First, based on IRS/LISSIII images acquired in 2012, the historical Landsat image database (1973–2001) was corrected for radiometric and atmospheric effects using dark vegetation as reference to create a normalized time-series. Next, a complete update of the mining areas distribution in 2012 derived from the TerraClass Project (an official land-use classification for the Brazilian Amazon) was conducted having IRS/LISSIII as the base map with the support of auxiliary data and vector editing. Once the ASGM in 2012 was quantified (261.7 km2) and validated with photos, a reverse classification of ASGM in 2001 (171.7 km2), 1993 (166.3 km2), 1984 (47.5 km2), and 1973 (15.4 km2) with the use of Landsat archives was applied. This procedure relies on the assumption that ASGM changes in the land cover are severe and remain detectable from satellite sensors for decades. The mining expansion area over time was then combined with the (TSS) data retrieved from the same atmospherically corrected satellite imagery based on the literature. In terms of gold mining expansion and water siltation effects, four main periods of ASGM activities were identified in the study area: (i) 1958–1977, first occurrence of mining activities and low water impacts; (ii) 1978–1993, introduction of low-budget mechanization associated with very high gold prices resulting in large mining area expansion and high water siltation levels; (iii) 1994–2003, general recession of ASGM activities and exhaustion of easy-access gold deposits, resulting in decreased TSS; (iv) 2004 to present, intensification of ASGM encouraged by high gold prices, resulting in an increase of TSS.

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.

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' 20'' e 23° 57' 26'' Sul e 46° 39' 27'' e 48° 34' 52'' 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.

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.

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.