Assessing Field Spectroscopy Metadata Quality

Rasaiah, Barbara A.; Jones, Simon; Bellman, Chris; Malthus, Tim J.; Hueni, Andreas

doi:10.3390/rs70404499

Cited by 12 publications

(6 citation statements)

References 17 publications

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“…A capacidade de medir e de rastrear a qualidade da informação é fundamental para gerenciar e melhorar a qualidade da produção, da distribuição de informações e para a criação do conhecimento. Após a seleção dos indicadores, com base em características ou dimensões apropriadas, deve ser estabelecido um processo de medição desses indicadores (Bizer e Cyganiak 2009;Rasaiah et al 2015). Esta tarefa é facilitada pelo uso de métricas de avaliação.…”

Section: Métricasunclassified

“…Para facilitar a seleção de informações relevantes para usuários e demandantes, e minimizar o problema de sobrecarga de informações, os sistemas de informação devem diferenciar os dados que podem ser seguramente resumidos dos dados que devem ser consultados em sua forma original (Dante 2008). Então, indicadores e métricas podem auxiliar o processo de estabelecer a pertinência e a qualidade de dados e de informações, utilizando-se tanto de métodos quantitativos como qualitativos para uma possível seleção (Rasaiah et al 2015). O uso de indicadores qualitativos fornece subsídios para o pesquisador identificar a relevância ou confiabilidade da informação.…”

Section: Introductionunclassified

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Uso de indicadores e métricas para avaliação da qualidade da informação

Guedes

Fonseca

2021

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A qualidade de informações fornecidas varia amplamente e a expressiva quantidade de informações acessíveis dificulta o acesso à informação relevante. O objetivo deste estudo foi identificar o uso de indicadores e de métricas para avaliar a qualidade de dados e de informações a partir da literatura branca especializada disponível nas bases de dados da Proquest, da Web of Science e da Scopus. O Protocolo de Recomendação Prisma e a Análise de Conteúdo foram utilizados para identificar construtos, métricas e indicadores usados. Os resultados apontaram o uso mais frequente dos indicadores de precisão, de confiabilidade e de completude. Houve discrepância e sobreposição de conceitos na definição dos indicadores, associadas ao tipo de indicador e ao objeto de avaliação, ou seja, dado ou informação. As métricas de avaliação, de contexto e de conteúdo foram utilizadas para avaliar a qualidade de dados, fontes de dados e informação de documentos. Conclui-se que a escolha de indicadores e de métricas para análise da qualidade de informação depende da tarefa e das preferências subjetivas do usuário da informação, sendo preferível usar métricas de avaliação rastreáveis, simples e de fácil compreensão.

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Section: Métricasunclassified

Section: Introductionunclassified

Uso de indicadores e métricas para avaliação da qualidade da informação

Guedes

Fonseca

2021

BRAJIS

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“…Imported from the FGDC Content Standard for Digital Geospatial Metadata (Remote Sensing Extension). Rasaiah et al [6], presents metadata quality parameters specifically aligned to field spectroscopy.…”

Section: A Way Forward: Towards a Robust Metadata Standardmentioning

confidence: 99%

“…Interoperability of field spectroscopy metadata is central to facilitating common platforms for sharing field spectroscopy datasets within the remote sensing community [1][2][3][4][5][6]. A field spectroscopy metadata standard is defined as those data elements that explicitly document the spectroscopy dataset and field protocols, sampling strategies, instrument properties and environmental and logistical variables [5].…”

Section: The Importance Of Interoperable Field Spectroscopy Metadatasetsmentioning

confidence: 99%

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

et al. 2015

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This paper presents an approach to developing robust metadata standards for specific applications that serves to ensure a high level of reliability and interoperability for a spectroscopy dataset. The challenges of designing a metadata standard that meets the unique requirements of specific user communities are examined, including in situ measurement of reflectance underwater, using coral as a case in point. Metadata schema mappings from seven existing metadata standards demonstrate that they consistently fail to meet the needs of field spectroscopy scientists for general and specific applications (μ = 22%, σ = 32% conformance with the core metadata requirements and μ = 19%, σ = 18% for the special case of a benthic (e.g., coral) reflectance metadataset). Issues such as field measurement methods, instrument calibration, and data representativeness for marine field spectroscopy campaigns are investigated within the context of submerged benthic measurements. The implication of semantics and syntax for a robust and flexible metadata standard are also considered. A hybrid standard that serves as a "best of breed" incorporating useful modules and parameters within the standards is proposed. This paper is Part 3 in a series of papers in this journal, examining the issues central to a metadata standard for field spectroscopy datasets. The results presented in this paper are an important step towards field spectroscopy metadata standards that address the specific needs of field OPEN ACCESSRemote Sens. 2015, 7 15669 spectroscopy data stakeholders while facilitating dataset documentation, quality assurance, discoverability and data exchange within large-scale information sharing platforms.

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“…In addition, there are limiting factors due to the ambiguous use of reflectance terminology, measurement geometry description and variable measurement protocols (Milton et al, 2009;. To control the limiting factors the provision of metadata and sufficient documentation on the measurement conditions and target characteristics is essential (Rasaiah et al, 2014(Rasaiah et al, , 2015. To produce highquality spectral information, some guidelines for successful measurements and factors influencing the measurement output have been reported by both the instrument manufacturers and the individual scientific projects (Goetz, 2012;Pfitzner et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Taiga and Tundra Snowpack in Development and Validation of Remote Sensing of Snow

Hannula¹

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Remote sensing of snow is a method to measure snow cover characteristics without direct physical contact with the target from airborne or space-borne platforms. Reliable estimates of snow cover extent and snow properties are vital for several applications including climate change research and weather and hydrological forecasting. Optical remote sensing methods detect the extent of snow cover based on its high reflectivity compared to other natural surfaces. A universal challenge for snow cover mapping is the high spatiotemporal variability of snow properties and heterogeneous landscapes such as the boreal forest biome. The optical satellite sensor’s footprint may extend from tens of meters to a kilometer; the signal measured by the sensor can simultaneously emerge from several target categories within individual satellite pixels. By use of spectral unmixing or inverse model-based methods, the fractional snow cover (FSC) within the satellite image pixel can be resolved from the recorded electromagnetic signal. However, these algorithms require knowledge of the spectral reflectance properties of the targets present within the satellite scene and the accuracy of snow cover maps is dependent on the feasibility of these spectral model parameters. On the other hand, abrupt changes in land cover types with large differences in their snow properties may be located within a single satellite image pixel and complicate the interpretation of the observations. Ground-based in-situ observations can be used to validate the snow parameters derived by indirect methods, but these data are affected by the chosen sampling. This doctoral thesis analyses laboratory-based spectral reflectance information on several boreal snow types for the purpose of the more accurate reflectance representation of snow in mapping method used for the detection of fractional snow cover. Multi-scale reflectance observations representing boreal spectral endmembers typically used in optical mapping of snow cover, are exploited in the thesis. In addition, to support the interpretation of remote sensing observations in boreal and tundra environments, extensive in-situ dataset of snow depth, snow water equivalent and snow density are exploited to characterize the snow variability and to assess the uncertainty and representativeness of these point-wise snow measurements applied for the validation of remote sensing observations. The overall goal is to advance knowledge about the spectral endmembers present in boreal landscape to improve the accuracy of the FSC estimates derived from the remote sensing observations and support better interpretation and validation of remote sensing observations over these heterogeneous landscapes. The main outcome from the work is that laboratory-controlled experiments that exclude disturbing factors present in field circumstances may provide more accurate representation of wet (melting) snow endmember reflectance for the FSC mapping method. The behavior of snow band reflectance is found to be insensitive to width and location differences between visible satellite sensor bands utilized in optical snow cover mapping which facilitates the use of various sensors for the construction of historical data records. The results also reveal the high deviation of snow reflectance due to heterogeneity in snow macro- and microstructural properties. The quantitative statistics of bulk snow properties show that areal averages derived from in-situ measurements and used to validate remote sensing observations are dependent on the measurement spacing and sample size especially over land covers with high absolute snow depth variability, such as barren lands in tundra. Applying similar sampling protocol (sample spacing and sample size) over boreal and tundra land cover types that represent very different snow characteristics will yield to non-equal representativeness of the areal mean values. The extensive datasets collected for this work demonstrate that observations measured at various scales can provide different view angle to the same challenge but at the same time any dataset individually cannot provide a full understanding of the target complexity. This work and the collected datasets directly facilitate further investigation of uncertainty in fractional snow cover maps retrieved by optical remote sensing and the interpretation of satellite observations in boreal and tundra landscapes.

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Assessing Field Spectroscopy Metadata Quality

Cited by 12 publications

References 17 publications

Uso de indicadores e métricas para avaliação da qualidade da informação

Uso de indicadores e métricas para avaliação da qualidade da informação

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

Characteristics of Taiga and Tundra Snowpack in Development and Validation of Remote Sensing of Snow

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