During state perception of a power system, fragments of harmonic data are inevitably lost owing to the loss of synchronization signals, transmission delays, instrument failures, or other factors. A harmonic data recov...During state perception of a power system, fragments of harmonic data are inevitably lost owing to the loss of synchronization signals, transmission delays, instrument failures, or other factors. A harmonic data recovery method is proposed based on multivariate norm matrix in this paper. The proposed method involves dynamic time warping for correlation analysis of harmonic data, normalized cuts for correlation clustering of power-quality monitoring devices, and adaptive alternating direction method of multipliers for multivariable norm joint optimization. Compared with existing data recovery methods, our proposed method maintains excellent recovery accuracy without requiring prior information or optimization of the power-quality monitoring device. Simulation results on the IEEE 39-bus and IEEE 118-bus test systems demonstrate the low computational complexity of the proposed method and its robustness against noise. In addition, the application of the proposed method to field data from a real-world system provides consistent results with those obtained from simulations.展开更多
Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while r...Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.展开更多
This paper explores potential of Remote Sensing and Geospatial Information Systems as viable tools for data collection, processing, transformation and adjustment of cadastral data discrepancies often noted by geospati...This paper explores potential of Remote Sensing and Geospatial Information Systems as viable tools for data collection, processing, transformation and adjustment of cadastral data discrepancies often noted by geospatial practitioners during rasterization and vectorization of land related data. Necessary datasets were collected employing main approach/procedure of scanning, georeferencing, digitization, transformation and analysis in that order, to amalgamate and harmonize all datasets into one common projection and coordinate system （Universal Transverse Mercator （UTM） on Arc-Datum 1960）. Discrepancies in derived areas against recorded values in land registries were noted, smaller parcels exhibited smaller discrepancies and vice versa. Discrepancies were found to be directly proportional to the parcel areas/sizes although large parcels （〉 1000 m2） exhibited abnormally high discrepancies. This procedure yielded systematic discrepancies that could be minimized by use of a fifth order polynomial. Resultant residuals were found to be tolerably low and could be ignored for small parcels （〈 1000 m2）. Final outputs included automated GIS geodatabase cadastre, containing cadastral attributes harmonized to one projection and coordinate system that can be overlaid to other datasets from engineering design and construction works, geological and geotechnical investigation surveys, etc. tied to Remote Sensing data without the requirement of further transformations.展开更多
Forest biodiversity studies conducted across Europe use a multitude of forestry terms,often inconsistently.This hinders the comparability across studies and makes the assessment of the impacts of forest management on ...Forest biodiversity studies conducted across Europe use a multitude of forestry terms,often inconsistently.This hinders the comparability across studies and makes the assessment of the impacts of forest management on biodiversity highly context-dependent.Recent attempts to standardize forestry and stand description terminology mostly used a top-down approach that did not account for the perspectives and approaches of forest biodiversity experts.This work aims to establish common standards for silvicultural and vegetation definitions,creating a shared conceptual framework for a consistent study on the effects of forest management on biodiversity.We have identified both strengths and weaknesses of the silvicultural and vegetation information provided in forest biodiversity studies.While quantitative data on forest biomass and dominant tree species are frequently included,information on silvicultural activities and vegetation composition is often lacking,shallow,or based on broad and heterogeneous classifications.We discuss the existing classifications and their use in European forest biodiversity studies through a novel bottom-up and top-driven review process,and ultimately propose a common framework.This will enhance the comparability of forest biodiversity studies in Europe,and puts the basis for effective implementation and monitoring of sustainable forest management policies.The standards here proposed are potentially adaptable and applicable to other geographical areas and could be extended to other forest interventions.展开更多
The Datathon series is a global initiative designed to foster microbial data reuse through community-driven metadata harmonization.By convening researchers from specific geographic regions,each annual Datathon promote...The Datathon series is a global initiative designed to foster microbial data reuse through community-driven metadata harmonization.By convening researchers from specific geographic regions,each annual Datathon promotes standardized metadata practices,supports sequence data archiving,and enables collaborative reuse of microbial metabarcoding datasets.Following successful events in Latin America(2022-2023)and Africa(2024),upcoming Datathons are scheduled for China(June 1-5,2026)and the Polar regions(November 2026).Each three-day event combines inspiration,training,and collaboration,and is followed by a year of virtual courses,a data helpdesk,and the creation of consolidated datasets co-authored by data contributors.These efforts address critical gaps in metadata quality and accessibility,especially from underrepresented regions,enhancing the utility of publicly archived microbiome data.By empowering local researchers and promoting interoperability,the Datathons aim to build lasting,regionally grounded networks that contribute to a more inclusive,global understanding of microbial biodiversity.We invite participation and collaboration in these upcoming events.展开更多
Data harmonization and documentation of the data processing are essential prerequisites for enabling Canonical Analysis Workflows.The recently revised Terabyte-scale air quality database system,which the Tropospheric ...Data harmonization and documentation of the data processing are essential prerequisites for enabling Canonical Analysis Workflows.The recently revised Terabyte-scale air quality database system,which the Tropospheric Ozone Assessment Report(TOAR)created,contains one of the world's largest collections of near-surface air quality measurements and considers FAIR data principles as an integral part.A special feature of our data service is the on-demand processing and product generation of several air quality metrics directly from the underlying database.In this paper,we show that the necessary data harmonization for establishing such online analysis services goes much deeper than the obvious issues of common data formats,variable names,and measurement units,and we explore how the generation of FAIR Digital Objects(FDO)in combination with automatically generateddocumentation may support Canonical Analysis Workflows for airquality and related data.展开更多
基金supported in part by the Science and Technology Project of China Southern Power Grid (No. 090000KK52190169/SZKJXM2019669)in part by the Open Fund of State Key Laboratory of Power System and Generation Equipment,Tsinghua University (No. SKLD21KM04)。
文摘During state perception of a power system, fragments of harmonic data are inevitably lost owing to the loss of synchronization signals, transmission delays, instrument failures, or other factors. A harmonic data recovery method is proposed based on multivariate norm matrix in this paper. The proposed method involves dynamic time warping for correlation analysis of harmonic data, normalized cuts for correlation clustering of power-quality monitoring devices, and adaptive alternating direction method of multipliers for multivariable norm joint optimization. Compared with existing data recovery methods, our proposed method maintains excellent recovery accuracy without requiring prior information or optimization of the power-quality monitoring device. Simulation results on the IEEE 39-bus and IEEE 118-bus test systems demonstrate the low computational complexity of the proposed method and its robustness against noise. In addition, the application of the proposed method to field data from a real-world system provides consistent results with those obtained from simulations.
基金supported by the National Natural Science Foundation of China(42271360 and 42271399)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(CAST)(2020QNRC001)the Fundamental Research Funds for the Central Universities,China(2662021JC013,CCNU22QN018)。
文摘Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.
文摘This paper explores potential of Remote Sensing and Geospatial Information Systems as viable tools for data collection, processing, transformation and adjustment of cadastral data discrepancies often noted by geospatial practitioners during rasterization and vectorization of land related data. Necessary datasets were collected employing main approach/procedure of scanning, georeferencing, digitization, transformation and analysis in that order, to amalgamate and harmonize all datasets into one common projection and coordinate system （Universal Transverse Mercator （UTM） on Arc-Datum 1960）. Discrepancies in derived areas against recorded values in land registries were noted, smaller parcels exhibited smaller discrepancies and vice versa. Discrepancies were found to be directly proportional to the parcel areas/sizes although large parcels （〉 1000 m2） exhibited abnormally high discrepancies. This procedure yielded systematic discrepancies that could be minimized by use of a fifth order polynomial. Resultant residuals were found to be tolerably low and could be ignored for small parcels （〈 1000 m2）. Final outputs included automated GIS geodatabase cadastre, containing cadastral attributes harmonized to one projection and coordinate system that can be overlaid to other datasets from engineering design and construction works, geological and geotechnical investigation surveys, etc. tied to Remote Sensing data without the requirement of further transformations.
基金This review was funded by the EU Framework Programme Horizon 2020 through the COST Association(www.cost.eu):COST Action CA18207:BOTTOMS-UP–Biodiversity of Temperate Forest Taxa Orienting Management Sustainability by Unifying Perspectives.TC and TS acknowledge the support of the NBFC to the University of Padova,funded by the Italian Ministry of University and Research,PNRR,Missione 4 Componente 2,“Dalla ricerca all’impresa”,Investimento 1.4,Project CN00000033.
文摘Forest biodiversity studies conducted across Europe use a multitude of forestry terms,often inconsistently.This hinders the comparability across studies and makes the assessment of the impacts of forest management on biodiversity highly context-dependent.Recent attempts to standardize forestry and stand description terminology mostly used a top-down approach that did not account for the perspectives and approaches of forest biodiversity experts.This work aims to establish common standards for silvicultural and vegetation definitions,creating a shared conceptual framework for a consistent study on the effects of forest management on biodiversity.We have identified both strengths and weaknesses of the silvicultural and vegetation information provided in forest biodiversity studies.While quantitative data on forest biomass and dominant tree species are frequently included,information on silvicultural activities and vegetation composition is often lacking,shallow,or based on broad and heterogeneous classifications.We discuss the existing classifications and their use in European forest biodiversity studies through a novel bottom-up and top-driven review process,and ultimately propose a common framework.This will enhance the comparability of forest biodiversity studies in Europe,and puts the basis for effective implementation and monitoring of sustainable forest management policies.The standards here proposed are potentially adaptable and applicable to other geographical areas and could be extended to other forest interventions.
文摘The Datathon series is a global initiative designed to foster microbial data reuse through community-driven metadata harmonization.By convening researchers from specific geographic regions,each annual Datathon promotes standardized metadata practices,supports sequence data archiving,and enables collaborative reuse of microbial metabarcoding datasets.Following successful events in Latin America(2022-2023)and Africa(2024),upcoming Datathons are scheduled for China(June 1-5,2026)and the Polar regions(November 2026).Each three-day event combines inspiration,training,and collaboration,and is followed by a year of virtual courses,a data helpdesk,and the creation of consolidated datasets co-authored by data contributors.These efforts address critical gaps in metadata quality and accessibility,especially from underrepresented regions,enhancing the utility of publicly archived microbiome data.By empowering local researchers and promoting interoperability,the Datathons aim to build lasting,regionally grounded networks that contribute to a more inclusive,global understanding of microbial biodiversity.We invite participation and collaboration in these upcoming events.
文摘Data harmonization and documentation of the data processing are essential prerequisites for enabling Canonical Analysis Workflows.The recently revised Terabyte-scale air quality database system,which the Tropospheric Ozone Assessment Report(TOAR)created,contains one of the world's largest collections of near-surface air quality measurements and considers FAIR data principles as an integral part.A special feature of our data service is the on-demand processing and product generation of several air quality metrics directly from the underlying database.In this paper,we show that the necessary data harmonization for establishing such online analysis services goes much deeper than the obvious issues of common data formats,variable names,and measurement units,and we explore how the generation of FAIR Digital Objects(FDO)in combination with automatically generateddocumentation may support Canonical Analysis Workflows for airquality and related data.
