Remote sensing of physical cycles in Lake Superior using a spatio-temporal analysis of optical water typologies

Trochta, John T.; Mouw, Colleen B.; Moore, Timothy S.

doi:10.1016/j.rse.2015.10.008

Cited by 21 publications

(15 citation statements)

References 54 publications

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“…The approach clusters coastal waters into optical water types (OWTs) (Moore et al 2001), based solely on field-, air-or space-borne spectral data (Moore et al 2014). It has been applied in both coastal and inland water studies with very promising results (Moore et al 2014;Trochta et al 2015;Eleveld et al 2017;Spyrakos et al 2018), and is now used by ESA CCI OC v3.1 in a blended approach to map chlorophyll-a concentrations globally (ESA Climate Change Initiative Ocean Colour 2016). The advantage of OWTs is that they enable grouping of complex coastal waters based on remotely sensed optical characteristics of coastal waters that are inherently dependent upon ecology without requiring information on ecology itself (Moore et al 2009).…”

Section: Application 1 Optical Water Types For Coastal Water Qualitymentioning

confidence: 99%

“…The advantage of OWTs is that they enable grouping of complex coastal waters based on remotely sensed optical characteristics of coastal waters that are inherently dependent upon ecology without requiring information on ecology itself (Moore et al 2009). Even though the exact and potentially complex relationship between OWTs and coastal water ecology has not yet been investigated in depth, previous studies have demonstrated the existence of relationships between spatiotemporal distributions of OWTs and physical and biogeochemical processes and ecological diversity indices (Moore et al 2012;Mélin and Vantrepotte 2015;Trochta et al 2015), signifying the potential benefit from inclusion of the approach in coastal ecological monitoring and water resource management.…”

Section: Application 1 Optical Water Types For Coastal Water Qualitymentioning

confidence: 99%

See 1 more Smart Citation

Earth observation applications for coastal sustainability: potential and challenges for implementation

Politi¹,

Paterson

Scarrott

et al. 2019

Anthropocene Coasts

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The coast is home to unique ecosystems, where complex ecological processes take place through the interaction of terrestrial, aquatic, atmospheric, and human landscapes. However, there are considerable knowledge and data gaps in achieving effective and future change-proof sustainable management of coastal zones around the world due to both technical and social barriers, as well as governance challenges. Currently, the role of Earth observation (EO) in addressing many of the recognised information gaps is small and under-utilised. While EO can provide much of the spatiotemporal information required for historical analysis and current status mapping, and offers the advantage of global coverage; its uptake can be limited by technical and methodological challenges associated mostly with lack of capacity and infrastructure, product accuracy and accessibility, costs, and institutional acceptance. While new initiatives and recent technological progress in the EO and information technology arena aim to tackle some of these issues so that EO products can be more easily used by non-EO experts, uptake is still limited. This paper discusses how EO can potentially inform transformative practices of planning in the coastal water zone, by using examples to demonstrate the EO potential in providing information relevant to decision-making framed by international agreements, such as the United Nations Agenda 2030, the Convention on Biological Diversity, and the Sendai Framework for Risk Reduction. By presenting evidence for how EO can contribute to innovative opportunities and data synergies at scale, the paper discusses opportunities and challenges for a more solution-led approach to sustainable coastal management.

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Section: Application 1 Optical Water Types For Coastal Water Qualitymentioning

confidence: 99%

Section: Application 1 Optical Water Types For Coastal Water Qualitymentioning

confidence: 99%

Earth observation applications for coastal sustainability: potential and challenges for implementation

Politi¹,

Paterson

Scarrott

et al. 2019

Anthropocene Coasts

View full text Add to dashboard Cite

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“…Global variability in water optical properties is significant yet the non-uniqueness of Rrs() hampers consistent interpretation across both empirical and semi-analytical methods (Werdell et al 2018 and references therein). Previous concepts for working around this issue, particularly in light of multispectral limitations, have included screening Rrs() to most likely cases based on optical water types, non-linear spectral optimization, linear matrix inversion, bulk inversion, ensemble inversion and spectral deconvolution (Brando et al 2012;Hieronymi et al 2017;Mélin and Vantrepotte 2015;Trochta et al 2015;Werdell et al 2018). These approaches are broadly defined as bottom-up and top-down strategies (Mouw et al 2015), where bottom-up strategies simultaneously solve for all parameters while top-down strategies allow for independent retrieval of absorbing and scattering constituents (a and bb).…”

Section: Applicationmentioning

confidence: 99%

Deriving inherent optical properties from decomposition of hyperspectral non-water absorption

Grunert

Mouw

Barnett

2019

Remote Sensing of Environment

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Semi-analytical algorithms (SAAs) developed for multispectral ocean color sensors have benefited from a variety of approaches for retrieving the magnitude and spectral shape of inherent optical properties (IOPs). SAAs generally follow two approaches: 1) simultaneous retrieval of all IOPs, resulting in pre-defined bio-optical models and spectral dependence between IOPs and 2) retrieval of bulk IOPs (absorption and backscattering) first followed by decomposition into separate components, allowing for independent retrievals of some components. Current algorithms used to decompose hyperspectral remotely-sensed reflectance into IOPs follow the first strategy. Here, a spectral deconvolution algorithm for incorporation into the second strategy is presented that decomposes at-w() from in situ measurements and estimates absorption due to phytoplankton (aph()) and colored detrital material (adg()) free of explicit assumptions. The algorithm described here, Derivative Analysis and Iterative Spectral Evaluation of Absorption (DAISEA), provides estimates of aph() and adg() over a spectral range from 350-700 nm. Estimated aph() and adg() showed an average normalized root mean square difference of <30% and <20%, respectively, from 350-650 nm for the majority of optically distinct environments considered. Estimated Sdg median difference was less than 20% for all environments considered, while distribution of Sdg uncertainty suggests that biogeochemical variability represented by Sdg can be estimated free of bias. DAISEA results suggest that hyperspectral satellite ocean color data will improve our ability to track biogeochemical processes affiliated with variability in adg() and Sdg free of explicit assumptions.

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“…Jay and Guillaume [33] used hyperspectral data for mapping depth and water quality. Trochta et al [79] presented the identification of water types with different biogeochemical properties and drivers through an optical classification scheme based on RS data. Hunink et al [27] studied the relationships between groundwater usage and crop type in irrigated 100,000.00 1,000,000.00 10,000,000.00…”

Section: Environmental Impacts Of Urban Growthmentioning

confidence: 99%

Advances in remote sensing applications for urban sustainability

Kadhim

Mourshed

Bray

2016

Euro-Mediterr J Environ Integr

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It is essential to monitor urban evolution at spatial and temporal scales to improve our understanding of the changes in cities and their impact on natural resources and environmental systems. Various aspects of remote sensing are routinely used to detect and map features and changes on land and sea surfaces, and in the atmosphere that affect urban sustainability. We provide a critical and comprehensive review of the characteristics of remote sensing systems, and in particular the trade-offs between various system parameters, as well as their use in two key research areas: (a) issues resulting from the expansion of urban environments, and (b) sustainable urban development. The analysis identifies three key trends in the existing literature: (a) the integration of heterogeneous remote sensing data, primarily for investigating or modelling urban environments as a complex system, (b) the development of new algorithms for effective extraction of urban features, and (c) the improvement in the accuracy of traditional spectral-based classification algorithms for addressing the spectral heterogeneity within urban areas. Growing interests in renewable energy have also resulted in the increased use of remote sensing-for planning, operation, and maintenance of energy infrastructures, in particular the ones with spatial variability, such as solar, wind, and geothermal energy. The proliferation of sustainability thinking in all facets of urban development and management also acts as a catalyst for the increased use of, and advances in, remote sensing for urban applications.

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Remote sensing of physical cycles in Lake Superior using a spatio-temporal analysis of optical water typologies

Cited by 21 publications

References 54 publications

Earth observation applications for coastal sustainability: potential and challenges for implementation

Earth observation applications for coastal sustainability: potential and challenges for implementation

Deriving inherent optical properties from decomposition of hyperspectral non-water absorption

Advances in remote sensing applications for urban sustainability

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