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16th International Conference on Machine Learning and Computing (ICMLC)

作者： Li, Xiangzhen Huang, Ping Zhou, Kan Zhang, Peng Zhang, Qiujie Wang, Xiaohang Beijing Inst Technol Natl Key Lab Scattering & Radiat Beijing Peoples R China Beijing Inst Technol Beijing Inst Control & Elect Technol Beijing Peoples R China Natl Key Lab Scattering & Radiat Beijing Peoples R China

ISBN: (纸本)9798400709234

This paper introduces a 3D model-based approach to calculate the coverage of target data, which aims to provide an intuitive and efficient way to analyze and evaluate the performance of remote sensing data acquisition of targets. We classify existing data by load and target, build a 3D model of the target, and project the data onto a hemisphere to visually show the coverage of the data. This method combines data science, GIS technology and the application of the *** plug-in to provide a powerful tool for research and decision-making in the field of remote sensing.

关键词： 3D model data coverage remote sensing

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TANDEM-X HEIGHT PERFORMANCE AND data coverage 37

TANDEM-X HEIGHT PERFORMANCE AND DATA COVERAGE

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IEEE International Geoscience & Remote Sensing Symposium

作者： Wecklich, Christopher Gonzalez, Carolina Rizzoli, Paola German Aerosp Ctr DLR Microwaves & Radar Inst Cologne Germany

ISBN: (纸本)9781509049516

TanDEM-X is a single-pass radar interferometric mission, which is comprised of two formation flying satellites, with the primary goal of generating a global Digital Elevation Model (DEM) of unprecedented accuracy. Between December 2010 and early 2015 all land surfaces have been acquired at least twice, difficult terrain up to seven or eight times and as of September 2016 the final TanDEM-X DEM dataset is available for download. This paper provides a final quality assessment of the TanDEM-X global DEM products with respect to the DEM relative and absolute height accuracy and data coverage both at the global and geocell level.

关键词： Synthetic Aperture Radar (SAR) Interferometry Digital Elevation Model (DEM) height accuracy data coverage voids

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Mobilisation of data From Natural History Collections Can Increase the Quality and coverage of Biodiversity Information

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ECOLOGY AND EVOLUTION 2025年第4期15卷 e71139页

作者： Blades, Bryony Ronquillo, Cristina Hortal, Joaquin Univ Oxford Dept Biol Oxford England African Nat Hist Res Trust ANHRT Kingsland Hers England Museo Nacl Ciencias Nat MNCN CSIC Dept Biogeog & Global Change Madrid Spain

The surge of biodiversity data availability in recent decades has allowed researchers to ask questions on previously unthinkable scales, but knowledge gaps still remain. In this study, we aim to quantify potential gains to insect data on the Global Biodiversity Information Facility (GBIF) through further digitisation of natural history collections, assess to what degree this would fill biases in spatial and environmental record coverage, and deepen understanding of environmental bias with regard to climate rarity. Using mainland Afrotropical records for Catharsius Hope, 1837 (Coleoptera: Scarabaeidae), we compared inventory completeness of GBIF data to a dataset which combined these with records from a recent taxonomic revision. We analysed how this improved dataset reduced regional and environmental bias in the distribution of occurrence records using an approach that identifies well-surveyed spatial units of 100 x 100km as well as emerging techniques to classify rarity of climates. We found that the number of cells for which inventory completeness could be calculated, as well as coverage of climate types by 'well-sampled' cells, increased threefold when using the combined set compared to the GBIF set. Improvements to sampling in Central and Western Africa were particularly striking, and coverage of rare climates was similarly improved, as not a single well-sampled cell from the GBIF data alone occurred in the rarest climate types. These findings support existing literature that suggests data gaps on GBIF are still pervasive, especially for insects and in the tropics, and so, is not yet ready to serve as a standalone data source for all taxa. However, we show that natural history collections hold the necessary information to fill many of these gaps, and their further digitisation should be a priority.

关键词： biodiversity data coverage digitisation GBIF mobilisation natural history collections

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Participant Service Quality Aware data Collecting Mechanism With High coverage for Mobile Crowdsensing

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IEEE ACCESS 2020年 8卷 10628-10639页

作者： Yang, Jing Fu, Lei Yang, Boran Xu, Jialiang Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China Key Lab Opt Commun & Network Chongqing Chongqing 400065 Peoples R China Key Lab Ubiquitous Sensing & Networking Chongqing Chongqing 400065 Peoples R China

A large number of participants are required to complete specific tasks to sense data and obtain the sensing information in Mobile Crowdsensing. In order to ensure the real-time effectiveness and comprehensiveness of the sensing information, this paper proposes a participant service quality aware data collecting mechanism with high coverage. Firstly, the service quality is measured by the willingness and regional preference of participants to analyze the real-time effectiveness of the sensing data. Then the sensing data coverage is evaluated according to the number of target points covered by the participants during the execution of sensing tasks. Furthermore, the efficiency of the participants is determined by service quality and data coverage under the condition of a limited platform budget. Finally, an iterative greedy algorithm is designed to select the sensing data from the participants set with the highest efficiency, so the coverage of sensing data can be efficiently optimized. The results demonstrate that the proposed data collecting mechanism can reduce the total reward for participants, make the tasks accomplished more efficiently, and effectively collect sensing data with high coverage.

关键词： Mobile crowdsensing data collecting data coverage service quality

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Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring

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ECOSPHERE 2025年第3期16卷

作者： Smits, Adrianne P. Hall, Ed K. Deemer, Bridget R. Scordo, Facundo Barbosa, Carolina C. Carlson, Stephanie M. Cawley, Kaelin Grossart, Hans-Peter Kelly, Patrick Mammola, Stefano Pintar, Matthew R. Robbins, Caleb J. Ruhi, Albert Sacco, Mattia Univ Calif Davis Environm Sci & Policy Davis CA 95616 USA Colorado State Univ Ecosyst Sci & Sustainabil Dept Ft Collins CO USA US Geol Survey Southwest Biol Sci Ctr Grand Canyon Monitoring & Res Ctr Flagstaff AZ USA Univ Nevada Renos Biol Dept Wildfire Technol Lab Reno NV USA Univ Nevada Global Water Ctr Reno NV USA UNCOMA Inst Invest Biodivers & Medioambiente CONICET San Carlos De Bariloche Rio Negro Argentina Univ Calif Berkeley Dept Environm Sci Policy & Management Berkeley CA USA Batelle Boulder CO USA Leibniz Inst Freshwater Ecol & Inland Fisheries Dept Plankton & Microbial Ecol Stechlin Germany Potsdam Univ Inst Biochem & Biol Potsdam Germany Wisconsin Dept Nat Resources Off Great Waters La Crosse WI USA Natl Res Council CNR Mol Ecol Grp MEG Water Res Inst IRSA Pallanza Italy Natl Biodivers Future Ctr Palermo Italy BIO WEST San Marcos TX USA Florida Int Univ Inst Environm Miami FL USA Univ Alaska Fairbanks Inst Arctic Biol Fairbanks AK USA Baylor Univ Ctr Reservoir & Aquat Syst Res Dept Biol Waco TX USA Curtin Univ Sch Mol & Life Sci Perth WA Australia Univ Parma Dept Chem Life Sci & Environm Sustainabil Parma Italy Univ Helsinki Finnish Museum Nat Hist Helsinki Finland SU Lab Biol Organismes & Ecosyst Aquat BOREA CNRS IRDUAMuseum Natl Hist Nat Paris France

Evaluating progress toward achieving freshwater conservation and sustainability goals requires transforming diverse types of data into useful information for scientists, managers, and other interest groups. Despite substantial increases in the volume of freshwater data collected worldwide, many regions and ecosystems still lack sufficient data collection and/or data access. We illustrate how these data challenges result from a diverse set of underlying mechanisms and propose solutions that can be applied by individuals or organizations. We discuss creative approaches to address data scarcity, including the use of community science, remote-sensing, environmental sensors, and legacy datasets. We highlight the importance of coordinated data collection efforts among groups and training programs to improve data access. At the institutional level, we emphasize the power of prioritizing data curation, incentivizing data publication, and promoting research that enhances data coverage and representativeness. Some of these strategies involve technological and analytical approaches, but many necessitate shifting the priorities and incentives of organizations such as academic and government research institutions, monitoring groups, journals, and funding agencies. Our overarching goal is to stimulate discussion to narrow the data disparities hindering the understanding of freshwater processes and their change across spatial scales.

关键词： aquatic ecosystems data access data collection data coverage data publication data sharing FAIR open science

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A multidimensional assessment of Antarctic terrestrial biological data

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DIVERSITY AND DISTRIBUTIONS 2025年第1期31卷

作者： Patterson, Charlotte R. Helmstedt, Kate J. Terauds, Aleks Shaw, Justine D. Queensland Univ Technol Sch Biol & Environm Sci Brisbane Qld Australia Queensland Univ Technol Securing Antarctica Environm Future Brisbane Qld Australia Queensland Univ Technol Ctr Data Sci Brisbane Qld Australia Queensland Univ Technol Sch Math Sci Brisbane Qld Australia Australian Antarctic Div Dept Climate Change Energy Environm & Water Kingston Tas Australia

AimThe globally significant communities of terrestrial Antarctica face an uncertain future amid growing threats in the region. Emerging data-driven approaches must be leveraged to predict and understand patterns of biodiversity across the continent. A new comprehensive database of Antarctic biological occurrence records, the Biodiversity of Ice-free Antarctica database, will enable such novel fundamental and applied biodiversity modelling. However, there are limitations of assembled occurrence databases that, if unaccounted for, can result in poor model inference and outcomes. We perform a data quality assessment of the new database to highlight its potential and to identify data limitations that must be considered during *** assessed the coverage of the Biodiversity of Ice-free Antarctica database across geographic, environmental, taxonomic, and temporal dimensions at several spatial *** demonstrate great potential for the database to improve our understanding of many at risk and poorly known Antarctic functional groups. We also provide evidence for limitations of the database across data dimensions, including low geographic coverage that is biased towards research stations, poor coverage of environmental variation across the landscape, and long periods since records were last collected. The magnitude of these limitations varies substantially by region and spatial *** ConclusionsIn combination, data limitations have a range of implications for terrestrial Antarctic modelling, including heightening the risk of model extrapolation. For future use, we recommend prioritising, mitigating, and presenting context-specific model uncertainty, advancing strategic data collection, and exploiting shared modelling challenges elsewhere in the world to maximise the opportunities for this unique dataset to robustly advance science and conservation in Antarctica.

关键词： Antarctica bias biodiversity biological records data coverage data quality database modelling species distribution models uncertainty

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OCCUR Shiny application: A user-friendly guide for curating species occurrence records

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METHODS IN ECOLOGY AND EVOLUTION 2024年第5期15卷 816-823页

作者： Ronquillo, Cristina Stropp, Juliana Hortal, Joaquin Museo Nacl Ciencias Nat MNCN CSIC Dept Biogeog & Global Change Madrid Spain Trier Univ Dept Biogeog Trier Germany

Ecology increasingly relies on a massive volume of biodiversity occurrence records to draw insights into large-scale biogeographical, ecological and evolutionary phenomena. This often involves defining a set of criteria that guides the collection, filtering and standardising of available records. These curation processes are often neither described in detail nor well documented. This hampers the comparability and reproducibility of studies and thus undermines the robustness of any ecological result. Yet, to date, there is no guide providing a friendly way to reason and document a complete data curation process. We reviewed the available literature on data curation, including tools such as R packages and workflows. From this assessment, we created a complete guide organised into five modules that allows users to consciously select and validate occurrence records based on these curation criteria. This is presented in the user-friendly Shiny R OCCUR application, available at . OCCUR application provides a guide for researchers to deal with the trade-off between data certainty and coverage generated in each data curation step. An interactive graph of these changes is provided within each module. OCCUR also produces a custom-made final report including all steps used for data filtering. This report helps to streamline the writing of the methods section of manuscripts and technical reports, thus promoting the reproducibility of data curation processes. This Shiny application provides an interactive overview of the data curation methods and their use for handling occurrence records from public repositories. It brings together the taxonomic, temporal and spatial dimensions of data and also the identification of duplicates of the records. OCCUR can be applied for multiple purposes, such as teaching R to ecologists or enhancing reproducibility of macroecology and biogeography.

关键词： biodiversity data biodiversity informatics data certainty data cleaning data coverage data curation Shiny application species occurrence records

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Who counts in poverty research?

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SOCIOLOGICAL REVIEW 2024年第2期72卷 235-257页

作者： Edmiston, Daniel Univ Leeds Sch Sociol & Social Policy Leeds LS2 9JT England

Mainstream poverty analysis currently renders certain people and degrees of privation more socially legible than others across high-income countries. This article examines how these hierarchies carry through to and corrupt wider social scientific analysis, inscribing differential value to actors and phenomena in ways that undermine social understanding and explanation. First, conventional approaches to poverty analysis and measurement obscure the de facto prevalence of deep poverty, as well as those most subject to its violence. Second, a growing number of hyper-marginalised groups are missing from population income surveys, undermining the accuracy of (deep) poverty estimates and public understanding of both its determinants and dynamics. Third, the inferential and external validity of income surveys is significantly diminished by problems surrounding data quality and coverage. Attempts to address this have principally focused on improving data quality, but as demonstrated in this article, these strategies exacerbate poor representation of the lowest-income groups in distributional analysis. Much more than merely technical or pragmatic, these are theoretical and normative judgements about who counts in welfare policy and politics. Overall, I demonstrate how current data practices occlude some the most violent forms of denigration and exploitation that structure advanced marginality, particularly the gendered, racialised, bordering and ableist practices underpinning state-citizen dynamics. Focusing principally on the UK context, I argue that the epistemic erasure committed features in and systematises a policy blindness to deep poverty for some of the most marginalised social groups making it harder to evidence its effects and address its causes across high-income countries.

关键词： data coverage deep poverty epistemic erasure non-private-household population welfare politics

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Recent Progress of Earth Observation Satellites in China

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空间科学学报 2024年第4期44卷 731-740页

作者： HUANG Shusong QI Wenping ZHANG Shuai XIA Tian WANG Jingqiao ZENG Yong China Centre for Resources Satellite Data and Application Beijing 100094

Currently,China has 32 Earth observation satellites in *** satellites can provide various data such as optical,multispectral,infrared,and *** spatial resolution of China Earth observation satellites ranges from low to medium to *** satellites possess the capability to observe across multiple spectral bands,under all weather conditions,and at all *** data of China Earth observation satellites has been widely used in fields such as natural resource detection,environmental monitoring and protection,disaster prevention and reduction,urban planning and mapping,agricultural and forestry surveys,land survey and geological prospecting,and ocean forecasting,achieving huge social *** article introduces the recent progress of Earth observation satellites in China since 2022,especially the satellite operation,data archiving,data distribution and data coverage.

关键词： China Earth Observation Satellites Satellite operation data archiving data distribution data coverage

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Assessment of oceanographic services for the monitoring of highly anthropised coastal lagoons: The Mar Menor case study

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ECOLOGICAL INFORMATICS 2024年 81卷

作者： Gimenez, Jose G. Granero, Alberto Senent-Aparicio, Javier Gomez-Jakobsen, Francisco Mercado, Jesus M. Blanco-Gomez, Pablo Ruiz, Juan M. Cecilia, Jose M. Univ Politecn Valencia UPV Camino Vera S-N Valencia 46011 Spain UCAM Univ Catolica Murcia Campus Jeronimos S-N Murcia 30107 Spain Inst Espanol Oceanog CSIC IEO Ctr Oceanog Malaga Puerto Pesquero S-N Fuengirola 29640 Malaga Spain Ctr Oceanog Murcia CSIC Inst Espanol Oceanog IEO C-Varadero 1 Murcia 30740 Spain Vielca Ingn SA Avda Aragon 17 Valencia 46010 Spain

Ocean monitoring systems are designed for continuous monitoring of the seas and oceans to track their evolution and thus anticipate environmental issues. However, they are often based on Internet of Things (IoT) systems that are expensive, hard to maintain, and offer little spatial coverage. An emerging alternative is Satellite Remote Sensing (SRS) systems that offer good geographical coverage but, as a reliable and real-time monitoring system, they also face several challenges such as environmental conditions, spatio-temporal granularity, terrain oleography, etc. This paper introduces an easy-to-use software tool to crawl water-quality data from up to 6 satellite instruments (i.e. Sentinel 3A, Sentinel-3B, NOAA VIIRS, SNPP VIIRS, Aqua MODIS, Terra MODIS) of the European Space Agency's (ESA) Coopernicus system and NASA's Marine Environmental Monitoring Service. We also provide an in-depth analysis in terms of reliability and data coverage for the chlorophyll-a (Chl-a) in a highly anthropised local/regional context like the Mar Menor lagoon (Murcia, Spain), where serious socioenvironmental issues are arising due to the eutrophication process. Our results show a good linear correlation between in situ data, obtained by several Spanish public institutions since 2016, and data generated by the IRTMNN (Inverse Radiative Transfer Model-Neural Network) algorithm of Sentinel 3 in general, reaching coefficient correlation values close to 0.9. They also show that organic matter inputs from ephemeral streams are relevant in determining Chl-a concentrations. Moreover, the temporal coverage using a single instrument is rather limited, as no data were recorded for 80% of the days studied. This figure decreases to 30% when data from the 6 satellite instruments are combined, increasing the temporal granularity of the measurements from approximately 5 to 1.5 days, suggesting the need for a combination of these systems for a robust SRS system.

关键词： Coastal lagoons Chlorophyll -a Satellite remote sensing data coverage Quantitative validation

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