Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Dynamic Backup Sharing Scheme of Service Function Chains in NFV

Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in response to failures.However,as a compromise,these solutions result in high resource consumption due to device maintenance.In this paper,we propose a novel method named dynamic backup sharing(DBS)that allows SFCs to dynamically share backups to reduce resource consumption.DBS formulates the problem of sharing backups among different VNFs as an integer linear programming(ILP).Thereafter,we design a novel online algorithm based on dynamic programming to solve the problem.The experimental results indicate that DBS outperforms state-ofthe-art works by reducing resource consumption and improving the number of accepted requests.

Mapping the hotspots and coldspots of ecosystem services in conservation priority setting

Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services （ES） conservation. However, little research has identified and tested the compactness and efficiency of their ES hotspots and coldspots, which may weaken the effectiveness of ecological conservation. In this study, based on the RUSLE model and Getis-Ord Gi＊ statistics, we quantified the variation of annual soil conservation services （SC） and identified the statistically significant hotspots and coldspots in Shaanxi Province of China from 2000 to 2013. The results indicate that, 1） areas with high SC presented a significantly increasing trend as well, while areas with low SC only changed slightly; 2） SC hotspots and coldspots showed an obvious spatial differentiation--the hotspots were mainly spatially ag- gregated in southern Shaanxi, while the coldspots were mainly distributed in the Guanzhong Basin and Sand-windy Plateau; and 3） the identified hotspots had the highest capacity of providing SC, with 29.6% of the total area providing 59.7% of the total service. In contrast, the coldspots occupied 46.3% of the total area, but only provided 17.2% of the total SC. In addition to conserving single ES, the Getis-Ord Gi＊ statistics method can also help identify multi-functional priority areas for conserving multiple ES and biodiversity.

What are the appropriate mapping units for ecosystem service assessments?A systematic review

Context:Without clear understanding of the units used for ecosystem service(ES)mapping,ES assessment accuracy and the practical application of ES knowledge will be hampered.Method:We systematically reviewed 106 studies over the past 11 years to explore the type,characteristic pattern and deficiencies of mapping units.Result:We proposed that ES mapping units can be categorized into minimal unit for assessing ESs using corresponding indicators and methods,and aggregated unit for analysis and application based on research objectives,and classified the mapping units into five common types.Of the 12 characterizing variables of ES mapping studies,some have been shown to introduce a difference in the selection of mapping units and to exhibit characteristic patterns.We also found that the accuracy of ES assessments based on minimal units was lacking,and aggregated units were insufficient to establish a link between ES knowledge and practice.Conclusion:Herein,we propose possible solutions such as the use of fine spatial resolution grids and the introduction of additional data beyond land cover as supplements to improve the assessment accuracy.To enhance the availability of the results for practice,aggregated units connected with urban planning units should be established at a spatial level suitable for urban management.

Urban restaurants and online food delivery during the COVID-19 pandemic:a spatial and socio-demographic analysis

In this research,we analyzed the delivery service areas of restaurants,customer satisfaction,and restaurant sales of urban restaurants during the COVID-19 pandemic.We obtained the datasets on food ordering options and restaurant rankings based on Google Maps,Open Street Map,and widely known online food order applications in Iran.Based on this analysis we further modeled suitable areas for future extension of restaurants.We analyzed the online food order data of restaurants’sales and food delivery reports for 1050 restaurants in the city of Tabriz.We collected and analyzed data on the restaurant locations,the number of food orders for each restaurant,and the number of customers and their locations.Our results revealed that the spatial dimension of the newly emerging food delivery areas is of utmost importance for the success of restaurants.This indicates that an optimal location is not longer only dependent on factors like population density and competitors in the direct vicinity but on the services density even from more distant competitors.The results indicate that an optimized spatial distribution of the restaurants together with efficient quality in services can contribute to optimistic urban development.

A digital earth prototype system:DEPS/CAS

Digital Earth is an information expression of the real Earth,and is a new way of understanding the Earth in the twenty-first century.This paper introduces a Digital Earth Prototype System(DEPS)developed at the Chinese Academy of Sciences(CAS)and supported by the Knowledge Innovation Program of the Chinese Academy of Sciences.Discussions are made to the theoretical model and technical framework of the Digital Earth,and its related key technologies on spatial information processing,spatial data warehouse technology,virtual reality technology,high-performance and parallel computing.The DEPS consists of seven sub-systems including the spatial data,metadata,model database,Grid geoscience computing,spatial information database,maps service and virtual reality.Meanwhile,we developed a series of application systems such as the environment monitoring for the Olympic Games 2008 in Beijing,natural disasters evaluation,digital city,digital archeology,Asia regional aerosol and climate change.The DEPS/CAS displayed the application ability and potential of the Digital Earth in three levels:the global,national and regional.

Text GCN-SW-KNN:a novel collaborative training multi-label classification method for WMS application themes by considering geographic semantics

Without explicit description of map application themes,it is difficult for users to discover desired map resources from massive online Web Map Services(WMS).However,metadata-based map application theme extraction is a challenging multi-label text classification task due to limited training samples,mixed vocabularies,variable length and content arbitrariness of text fields.In this paper,we propose a novel multi-label text classification method,Text GCN-SW-KNN,based on geographic semantics and collaborative training to improve classifica-tion accuracy.The semi-supervised collaborative training adopts two base models,i.e.a modified Text Graph Convolutional Network(Text GCN)by utilizing Semantic Web,named Text GCN-SW,and widely-used Multi-Label K-Nearest Neighbor(ML-KNN).Text GCN-SW is improved from Text GCN by adjusting the adjacency matrix of the heterogeneous word document graph with the shortest semantic distances between themes and words in metadata text.The distances are calculated with the Semantic Web of Earth and Environmental Terminology(SWEET)and WordNet dictionaries.Experiments on both the WMS and layer metadata show that the proposed methods can achieve higher F1-score and accuracy than state-of-the-art baselines,and demonstrate better stability in repeating experiments and robustness to less training data.Text GCN-SW-KNN can be extended to other multi-label text classification scenario for better supporting metadata enhancement and geospatial resource discovery in Earth Science domain.

A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created.However,challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist.The objective of this paper is to present a publically available Geospatial Search Engine(GSE)that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data.The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services.A procedure runs daily to update map server layers and metadata,and to eliminate servers that go offline.The GSE supports Web Map Services,ArcGIS services,and websites that have geospatial data for download.We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services.While enhancements to our GSE and to web crawler technology in general lie ahead,our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.

An integrated framework for automatic green building evaluation:A case study of China

With the burgeoning emphasis on sustainable construction practices in China,the demand for green building assessment has significantly escalated.The overall evaluation process comprises two key components:The acquisition of evaluation data and the evaluation of green scores,both of which entail considerable time and effort.Previous research predominantly concentrated on automating the latter process,often neglecting the exploration of automating the former in accordance with the Chinese green building assessment system.Furthermore,there is a pressing requirement for more streamlined management of structured standard knowledge to facilitate broader dissemination.In response to these challenges,this paper presents a conceptual framework that integrates building information modeling,ontology,and web map services to augment the efficiency of the overall evaluation process and the management of standard knowledge.More specifically,in accordance with the Assessment Standard for Green Building(GB/T 50378-2019)in China,this study innovatively employs visual programming software,Dynamo in Autodesk Revit,and the application programming interface of web map services to expedite the acquisition of essential architectural data and geographic information for green building assessment.Subsequently,ontology technology is harnessed to visualize the management of standard knowledge related to green building assessment and to enable the derivation of green scores through logical reasoning.Ultimately,a residential building is employed as a case study to validate the theoretical and technical feasibility of the developed automated evaluation conceptual framework for green buildings.The research findings hold valuable utility in providing a self-assessment method for applicants in the field.