The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.
<p>The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.</p>
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , |
| Published: |
2024
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1852025653936783360 |
|---|---|
| author | Jie Song (60883) |
| author2 | Xin He (48101) Fei Zhang (85787) Weiwei Wang (105069) Ngai Weng Chan (19950010) Jingchao Shi (1938724) Mou Leong Tan (16954874) |
| author2_role | author author author author author author |
| author_facet | Jie Song (60883) Xin He (48101) Fei Zhang (85787) Weiwei Wang (105069) Ngai Weng Chan (19950010) Jingchao Shi (1938724) Mou Leong Tan (16954874) |
| author_role | author |
| dc.creator.none.fl_str_mv | Jie Song (60883) Xin He (48101) Fei Zhang (85787) Weiwei Wang (105069) Ngai Weng Chan (19950010) Jingchao Shi (1938724) Mou Leong Tan (16954874) |
| dc.date.none.fl_str_mv | 2024-10-25T17:38:33Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0312388.t007 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/The_evolution_of_the_standard_deviation_ellipse_model_parameters_for_Xinjiang_s_provinces_/27306742 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Ecology Sociology Inorganic Chemistry Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified standard deviation ellipse significant regional differences promoting industrial transformation past 15 years rapid economic development total carbon emissions related carbon emissions optimizing energy structures dominated energy structure carbon economic development growth rate fluctuated carbon emission areas energy carbon emissions paper integrates dmsp energy consumption intensity clear spatial clustering carbon emissions energy consumption economic growth peripheral areas clustering stabilized spatial variations spatial distribution spatial autocorrelation xlink "> urban agglomerations sized towns showing distinct short term results show provincial capitals provincial capital primary source population size mainly located later showed key cities higher frequencies generate long findings provided distribution characteristics continue rising concentrated around closely linked |
| dc.title.none.fl_str_mv | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_3545e2a4e9acc12810690fcadf88cd0b |
| identifier_str_mv | 10.1371/journal.pone.0312388.t007 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/27306742 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.Jie Song (60883)Xin He (48101)Fei Zhang (85787)Weiwei Wang (105069)Ngai Weng Chan (19950010)Jingchao Shi (1938724)Mou Leong Tan (16954874)EcologySociologyInorganic ChemistryScience PolicyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedstandard deviation ellipsesignificant regional differencespromoting industrial transformationpast 15 yearsrapid economic developmenttotal carbon emissionsrelated carbon emissionsoptimizing energy structuresdominated energy structurecarbon economic developmentgrowth rate fluctuatedcarbon emission areasenergy carbon emissionspaper integrates dmspenergy consumption intensityclear spatial clusteringcarbon emissionsenergy consumptioneconomic growthperipheral areasclustering stabilizedspatial variationsspatial distributionspatial autocorrelationxlink ">urban agglomerationssized townsshowing distinctshort termresults showprovincial capitalsprovincial capitalprimary sourcepopulation sizemainly locatedlater showedkey citieshigher frequenciesgenerate longfindings provideddistribution characteristicscontinue risingconcentrated aroundclosely linked<p>The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces.</p>2024-10-25T17:38:33ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0312388.t007https://figshare.com/articles/dataset/The_evolution_of_the_standard_deviation_ellipse_model_parameters_for_Xinjiang_s_provinces_/27306742CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/273067422024-10-25T17:38:33Z |
| spellingShingle | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. Jie Song (60883) Ecology Sociology Inorganic Chemistry Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified standard deviation ellipse significant regional differences promoting industrial transformation past 15 years rapid economic development total carbon emissions related carbon emissions optimizing energy structures dominated energy structure carbon economic development growth rate fluctuated carbon emission areas energy carbon emissions paper integrates dmsp energy consumption intensity clear spatial clustering carbon emissions energy consumption economic growth peripheral areas clustering stabilized spatial variations spatial distribution spatial autocorrelation xlink "> urban agglomerations sized towns showing distinct short term results show provincial capitals provincial capital primary source population size mainly located later showed key cities higher frequencies generate long findings provided distribution characteristics continue rising concentrated around closely linked |
| status_str | publishedVersion |
| title | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| title_full | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| title_fullStr | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| title_full_unstemmed | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| title_short | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| title_sort | The evolution of the standard deviation ellipse model parameters for Xinjiang’s provinces. |
| topic | Ecology Sociology Inorganic Chemistry Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified standard deviation ellipse significant regional differences promoting industrial transformation past 15 years rapid economic development total carbon emissions related carbon emissions optimizing energy structures dominated energy structure carbon economic development growth rate fluctuated carbon emission areas energy carbon emissions paper integrates dmsp energy consumption intensity clear spatial clustering carbon emissions energy consumption economic growth peripheral areas clustering stabilized spatial variations spatial distribution spatial autocorrelation xlink "> urban agglomerations sized towns showing distinct short term results show provincial capitals provincial capital primary source population size mainly located later showed key cities higher frequencies generate long findings provided distribution characteristics continue rising concentrated around closely linked |