Unmixing water and mud: Characterizing diffuse boundaries of subtidal mud banks from individual satellite observations

This is the final version. Available from Elsevier via the DOI in this record. Mapping of subtidal banks in mud-dominated coastal systems is crucial as they influence not only shoreline and ecosystem dynamics but also economic activities and livelihoods of local communities. Due to associated spatiotemporal variations in suspended particulate matter concentrations, subtidal mudbanks are often confined by diffuse and rapidly changing boundaries. To avoid inaccurate representations of these mudbanks in remote sensing images, it is necessary to unmix distinctive reflectance signals into representative landcover fractions. Yet, extracting mud fractions, in order to characterize such diffuse boundaries, is challenging because of the spectral similarity between subtidal- and intertidal features. Here we show that an unsupervised decision tree, used to derive spatially explicit and spectrally coherent image endmembers, facilitates robust linear spectral unmixing on an image-to-image basis, enabling the separation of these coastal features. We found that resulting abundance maps represent cross-shore gradients of vegetation, water and mud fractions present at the coast of Suriname. Furthermore, we confirmed that it is possible to separate land, water and an initial estimate of intertidal zones on individual images. Thus, spectral signatures of end-member candidates, determined from relevant index histograms within these initial estimates, are consistent. These results demonstrate that spectral information from well-defined spatial neighbourhoods facilitates the detection of diffuse boundaries of mudbanks with a spectral unmixing approach.NWO WOTR

Development of a spectral unmixing procedure using a genetic algorithm and spectral shape

xvi, 85 leaves : ill. (chiefly col.) ; 29 cmSpectral unmixing produces spatial abundance maps of endmembers or ‘pure’ materials using sub-pixel scale decomposition. It is particularly well suited to extracting a greater portion of the rich information content in hyperspectral data in support of real-world issues such as mineral exploration, resource management, agriculture and food security, pollution detection, and climate change. However, illumination or shading effects, signature variability, and the noise are problematic. The Least Square (LS) based spectral unmixing technique such as Non-Negative Sum Less or Equal to One (NNSLO) depends on “shade” endmembers to deal with the amplitude errors. Furthermore, the LS-based method does not consider amplitude errors in abundance constraint calculations, thus, often leads to abundance errors. The Spectral Angle Constraint (SAC) reduces the amplitude errors, but the abundance errors remain because of using fully constrained condition. In this study, a Genetic Algorithm (GA) was adapted to resolve these issues using a series of iterative computations based on the Darwinian strategy of ‘survival of the fittest’ to improve the accuracy of abundance estimates. The developed GA uses a Spectral Angle Mapper (SAM) based fitness function to calculate abundances by satisfying a SAC-based weakly constrained condition. This was validated using two hyperspectral data sets: (i) a simulated hyperspectral dataset with embedded noise and illumination effects and (ii) AVIRIS data acquired over Cuprite, Nevada, USA. Results showed that the new GA-based unmixing method improved the abundance estimation accuracies and was less sensitive to illumination effects and noise compared to existing spectral unmixing methods, such as the SAC and NNSLO. In case of synthetic data, the GA increased the average index of agreement between true and estimated abundances by 19.83% and 30.10% compared to the SAC and the NNSLO, respectively. Furthermore, in case of real data, GA improved the overall accuracy by 43.1% and 9.4% compared to the SAC and NNSLO, respectively

A Source-to-Sink Analysis of the Pantanal Basin (Brazil): Implications for Weathering, Erosion, and Landscape Evolution in the World\u27s Largest Wetland

Large back-bulge retro-arc basins have limited information about the sediment composition, yet they comprise important parts of the stratigraphic rock record. The exorheic Pantanal Basin is the world\u27s largest continental wetland that regulates many valuable ecosystem services (water storage, nutrient cycling, agriculture, ranching, tourism, and transportation). This dissertation is composed of three studies that utilize a suite of tools to examine the most fundamental basin-wide source-to-sink sediment processes and controls that affect the characteristics and distribution of modern sediments. The first paper consists of a metadata analysis of 76 shallow tropical floodplain lakes in the literature with bathymetric data and age models developed from 210Pb, 14C, or optically stimulated luminescence. The assessment revealed an exponential increase in sediment accumulation rate since the 1960s, sometimes by as much as an order of magnitude compared to the historical sedimentation. Short-term sedimentation showed that the average lake infill time is 100-1,000 years, well within the time span of a few human generations. We highlighted the importance of lake bathymetry surveys because computing lake volume based on average depth tends to overestimate the true volume of the lake. Tropical lakes with steeper slopes and higher population density are at risk of more rapid infill rates, which implies accelerating sedimentation rates resulting from anthropogenic land use change. The second paper presents a petrographic investigation of 97 modern fluvial sands across the Pantanal, coupled with a pour point analysis for each sampling station. The sands were prepared as grain mount thin sections, and 500 grains were counted for every sample following the Gazzi-Dickinson point counting method. We defined six provenance regions across the Pantanal Basin: lowlands, Amazon craton, Rio Apa craton, plateau, Southern Paraguay Belt, and Northern Paraguay Belt. The most commonly occurring grain was non-orogenic quartzose detritus (%Quartz\Feldspar\Lithic 88\5\7). Lithic grains were most concentrated in rivers draining the Paraguay Belt highlands, whereas K-feldspars were frequently observed in sands in rivers of the Rio Apa craton. Finer K-feldspar sands were found in the medial Taquari River megafan caused by channel avulsion and exhumation of more feldspar-rich floodplain deposits. The main control on sand is bedrock lithology, followed by mean annual precipitation. The third paper is a study of the mineralogy and geochemistry of 74 distinct modern fluvial clays in the Pantanal Basin to assess the controls on clay composition. We used wavelength-dispersive X-ray fluorescence to measure major elemental abundance in silt + clay samples, and we used X-ray diffraction to obtain semi-quantitative clay proportions. The abundance of clay is as follows: kaolinite \u3e vermiculite \u3e illite \u3e smectite. We identified the Taquari River weathering hinge, where kaolinite is most abundant in northern Pantanal muds and vermiculite is most abundant in southern Pantanal muds. The controls on clay compositions are as follows: hydroclimate \u3e soils \u3e lithology. The geochemistry of the silt + clay reveals the influence of quartz addition from parent rocks. In the context of the Plata River watershed, the kaolinite-dominant fluvial clays from the Pantanal Basin are diluted by illite-dominant clays from the sub-Andean foreland basin

Amazon hydrology from space : scientific advances and future challenges

As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite-based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin-scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes-Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology-oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space-time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure

Tributary impacts, hydrological connectivity and distribution of sediment sinks along the middle-lower Amazon River

By integrating hydro-geomorphic data collected from the field with remote sensing data, this dissertation investigates the roles of the tributaries and vast floodplain on suspended sediment distribution patterns in the Amazon River system. To assess the tributary impacts, I focused on the Solimões and Negro Rivers, and found the significant seasonal variations in surface water mixing and distribution patterns; however inter-annual variations between flooded (2009) and drought years (2005) were not notable. It is also observed that the anabranching channel patterns were observed to prevent fast mixing of different water types. Channel-floodplain hydro-sedimentary interactions were investigated over water-saturated floodplain in the lower Amazon by mapping geomorphic mosaic, and characterizing the seasonal flooding and storage patterns. Hydrological connectivity processes over floodplain varied significantly between geomorphic units, which were not correlated with their distance from the river, implying that application of the traditional “flood pulse” model is not applicable in the Amazon. The channel-floodplain connectivity also resulted in failure of the rating curve around Obidos due to the seasonal water storage in floodplain. Using a series of ADCP data, both the threshold of hydrological connectivity and geomorphic factors influencing the rating curve were assessed, and then the rating curve at Obidos was revised. Floodplain suspended sediment storage along the lower Amazon in between Manacapuru and Obidos was estimated as 79 million tons annually. However sedimentation rates which are determined by the connectivity processes and geomorphologic characteristics of floodplain significantly varied between different reaches, showing downstream increase in the magnitude of sediment sinks. This indicates a nonlinear geomorphic evolution of the Amazon floodplain at least since the Holocene through the river’s longitudinal profile. Through sequences of interrelated chapters, I arrived to the conclusion that the influences of the tributaries and channel-floodplain interactions on the Amazon River system’s suspended sediment distribution are significant and their patterns are more complex than expected. The major factor contributing to this complexity is the geomorphologic styles of the river, which are related both to the long-term evolution processes and to the current anabranching channel dynamics. These geomorphologic styles along the Amazon River are different reach-by-reach due to the varying interactive processes with regional tectonics, hydroclimatology and human activities.Geography and the Environmen