Pub Date : 2022-12-31DOI: 10.11922/11-6035.nasdc.2022.0012.zh
L. Luo, Tingting Liu, Lina Hu, Shanshan Cao, Wei Sun
Spruces are an important tree species in Xinjiang. Accurate estimation of spruce biomass plays an important role in evaluating forest ecological structure and forest carbon balance in Xinjiang. In this study, we collected the relevant literature of Xinjiang spruce biomass estimation model from CNKI, Web of Science and the National Public Service Platform for Standards Information by constructing a retrieval method. And we collated the literature and used CiteSpace software for visualized mapping, so as to create a dataset of biomass estimation models and parameters of spruces in Xinjiang from 1980 to 2021. Biomass estimation models consist of biomass estimation models based on measurable factors and biomass estimation models based on remote sensing, machine learning algorithm. The former has 13 types, 101 fitting formulas, applicable to the estimation of different spruce organs, and the ground biomass; the latter has 3 types, 12 fitting formulas, suitable for the estimation of spruce forest biomass. This dataset can provide model data support for the study on spruce biomass estimation in Xinjiang.
云杉是新疆重要的乔木树种。准确估算云杉生物量对评价新疆森林生态结构和森林碳平衡具有重要意义。本研究通过构建检索方法，从CNKI、Web of Science和国家标准信息公共服务平台上收集了新疆云杉生物量估算模型的相关文献。通过文献整理，利用CiteSpace软件进行可视化制图，建立了1980 - 2021年新疆云杉生物量估算模型和参数数据集。生物量估算模型包括基于可测量因子的生物量估算模型和基于遥感、机器学习算法的生物量估算模型。前者有13种类型，101个拟合公式，适用于云杉不同器官和地面生物量的估算;后者有3种类型，12种拟合公式，适用于云杉林生物量的估算。该数据集可为新疆云杉生物量估算研究提供模型数据支持。
{"title":"A dataset of biomass estimation models and parameters of spruces in Xinjiang from 1980 to 2021","authors":"L. Luo, Tingting Liu, Lina Hu, Shanshan Cao, Wei Sun","doi":"10.11922/11-6035.nasdc.2022.0012.zh","DOIUrl":"https://doi.org/10.11922/11-6035.nasdc.2022.0012.zh","url":null,"abstract":"Spruces are an important tree species in Xinjiang. Accurate estimation of spruce biomass plays an important role in evaluating forest ecological structure and forest carbon balance in Xinjiang. In this study, we collected the relevant literature of Xinjiang spruce biomass estimation model from CNKI, Web of Science and the National Public Service Platform for Standards Information by constructing a retrieval method. And we collated the literature and used CiteSpace software for visualized mapping, so as to create a dataset of biomass estimation models and parameters of spruces in Xinjiang from 1980 to 2021. Biomass estimation models consist of biomass estimation models based on measurable factors and biomass estimation models based on remote sensing, machine learning algorithm. The former has 13 types, 101 fitting formulas, applicable to the estimation of different spruce organs, and the ground biomass; the latter has 3 types, 12 fitting formulas, suitable for the estimation of spruce forest biomass. This dataset can provide model data support for the study on spruce biomass estimation in Xinjiang.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47258423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-31DOI: 10.11922/11-6035.noda.2022.0019.zh
Jiawei Guo, H. Ye, Chao Nie, B. Cui, Wenjiang Huang
The multiple cropping index is an important parameter for the evaluation of cultivated land fertility and agroecological evaluation. The development of remote sensing technology makes it possible to monitor multiple cropping indexes with high temporal and spatial resolution. Based on Sentinel-2 data, we used in this paper the Savitzky-Golay filtering method and the quadratic difference method to carry out a research on the extraction of the multiple cropping indexes on Hainan Island. We combined the ground sample data in 2020 for verification to produce a dataset of multiple cropping indexes on Hainan Island in 2016 and 2020. The overall accuracy of the multiple cropping indexes obtained by remote sensing extraction in this way is 91.9%, and the Kappa coefficient is 0.9. This dataset can be used as basic data for the analysis of temporal and spatial changes of cultivated lands in Hainan. Moreover, it can also provide data reference and decision support for Hainan Province to carry out the supervision of agricultural ecological resources and implement the sustainable development strategy of tropical high-efficiency agriculture.
{"title":"A dataset of multiple cropping indexes with the 10 m spatial resolution on Hainan Island in 2016 and 2020","authors":"Jiawei Guo, H. Ye, Chao Nie, B. Cui, Wenjiang Huang","doi":"10.11922/11-6035.noda.2022.0019.zh","DOIUrl":"https://doi.org/10.11922/11-6035.noda.2022.0019.zh","url":null,"abstract":"The multiple cropping index is an important parameter for the evaluation of cultivated land fertility and agroecological evaluation. The development of remote sensing technology makes it possible to monitor multiple cropping indexes with high temporal and spatial resolution. Based on Sentinel-2 data, we used in this paper the Savitzky-Golay filtering method and the quadratic difference method to carry out a research on the extraction of the multiple cropping indexes on Hainan Island. We combined the ground sample data in 2020 for verification to produce a dataset of multiple cropping indexes on Hainan Island in 2016 and 2020. The overall accuracy of the multiple cropping indexes obtained by remote sensing extraction in this way is 91.9%, and the Kappa coefficient is 0.9. This dataset can be used as basic data for the analysis of temporal and spatial changes of cultivated lands in Hainan. Moreover, it can also provide data reference and decision support for Hainan Province to carry out the supervision of agricultural ecological resources and implement the sustainable development strategy of tropical high-efficiency agriculture.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48890973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rubber plantation is one of the main artificial vegetation types in Hainan Island. As an important forest ecosystem in China’s tropical regions, rubber plantation plays an important role in the regional carbon and water cycle. Measuring the carbon and water fluxes is critical for estimating the carbon and water balance and energy exchange of rubber plantation. Since November 2009, near-surface CO2 and H2O fluxes observation have been carried out in Danzhou rubber plantation, including eddy covariance system and meteorological observation system. Up to now, it has accumulated flux and meteorological observation data for 12 years. This dataset organizes the rubber plantation flux and conventional meteorological data in Danzhou from 2010 to 2018, including net ecosystem productivity, ecosystem respiration, gross ecosystem productivity, latent heat flux, sensible heat flux, evapotranspiration, air temperature, air relative humidity, vapor pressure, wind speed, wind direction, atmospheric pressure, total radiation, net radiation, photosynthetically active radiation, soil temperature, soil water content and precipitation. This dataset can provide basis and reference for ecosystem evaluation and sustainable development planning in economic and social.
{"title":"A dataset of carbon and water fluxes and micrometerological elements in Danzhou rubber plantation (2010-2018)","authors":"Siqi Yang, Junyi Liu, Chuan Yang, G. Lan, Bonkeun Song, Zhixiang Wu","doi":"10.11922/11-6035.csd.2022.0063.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0063.zh","url":null,"abstract":"Rubber plantation is one of the main artificial vegetation types in Hainan Island. As an important forest ecosystem in China’s tropical regions, rubber plantation plays an important role in the regional carbon and water cycle. Measuring the carbon and water fluxes is critical for estimating the carbon and water balance and energy exchange of rubber plantation. Since November 2009, near-surface CO2 and H2O fluxes observation have been carried out in Danzhou rubber plantation, including eddy covariance system and meteorological observation system. Up to now, it has accumulated flux and meteorological observation data for 12 years. This dataset organizes the rubber plantation flux and conventional meteorological data in Danzhou from 2010 to 2018, including net ecosystem productivity, ecosystem respiration, gross ecosystem productivity, latent heat flux, sensible heat flux, evapotranspiration, air temperature, air relative humidity, vapor pressure, wind speed, wind direction, atmospheric pressure, total radiation, net radiation, photosynthetically active radiation, soil temperature, soil water content and precipitation. This dataset can provide basis and reference for ecosystem evaluation and sustainable development planning in economic and social.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45761397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-31DOI: 10.11922/11-6035.noda.2021.0016.zh
Jingjuan Liao, Bing Zhu, Yunlei Chang, Li Zhang
Mangrove forests are wetland ecosystems in the coastal zone with important ecological and eco-economic service values. At the same time, mangrove forests are vulnerable ecosystems, being under threat from both natural and anthropogenic forces, so mangrove monitoring is a permanent task. The development of remote sensing technology has provided an efficient and convenient means for mangrove monitoring. In this study, we adopted a support vector machine (SVM) classification method with Gaussian radial kernel function, penalty factor of 100 and Gamma function 0f 0.022 to obtain a dataset of mangrove forest changes on Hainan Island from 2015 to 2019 by using Gaofen-2 (GF-2) data in 2015, 2017 and 2019 in combination with field survey data. The overall classification accuracy of this dataset is more than 99%, and the data volume is 58.7 MB. It can be used as the basic data for the analysis of spatial and temporal changes of mangrove forests. It can also provide decision-making support for the restoration, protection and management of mangrove wetland ecosystems, and facilitate the ecological environment supervision in Hainan Province.
{"title":"A dataset of mangrove forest changes on Hainan Island based on GF-2 data during 2015–2019","authors":"Jingjuan Liao, Bing Zhu, Yunlei Chang, Li Zhang","doi":"10.11922/11-6035.noda.2021.0016.zh","DOIUrl":"https://doi.org/10.11922/11-6035.noda.2021.0016.zh","url":null,"abstract":"Mangrove forests are wetland ecosystems in the coastal zone with important ecological and eco-economic service values. At the same time, mangrove forests are vulnerable ecosystems, being under threat from both natural and anthropogenic forces, so mangrove monitoring is a permanent task. The development of remote sensing technology has provided an efficient and convenient means for mangrove monitoring. In this study, we adopted a support vector machine (SVM) classification method with Gaussian radial kernel function, penalty factor of 100 and Gamma function 0f 0.022 to obtain a dataset of mangrove forest changes on Hainan Island from 2015 to 2019 by using Gaofen-2 (GF-2) data in 2015, 2017 and 2019 in combination with field survey data. The overall classification accuracy of this dataset is more than 99%, and the data volume is 58.7 MB. It can be used as the basic data for the analysis of spatial and temporal changes of mangrove forests. It can also provide decision-making support for the restoration, protection and management of mangrove wetland ecosystems, and facilitate the ecological environment supervision in Hainan Province.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45868084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-31DOI: 10.11922/11-6035.ncdc.2021.0025.zh
Meirong Gao, Yaonan Zhang, Jianfang Kang
Based on the results of the Second National soil Survey, Gansu Soil Species was established to accumulate systematic, standardized and quantitative data of soil classification as a solid foundation for the development of soil science in Gansu province.This dataset is based on the processing and integration of Gansu Soil Species published by Gansu Science and Technology Press in 1992. The original data and information of 285 soil species in the book (e.g. attribution and distribution, main characters, production performance summary, physical and chemical properties of profiles) are extracted and collected in a standardized, structured and digital way, integrated with 8 specialized subject data tables indexed by species ID and species name, and conducive to the development of online query, including soil species classification, distribution and characteristics of main soil types, basic information and distribution of soil species, sampling sites and occurrence layers of typical profiles, statistical physicochemical properties of typical profiles and soil species profiles, etc. This dataset can be widely used in regional land quality assessment, environmental effect research, soil carbon storage research, etc., providing significant scientific support for the promotion of new agricultural technology and rational utilization of soil resources.
{"title":"A dataset of Gansu soil species based on the Second National Soil Survey","authors":"Meirong Gao, Yaonan Zhang, Jianfang Kang","doi":"10.11922/11-6035.ncdc.2021.0025.zh","DOIUrl":"https://doi.org/10.11922/11-6035.ncdc.2021.0025.zh","url":null,"abstract":"Based on the results of the Second National soil Survey, Gansu Soil Species was established to accumulate systematic, standardized and quantitative data of soil classification as a solid foundation for the development of soil science in Gansu province.This dataset is based on the processing and integration of Gansu Soil Species published by Gansu Science and Technology Press in 1992. The original data and information of 285 soil species in the book (e.g. attribution and distribution, main characters, production performance summary, physical and chemical properties of profiles) are extracted and collected in a standardized, structured and digital way, integrated with 8 specialized subject data tables indexed by species ID and species name, and conducive to the development of online query, including soil species classification, distribution and characteristics of main soil types, basic information and distribution of soil species, sampling sites and occurrence layers of typical profiles, statistical physicochemical properties of typical profiles and soil species profiles, etc. This dataset can be widely used in regional land quality assessment, environmental effect research, soil carbon storage research, etc., providing significant scientific support for the promotion of new agricultural technology and rational utilization of soil resources.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41879989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-31DOI: 10.11922/11-6035.csd.2022.0039.zh
Han Wang, Qiao Liu, Yan Zhong, Yunyi Luo
The distribution of crevasses in mountain glaciers is of great significance for the study on glacier dynamics, ablation, and glacial instability-induced disasters. From 2016 to 2021, based on repeated aerial surveys during ablation seasons in the Hailuogou Glacier ablation areas on the eastern slope of Gongga Mountain, we obtained the annual high-resolution orthophoto images of the 4 km ice tongue of the glacier during the ablation period. Based on these co-registered images, the crevasses in Hailuogou ice tongue were visually interpreted and delineated from 2016 to 2021. We preliminarily analyzed the distribution characteristics and inter-annual variation of the crevasses. This dataset contains spatial information attributes like the crevasse length and orientation. It is the first set of survey results related to the structural glaciology of mountain glaciers in western China and it can provide data reference for the study on glacial hydrology, mass balance and dynamic models.
{"title":"A dataset of glacier crevasse distribution in the ablation areas of Hailuogou Glacier, Mt. Gongga (2016–2021)","authors":"Han Wang, Qiao Liu, Yan Zhong, Yunyi Luo","doi":"10.11922/11-6035.csd.2022.0039.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0039.zh","url":null,"abstract":"The distribution of crevasses in mountain glaciers is of great significance for the study on glacier dynamics, ablation, and glacial instability-induced disasters. From 2016 to 2021, based on repeated aerial surveys during ablation seasons in the Hailuogou Glacier ablation areas on the eastern slope of Gongga Mountain, we obtained the annual high-resolution orthophoto images of the 4 km ice tongue of the glacier during the ablation period. Based on these co-registered images, the crevasses in Hailuogou ice tongue were visually interpreted and delineated from 2016 to 2021. We preliminarily analyzed the distribution characteristics and inter-annual variation of the crevasses. This dataset contains spatial information attributes like the crevasse length and orientation. It is the first set of survey results related to the structural glaciology of mountain glaciers in western China and it can provide data reference for the study on glacial hydrology, mass balance and dynamic models.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49074645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-31DOI: 10.11922/11-6035.csd.2021.0089.zh
Tong Wu, H. Liu, Bo Hu, Zirui Liu, Guang-ren Liu
Ultraviolet radiation data can provide data support for many fields such as agriculture, ecology, environmental science, materials science, and human health. They have important application value in ecosystem succession, climate change research and environmental impact assessment. But with so little observational data and a short time scale, obtaining accurate, long-time, and wide range UV radiation data will provide scientific data support for relevant research. Therefore, based on the observation data of existing stations, in this paper, we constructed a method suitable for the reconstruction of ultraviolet radiation at the national scale, and combined with the conventional meteorological data observed for a long time, so as to obtain a dataset of ultraviolet radiation reconstruction. During the production of this dataset, first, we got the historical data of total surface radiation in accordance with the "hybrid model". Then, we created the UV radiation estimation formula by using clear sky index and other parameters. Finally, we calculated the reconstructed UV radiation data of 705 observation stations in China followed by the process of accuracy verification. The time range of this dataset is during 2015–2020.
{"title":"A dataset of ultraviolet radiation reconstruction in China during 2015–2020","authors":"Tong Wu, H. Liu, Bo Hu, Zirui Liu, Guang-ren Liu","doi":"10.11922/11-6035.csd.2021.0089.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2021.0089.zh","url":null,"abstract":"Ultraviolet radiation data can provide data support for many fields such as agriculture, ecology, environmental science, materials science, and human health. They have important application value in ecosystem succession, climate change research and environmental impact assessment. But with so little observational data and a short time scale, obtaining accurate, long-time, and wide range UV radiation data will provide scientific data support for relevant research. Therefore, based on the observation data of existing stations, in this paper, we constructed a method suitable for the reconstruction of ultraviolet radiation at the national scale, and combined with the conventional meteorological data observed for a long time, so as to obtain a dataset of ultraviolet radiation reconstruction. During the production of this dataset, first, we got the historical data of total surface radiation in accordance with the \"hybrid model\". Then, we created the UV radiation estimation formula by using clear sky index and other parameters. Finally, we calculated the reconstructed UV radiation data of 705 observation stations in China followed by the process of accuracy verification. The time range of this dataset is during 2015–2020.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45364811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on ESA (European Space Agency) landcover data, national polar-orbiting partnership-visible infrared imaging radiometer suite (NPP-VIIRS) nighttime light data and Hainan provincial statistical data, we implemented the spatialization of Hainan Island’s Gross Domestic Product (GDP) in this article. According to the relationship between gross product of primary industry and landcover type, spatialization of Hainan Island gross product of primary industry was implemented. And by building the regression model between gross product of secondary and tertiary industries and the nighttime light index, Hainan Island gross product of secondary and tertiary industries is spatialized. Then the spatialization of GDP was realized by combining the results of spatialization of Hainan Island's primary industry, secondary and tertiary industries. Compared with Hainan provincial statistical data, the results show that the maximum relative errors of spatial distribution data and actual statistical data of gross product of primary industry, gross product of secondary and tertiary industries and GDP in each period are 3.25%, 9.57% and 7.49%, respectively, which indicates the dataset can better describe the spatial distribution of GDP in Hainan Island. In addition, this dataset can provide a decision-making basis for the government to formulate policies on economic development of Hainan Island, and provide data support for scholars to explore differences and trends in economic development of Hainan Island.
{"title":"A spatial distribution dataset for GDP in Hainan Island at 500 m from 2012 to 2020","authors":"Degang Zhang, Bowen Cheng, Jinfen Chen, Xiaoping Zhang","doi":"10.11922/11-6035.noda.2022.0012.zh","DOIUrl":"https://doi.org/10.11922/11-6035.noda.2022.0012.zh","url":null,"abstract":"Based on ESA (European Space Agency) landcover data, national polar-orbiting partnership-visible infrared imaging radiometer suite (NPP-VIIRS) nighttime light data and Hainan provincial statistical data, we implemented the spatialization of Hainan Island’s Gross Domestic Product (GDP) in this article. According to the relationship between gross product of primary industry and landcover type, spatialization of Hainan Island gross product of primary industry was implemented. And by building the regression model between gross product of secondary and tertiary industries and the nighttime light index, Hainan Island gross product of secondary and tertiary industries is spatialized. Then the spatialization of GDP was realized by combining the results of spatialization of Hainan Island's primary industry, secondary and tertiary industries. Compared with Hainan provincial statistical data, the results show that the maximum relative errors of spatial distribution data and actual statistical data of gross product of primary industry, gross product of secondary and tertiary industries and GDP in each period are 3.25%, 9.57% and 7.49%, respectively, which indicates the dataset can better describe the spatial distribution of GDP in Hainan Island. In addition, this dataset can provide a decision-making basis for the government to formulate policies on economic development of Hainan Island, and provide data support for scholars to explore differences and trends in economic development of Hainan Island.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45546662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-30DOI: 10.11922/11-6035.csd.2022.0057.zh
Yongfang Zhao, X. Tian, Youquan Ye, Fangjian Xu
{"title":"A dataset of trace elements in surface sediments from main rivers and intertidal zones in Jiaozhou Bay in 2015","authors":"Yongfang Zhao, X. Tian, Youquan Ye, Fangjian Xu","doi":"10.11922/11-6035.csd.2022.0057.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0057.zh","url":null,"abstract":"","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42460320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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