687 research outputs found

    Time delay evaluation on thewater-leaving irradiance retrieved from empirical models and satellite imagery

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    Temporal delays and spatial randomness between ground-based data and satellite overpass involve important deviations between the empirical model output and real data; these are factors poorly considered in the model calibration. The inorganic matter-generated turbidity in Lake Chapala (Mexico) was taken as a study case to expose the influence of such factors. Ground-based data from this study and historical records were used as references. We take advantage of the at-surface reflectance from Landsat-8, sun-glint corrections, a reduced NIR-band range, and null organic matter incidence in these wavelengths to diminish the physical phenomena-related radiometric artifacts; leaving the spatio-temporal relationships as the principal factor inducing the model uncertainty. Non-linear correlations were assessed to calibrate the best empirical model; none of them presented a strong relationship (<73%), including that based on hourly delays. This last model had the best predictability only for the summer-fall season, explaining 71% of the turbidity variation in 2016, and 59% in 2017, with RMSEs < 24%. The instantaneous turbidity maps depicted the hydrodynamic complexity of the lake, highlighting a strong component of spatial randomness associated with the temporal delays. Reasonably, robust empirical models will be developed if several dates and sampling-sites are synchronized with more satellite overpasses.</p

    Water Quality and Algal Bloom Sensing from Multiple Imaging Platforms

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    Harmful cyanobacteria blooms have been increasing in frequency throughout the world resulting in a greater need for water quality monitoring. Traditional methods of monitoring water quality, such as point sampling, are often resource expensive and time consuming in comparison to remote sensing approaches, however the spatial resolution of established water remote sensing satellites is often too coarse (300 m) to resolve smaller inland waterbodies. The fine scale spatial resolution and improved radiometric sensitivity of Landsat satellites (30 m) can resolve these smaller waterbodies, enabling their capability for cyanobacteria bloom monitoring. In this work, the utility of Landsat to retrieve concentrations of two cyanobacteria bloom pigments, chlorophyll-a and phycocyanin, is assessed. Concentrations of these pigments are retrieved using a spectral Look-Up-Table (LUT) matching process, where an exploration of the effects of LUT design on retrieval accuracy is performed. Potential augmentations to the spectral sampling of Landsat are also tested to determine how it can be improved for waterbody constituent concentration retrieval. Applying the LUT matching process to Landsat 8 imagery determined that concentrations of chlorophyll-a, total suspended solids, and color dissolved organic matter were retrieved with a satisfactory accuracy through appropriate choice of atmospheric compensation and LUT design, in agreement with previously reported implementations of the LUT matching process. Phycocyanin proved to be a greater challenge to this process due to its weak effect on waterbody spectrum, the lack of Landsat spectral sampling over its predominant spectral feature, and error from atmospheric compensation. From testing potential enhancements to Landsat spectral sampling, we determine that additional spectral sampling in the yellow and red edge regions of the visible/near-infrared (VNIR) spectrum can lead to improved concentration retrievals. This performance further improves when sampling is added to both regions, and when Landsat is transitioned to a VNIR imaging spectrometer, though this is dependent on band position and spacing. These results imply that Landsat can be used to monitor cyanobacteria blooms through retrieval of chlorophyll-a, and this retrieval performance can be improved in future Landsat systems, even with minor changes to spectral sampling. This includes improvement in retrieval of phycocyanin when implementing a VNIR imaging spectrometer

    LĂ€hi-kaugseire meetodite arendamine veekogude seisundi hindamiseks

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    VĂ€itekirja elektrooniline versioon ei sisalda publikatsioone.Veekogude kvaliteedi hindamine on inimkonnale oluline olnud juba tuhandeid aastaid ja viimastel aastakĂŒmnetel on rohkem tĂ€helepanu hakatud pöörama ka veekogude ökoloogilisele seisundile. Euroopas on veekogude kvaliteedi hindamise aluseks kaks dokumenti: Euroopa Liidu Vee Raamdirektiiv ja Euroopa Liidu Merestrateegia Raamdirektiiv. MĂ”lemad dokumendid sĂ€testavad, et aastaks 2020 tuleb Euroopa Liidu veekogudes saavutada „hea“ seisund. Nende eesmĂ€rkide tĂ€itmiseks tuleb regulaarselt veekogude seisundit seirata. KuivĂ”rd kĂ”ikidelt veekogudelt veeproovide vĂ”tmine ja laboris analĂŒĂŒsimine ei ole vĂ”imalik (liigne raha ja tööjĂ”ukulu) ning lisaks ei anna sellised proovid ĂŒlevaadet veekogu seisundi parameetrite ruumilise jaotuse kohta tuleb appi vĂ”tta optilised instrumendid. Lisaks vĂ€litöödel kasutatavale optikale on Copernicus programmi raames jĂ€rgnevatel aastakĂŒmnetel kĂ€ttesaadav ka mitu erinevat satelliiditulemit. Nende tulemite kasutamiseks peab aga pidevalt nende tĂ€psust hindama ja leidma tĂ€psemaid arvutusmeetmeid, mis sobiksid konkreetsete parameetrite hindamiseks. Töö kĂ€igus tĂ”estati, et vee optilised omadused, nagu neeldumine ja hajumine, varieeruvad LÀÀnemere rannikuosas rohkem, kui on variatsioon ranniku ja mere keskosa vahel. Lisaks absoluutvÀÀrtuste erinevusele tuvastati ka spektraalse kuju muutusi eri piirkondade vahel. TĂ”estati, et elektromagnetkiirguse lĂ€hisinfrapuna piirkonda saab rakendada veekogude seires (tavaliselt eeldatakse, et selles spektripiirkonnas on veest tulev signaal null) ja eriti on see kasulik ohtralt lahustunud orgaanikat sisaldavate jĂ€rvede seires. Testiti ja pakuti vĂ€lja sobivaid kaugseire algoritme LÀÀnemere vee kvaliteedi parameetrite hindamiseks. AnalĂŒĂŒsiti erinevate spektromeetrite tulemuste varieeruvust ja leiti, et mÔÔtmisprotokolli korrektsel jĂ€lgimisel on erinevate sensorite tulemused kĂŒll erinevad, ent seire teostamiseks piisavalt sarnased. LĂ”petuseks uuriti, millised on erinevate kĂ€sispektromeetrite potentsiaalsed rakendused.Knowing the quality of different waterbodies has been essential for human kind for thousands of years. There are two main European Union’s documents guiding the status assessment of water bodies: Water Framework Directive and Marine Strategy Framework Directive. Both of these documents state that all waterbodies in the European Union have to achieve “good” status by the year 2020. In order to fulfil this requirement, water bodies have to be monitored in regular bases. It is impossible to collect laboratory samples from every waterbody as it would be too expensive and would require many workers and still wouldn’t provide information about the spatial distribution of water quality parameters within each waterbody. Optical instruments can provide data fast and over larger areas and therefore have to be included in the monitoring programs. In addition to devices used at the in situ measurements are several satellite products that are available through Copernicus program for the coming decades. These products must, however, be constantly validated with in situ measurements. Additionally, new calculation methods have to be developed to improve the results precision. During this thesis, the variability of optical properties (like absorption and scattering) was assessed in the Baltic Sea. It was studied how much this variability influences the reflectance signal that reaches water remote sensing instruments. The performance of different set-ups and protocols of field spectrometers to collect reflectance data was assessed. The possibility to use near-infrared part of the spectrum in water remote sensing was investigated. In extreme absorbing lakes this is the only part of radiation providing us information about the water properties, but it proved to be useful also in other waterbodies. The performance of many remote sensing algorithms in retrieving water quality parameters in the Baltic Sea was tested. The possible applications for hand-held spectrometers were investigated

    Remote sensing, numerical modelling and ground truthing for analysis of lake water quality and temperature

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    Freshwater accounts for just 2.5% of the earth’s water resources, and its quality and availability are becoming an issue of global concern in the 21st century. Growing human population, over-exploitation of water sources and pressures of global warming mean that both water quantity and quality are affected. In order to effectively manage water quality there is a need for increased monitoring and predictive modelling of freshwater resources. To address these concerns in New Zealand inland waters, an approach which integrates biological and physical sciences is needed. Remote sensing has the potential to allow this integration and vastly increase the temporal and spatial resolution of current monitoring techniques, which typically involve collecting grab-samples. In a complementary way, lake modelling has the potential to enable more effective management of water resources by testing the effectiveness of a range of possible management scenarios prior to implementation. Together, the combination of remote sensing and modelling data allows for improved model initialisation, calibration and validation, which ultimately aid in understanding of complex lake ecosystem processes. This study investigated the use of remote sensing using empirical and semi-analytical algorithms for the retrieval of chlorophyll a (chl a), tripton, suspended minerals (SM), total suspended sediment (SS) and water surface temperature. It demonstrated the use of spatially resolved statistical techniques for comparing satellite estimated and 3-D simulated water quality and temperature. An automated procedure was developed for retrieval of chl a from Landsat Enhanced Thematic Mapper (ETM+) imagery, using 106 satellite images captured from 1999 to 2011. Radiative transfer-based atmospheric correction was applied to images using the Second Simulation of the Satellite in the Solar Spectrum model (6sv). For the estimation of chl a over a time series of images, the use of symbolic regression resulted in a significant improvement in the precision of chl a hindcasts compared with traditional regression equations. Results from this investigation suggest that remote sensing provides a valuable tool to assess temporal and spatial distributions of chl a. Bio-optical models were applied to quantify the physical processes responsible for the relationship between chl a concentrations and subsurface irradiance reflectance used in regression algorithms, allowing the identification of possible sources of error in chl a estimation. While the symbolic regression model was more accurate than traditional empirical models, it was still susceptible to errors in optically complex waters such as Lake Rotorua, due to the effect of variations of SS and CDOM on reflectance. Atmospheric correction of Landsat 7 ETM+ thermal data was carried out for the purpose of retrieval of lake water surface temperature in Rotorua lakes, and Lake Taupo, North Island, New Zealand. Atmospheric correction was repeated using four sources of atmospheric profile data as input to a radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN) v.3.7. The retrieved water temperatures from 14 images between 2007 and 2009 were validated using a high-frequency temperature sensor deployed from a mid-lake monitoring buoy at the water surface of Lake Rotorua. The most accurate temperature estimation for Lake Rotorua was with radiosonde data as an input into MODTRAN, followed by Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2, Atmospheric Infrared Sounder (AIRS) Level 3, and NASA data. Retrieved surface water temperature was used for assessing spatial heterogeneity of surface water temperature simulated with a three-dimensional (3-D) hydrodynamic model (ELCOM) of Lake Rotoehu, located approximately 20 km east of Lake Rotorua. This comparison demonstrated that simulations reproduced the dominant horizontal variations in surface water temperature in the lake. The transport and mixing of a geothermal inflow and basin-scale circulation patterns were inferred from thermal distributions from satellite and model estimations of surface water temperature and a spatially resolved statistical evaluation was used to validate simulations. This study has demonstrated the potential of accurate satellite-based thermal monitoring to validate water surface temperature simulated by 3-D hydrodynamic models. Semi-analytical and empirical algorithms were derived to determine spatial and temporal variations in SS in Lake Ellesmere, South Island, New Zealand, using MODIS band 1. The semi-analytical model and empirical model had a similar level of precision in SS estimation, however, the semi-analytical model has the advantage of being applicable to different satellite sensors, spatial locations, and SS concentration ranges. The estimations of SS concentration (and estimated SM concentration) from the semi-analytical model were used for a spatially resolved validation of simulations of SM derived from ELCOM-CAEDYM. Visual comparisons were compared with spatially-resolved statistical techniques. The spatial statistics derived from the Map Comparison Kit allowed a non-subjective and quantitative method to rank simulation performance on different dates. The visual and statistical comparison between satellite estimated and model simulated SM showed that the model did not perform well in reproducing both basin-scale and fine-scale spatial variation in SM derived from MODIS satellite imagery. Application of the semi-analytical model to estimate SS over the lifetime of the MODIS sensor will greatly extend its spatial and temporal coverage for historical monitoring purposes, and provide a tool to validate SM simulated by 1-D and 3-D models on a daily basis. A bio-optical model was developed to derive chl a, SS concentrations, and coloured dissolved organic matter /detritus absorption at 443 nm, from MODIS Aqua subsurface remote sensing reflectance of Lake Taupo, a large, deep, oligotrophic lake in North Island, New Zealand. The model was optimised using in situ inherent optical properties (IOPs) from the literature. Images were atmospherically corrected using the radiative transfer model 6sv. Application of the bio-optical model using a single chl a-specific absorption spectrum (a*ϕ(λ)) resulted in low correlation between estimated and observed values. Therefore, two different absorption curves were used, based on the seasonal dominance of phytoplankton phyla with differing absorption properties. The application of this model resulted in reasonable agreement between modelled and in situ chl a concentrations. Highest concentrations were observed during winter when Bacillariophytes (diatoms) dominated the phytoplankton assemblage. On 4 and 5 March 2004 an unusually large turbidity current was observed originating from the Tongariro River inflow in the south-east of the lake. In order to resolve fine details of the plume, empirical relationships were developed between MODIS band 1 reflectance (250 m resolution) and SS estimated from MODIS bio-optical features (1 km resolution) were used estimate SS at 250 m resolution. Complex lake circulation patterns were observed including a large clockwise gyre. With the development of this bio-optical model MODIS can potentially be used to remotely sense water quality in near real time, and the relationship developed for B1 SS allows for resolution of fine-scale features such turbidity currents

    Utility of remote sensing data in retrieval of water quality consituents concentrations in coastal water of New Jersey

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    Three important optical properties used for monitoring coastal water quality are the concentrations of chlorophyll (CHL), color dissolved organic matter (CDOM) and total suspended materials (TSM). Ocean color remote sensing, a technique to collect color data by detection of upward radiance from a distance (Bukata et al.,1995), provides a synoptic view for determining these concentrations from upwelling radiances. In the open ocean (Case-I), it is not difficult to derive empirical algorithms relating the received radiances to surface concentrations of water quality parameters. In coastal waters (Case-Il), there are serious unresolved problems in extracting chlorophyll concentration because of high concentration of suspended particles (Gordon and Morel, 1983). There are three basic approaches to estimate optical water quality parameters from remotely sensed spectral data based on the definitions given by Morel & Gordon (1980): (1) an empirical method, in which statistical relationships between the upward radiance at the sea surface and the quantity of interest are taken into account; (2) a semiempirical method, in which the spectral characteristics of the parameters of interest are known and some modeling of the physics is introduced; and (3) an analytical method, in which radiative transfer models are used to extract the inherent optical properties (lOPs) and a suite of analysis methods can be used to optimally retrieve the water constituents from the remotely sensed upwelling radiance or irradiance reflectance signal. The focus of this research is the modification and application of analytical and statistical algorithms to characterize the physically based surface spectral reflectance for the waters of the Hudson/Raritan Estuary and to retrieve the water constituent concentrations from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and LIght Detection And Ranging (LIDAR) signals. The approaches used here are based on the unique capabilities of AVIRIS and LIDAR data which can potentially provide a better understanding of how sunlight interacts with estuarine/inland water, especially when complemented with in situ measurements for analysis of water quality parameters and eutrophication processes. The results of analysis in forms of thematic maps are then input into geographic information system (GIS) of the study site for use by water resource managers and planners for better monitoring and management of water quality condition

    SIMBIOS Project 1998 Annual Report

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    The purpose of this series of technical reports is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Ocean Studies (SIMBIOS) Project activities, NASA Research Announcement (NRA) research status, satellite data processing, data product validation and field calibration. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report is not meant to substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issues by an operational project

    Offshore Radiation Observations for Climate Research at the CERES Ocean Validation Experiment

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    When radiometers on a satellite are pointed towards the planet with the goal of understanding a phenomenon quantitatively, rather than just creating a pleasing image, the task at hand is often problematic. The signal at the detector can be affected by scattering, absorption, and emission; and these can be due to atmospheric constituents (gases, clouds, and aerosols), the earth's surface, and subsurface features. When targeting surface phenomena, the remote sensing algorithm needs to account for the radiation associated with the atmospheric constituents. Likewise, one needs to correct for the radiation leaving the surface, when atmospheric phenomena are of interest. Rigorous validation of such remote sensing products is a real challenge. In visible and near infrared wavelengths, the jumble of effects on atmospheric radiation are best accomplished over dark surfaces with fairly uniform reflective properties (spatial homogeneity) in the satellite instrument's field of view (FOV). The ocean's surface meets this criteria; land surfaces - which are brighter, more spatially inhomogeneous, and more changeable with time - generally do not. NASA's Clouds and the Earth's Radiant Energy System (CERES) project has used this backdrop to establish a radiation monitoring site in Virginia's coastal Atlantic Ocean. The project, called the CERES Ocean Validation Experiment (COVE), is located on a rigid ocean platform allowing the accurate measurement of radiation parameters that require precise leveling and pointing unavailable from ships or buoys. The COVE site is an optimal location for verifying radiative transfer models and remote sensing algorithms used in climate research; because of the platform's small size, there are no island wake effects; and suites of sensors can be simultaneously trained both on the sky and directly on ocean itself. This paper describes the site, the types of measurements made, multiple years of atmospheric and ocean surface radiation observations, and satellite validation results

    Remote sensing and bio-geo-optical properties of turbid, productive inland waters: a case study of Lake Balaton

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    Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters

    Bio-Optical Sensors on Argo Floats

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    The general objective of the IOCCG BIO-Argo working group is to elaborate recommendations for establishing a framework for the future development of a cost-effective, bio-optical float network corresponding to the needs and expectations of the scientific community. In this context, our recommendations will necessarily be broad; they range from the identification of key bio-optical measurements to be implemented on floats, to the real-time management of the data flux resulting from the deployment of a "fleet of floats". Each chapter of this report is dedicated to an essential brick leading towards the goal of implementing a bio-optical profiling float network. The following topics are discussed in the Chapters listed below: - Chapter 2 reviews the scientific objectives that could be tackled through the development of such networks, by allowing some of the gaps in the present spatio-temporal resolution of bio-optical variables to be progressively filled. - Chapter 3 identifies the optical and bio-optical properties that are now amenable to remote and autonomous measurement through the use of optical sensors mounted on floats. - Chapter 4 addresses the question of sensor requirements, in particular with respect to measurements performed from floats. - Chapter 5 proposes and argues for the development of dedicated float missions corresponding to specific scientific objectives and relying on specific optical sensor suites, as well as on specific modes of float operation. - Chapter 6 identifies technological issues that need to be addressed for the various bio-optical float missions to become even more cost-effective. - Chapter 7 covers all aspects of data treatment ranging from the development of various quality control procedures (from real-time to delayed mode) to the architecture required for favoring easy access to data. - Chapter 8 reviews the necessary steps and experience required before the operational implementation of different types of float networks can become a reality.JRC.H.5-Land Resources Managemen
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