This data set contains soil organic carbon properties under the impervious surfaces areas (ISA) and Pervious Surface Area (PSA) of 41 cities in China. Field samplings were conducted during 2013-2014. The observed soil attribute elements include BD(bulk density), SOCC(soil organic carbon content), SOCD(soil organic carbon density), EC(electrical conductivity),et al.
采集时间 | 2013/01/01 - 2014/12/31 |
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采集地点 | mainland China |
数据量 | 119.6 KiB |
数据格式 | excel |
坐标系 |
Nation-wide soil sampling was conducted in 41 cities that were evenly distributed across China during 2013–2014 . The selected cities were either provincial capitals or representative cities at the regional scale. They covered all major climate regimes, vegetation types and soil types in China, except for the Tibet Plateau. Soil samples were taken from multiple sites in each city. To guaranty that the sampling sites in a city were evenly distributed, each sample site belonged to a different city district. In addition, observations from previous studies in the Chendu city and Yixin city were compiled and added to this dataset.
The sampled ISA types included pavements, highways, patios, driveways, parking lots etc. Field surveys and remote sensing analysis have confirmed that the sealing of impervious soils and the land cover/vegetation types (trees, shrubs, lawns, bare land, vegetable fields ect) of the adjacent pervious surface area (PSA) have been stable for over ten years at the sampling sites (detailed information of the sampling sites are found in the data file). At each site, three representative sampling plots, at least 10 m apart from each other, were set up under the ISA with three paired sampling plots in an adjacent PSA for comparison. A 100 cm depth profile pit was dug in each plot. Using 100 cm3 sample rings, soil profiles in the pits were sampled at 20 cm intervals to 100 cm depth. Technosols were thought to contain large amount of artefacts such as bricks, glass, etc. (FOA, 2015; Lorenz & Lal, 2009). However, our study across China found that most of the Ekranic (sealed) Technosols profiles has a clear boundary between the building material layers and the soil. These soils didn’t have extraordinary large amount of artefacts mixed in. Where the boundary is unclear, we treated the surface layers with large amount of hard building materials, where artefacts > 0.15 mm accounted for over half of the soil weight or volume, as the building material layers and only sampled the soils below them. Samples with notable additions of anthropogenic artefacts mixed in the soil were discarded, because we were unsure if they represented the building materials or the soils. These samples (ID# XJBIZC0001-XJBIZC4356) are currently stored in the Herbarium of the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China. We measured the soil bulk density (BD) and SOC content in each soil sample and then calculated the SOC density by multiplying them together. All samples were air-dried, grounded and sieved at 0.15 mm. BD was measured using the volumetric ring method. To match the methodology of the Second China’s National Soil Surveys that provided information of the background SOC density, the SOC content was measured using the Mebius method involving Walkley-Black acid digestion. SOC density was calculated according to dry BD (g cm-3) and SOC content based on a soil depth of 20 cm. For each soil layer, the SOC densities of the three sampling plots in a site were averaged to derive the site-level mean SOC density.
The data quality is good.
# | 标题 | 文件大小 |
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1 | observations of soil organic carbon density under impervious surfaces of China.xlsx | 119.6 KiB |
# | 时间 | 姓名 | 用途 |
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1 | 2024/11/06 06:44 | 洪*鹏 |
学生学习锻炼数据收集 分析处理的能力, 获取新疆地区多源数据
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2 | 2024/10/17 04:51 | 许*瑾 |
我们希望借助您的数据进一步量化我国当前土壤碳汇及影响因素。
我们声明,在使用数据时,一定会严格按照要求注引用。谢谢!
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3 | 2024/10/14 18:27 | 刘*晖 |
收集全球地表硬化下的数据,会在论文中披露数据集的来源。
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4 | 2024/05/25 00:45 | 王* |
Paper title:耦合PLUS-InVEST模型的黄河流域碳储量时空演变及多情景预测
Paper abstract:目前我国正处于城市化快速发展阶段,黄河流域城市群作为我国社会经济发展的重要区域,却因流域生态环境脆弱,长期处于高负载状态。因此,对黄河流域碳储量进行预测和合理规划,对其可持续发展至关重要。本研究基于PLUS模型以黄河流域为研究对象,运用该区域2000-2020年的LUCC(Land use and cover change)数据,分析了研究区域内土地利用的时空变化格局,耦合InVEST模型估算了在不同情景下2050年黄河流域碳储量的空间分布格局。结果表明:(1)2000—2020年,黄河流域土地利用变化主要表现为耕地和未利用地面积减少,林地、草地、水域和建设用地面积增加。(2)在五种不同的发展情景下,2050年黄金情景更充分地利用了未利用地和草地面积,同时抑制了建设用地的扩张,总体上有利于生态用地的发展。(3)2050年黄河流域的碳储量分布为,位于东南山区的林地碳密度较大,而位于研究区西北方的未利用地和水域的碳密度最小。在五种发展情景中,黄金情景下2050年碳储量相较于2020年增加量最大,增加了5.69×107 t。
Paper type:期刊论文
Tutor:艳燕
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5 | 2023/07/07 23:22 | 夏*波 |
用于研究沙漠冻土的研究区分布划分,将冻土在沙漠当中的分布做出一个分类
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6 | 2023/07/04 07:01 | 董* |
计算有机碳,看有机碳的时空变化,是什么因素引起
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7 | 2023/06/08 16:26 | 何*皓 |
论文题目:中国典型城市绿地碳储量研究
论文摘要:城市绿地在碳循环中承担着重要作用。然而现存研究缺乏在区域尺度上对不同气候区城市绿地土壤有机碳特征进行对比分析以及对绿地未来碳汇潜力的估测。本研究以三个中国典型城市(西安、成都、上海)绿地土壤有机碳为研究对象,采用数据整合的研究手段,分析不同城市之间不同功能区绿地土壤有机碳分布特征;并结合统计模型,估计未来城市绿地土壤有机碳储量。结果表明:成都市绿地土壤有机碳密度显著高于上海和西安;三座城市中草本覆盖类型下土壤有机碳密度最低;各城市公园绿地相较于其他功能区的有机碳密度含量都较高;自城市中心过渡至郊区,成都和上海市绿地土壤有机碳密度呈现城中大于城市边缘的特征,但是西安出现了城郊>城中>城市边缘的特征。随着城市化年份的增加,成都市绿地土壤有机碳密度呈现缓慢增加的趋势;上海市呈现递减趋势;西安市呈现先减小后增加的趋势。对2010—2020年城市绿地土壤碳密度增量分析表明,年成都、西安城市平均约补偿了城市化导致的碳损失87.7%和20.1%。上海市城市绿地土壤有机碳密度减少了2.54 kg/m2,贡献了更多的城市碳排放。
论文类型:学士论文
导师姓名:何俊皓
申请原因:论文中需要城市不透水路面下的土壤有机碳数据进一步估算城市有机碳储量。
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8 | 2023/04/02 00:51 | 安* |
参加职称评定,攥写职称论文,需下载数据做实验
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9 | 2022/11/16 04:32 | 尹*雷 |
论文题目:城市化进程土壤碳动态研究
论文摘要:
论文类型:期刊论文
导师姓名:邹元春
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10 | 2022/10/16 06:30 | 毕* |
该数据对城市化方面的研究工作有重要用途,申请人迫切需要这样一份数据支撑相关科研项目。请务必批准下载。
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Impervious Surface Area Pervious Surface Area bulk density soil organic carbon content soil organic carbon density electrical conductivity
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