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| 1 | A standardized dataset of built-up areas of China’s cities with populations over 300,000 for the period 1990-2015显示文摘China’s urbanization has attracted a lot of attention due to its unprecedented pace and intensity in terms of land,population,and economic impact.However,due to the lack of consistent and harmonized data,little is known about the patterns and dynamics of the interaction between these different aspects over the past few decades.Along with the implementation of the 2030 Agenda for Sustainable Development,a standardized dataset for assessing the sustainability of urbanization in China is needed.In this paper,we used remote sensing data from multiple sources(time-series of Landsat and Sentinel images)to map the impervious surface area(ISA)at five-year intervals from 1990 to 2015 and then converted the results into a standardized dataset of the built-up area for 433 Chinese cities with 300,000 inhabitants or more.This dataset was produced following the well-established rules adopted by the United Nations(UN).Validation of the ISA maps in urban areas based on the visual interpretation of Google Earth images showed that the average overall accuracy(OA),producer’s accuracy(PA)and user’s accuracy(UA)were 91.24%,92.58%and 89.65%,respec-tively.Comparisons with other existing urban built-up area datasets derived from the National Bureau of Statistics of China,the World Bank and UN-habitat indicated that our dataset,namely the stan-dardized urban built-up area dataset for China(SUBAD-China),provides an improved description of the spatiotemporal character-istics of the urbanization process and is especially applicable to a combined analysis of the spatial and socio-economic domains in urban areas.Potential applications of this dataset include combin-ing the spatial expansion and demographic information provided by UN to calculate sustainable development indicators such as SDG 11.3.1.The dataset could also be used in other multidimensional syntheses related to the study of urbanization in China. | Huiping Jiang Zhongchang Sun Huadong Guo Qiang Xing Wenjie Du Guoyin Cai | 2022 | Big Earth Data2022，6，1： | 2 |
| 2 | 城市三维空间结构对碳排放影响的尺度效应显示文摘城市是碳排放最集中的区域,全面厘清城市空间结构对碳排放的影响对碳减排规划具有重要意义。以往研究主要关注城市二维结构与碳排放的关系,表明城市扩张是碳排放剧增的主要原因。虽然城市三维空间结构也会显著影响碳排放,然而其影响的尺度效应依然缺少深入分析。为此以广州市为例,结合相关性分析、随机森林探究三维空间结构与碳排放的关系,并揭示三维空间结构影响的尺度效应。研究结果表明:(1)(高层)建筑物密度、建筑覆盖率、容积率与人口密度是碳排放的关键影响因素,主要通过直接增加人类活动或加剧热岛效应使得能源消耗和碳排放增多;(2)三维空间结构对碳排放的影响具有明显的尺度效应。随着分析尺度的变化,碳排放受三维空间结构的不同方面主导;(3)广州作为紧凑型城市的代表,如果片面追求城市三维空间的紧凑布局将不利于低碳城市的发展。因此,相关部门应重视宏观尺度下的三维空间结构的合理布局,合理开发城市边缘地区,降低城市中心建筑物的紧凑布局,构建多中心的城市格局,以有效降低碳排放水平,促进低碳城市的构建与可持续发展。研究所得成果可为城市建筑三维空间布局的合理优化提供参考依据,助力“双碳”目标的实现。 | 何小钰 庄雅烨 邱穗萱 李桦 招扬 卢思言 林锦耀 | 2024 | 生态学报2024，44，2： | 1 |
| 3 | A comprehensive method for refining essential SDGs variables for land degradation monitoring based on the DPSIR framework显示文摘The United Nations adopted 17 Sustainable Development Goals(SDGs)to address societal,economic and environmental sustainability issues.The efficiency of SDGs monitoring could be improved by essential variables(EVs),which can help to better deal with massive data,interdisciplinary knowledge and workloads.However,in practice,effectively combining EVs with SDGs monitoring remains challenging.In this paper,we proposed a refining method of essential SDGs variables(ESDGVs)to land degradation.Firstly,we selected northwest China as our experimental region and extracted a group of variables related to land degradation from SDG indicators based on the DPSIR framework.Next,we identify the essential ones using a combined qualitative and quantitative methods with the criteria of feasibility,spatialization,and relevance which considered the issues of data acquisition,monitoring scale,and closeness to the land degradation.Finally,we analysed the monitoring role of ESDGVs.Results show that,compared to conventional observations,ESDGVs facilitate the monitoring and evaluation of regional SDGs with reduced efforts.And both climate and human activities have a facilitating or inhibiting effect on land degradation processes.In the future,we hope to have more mature data sets and consider adding more SDG indicators for ESDGVs’refinement. | Yijing Zhao Xuesheng Zhao Deqin Fan Yue Qiu | 2023 | International Journal of Digital Earth2023，16，1： | 0 |
| 4 | 现代人地系统科学认知与探测方法显示文摘人地系统是人类活动与地理环境相互联系、相互作用而形成的复杂适应系统,具有综合性、区域性、复杂性、开放性、动态性特征.人地系统空间识别、类型诊断和强度评估是现代人地系统科学和地理学综合研究的核心内容,是科学认知人地系统演化过程与机理、服务支撑人地系统协调与可持续发展决策的重要基础.本文基于人地关系地域系统理论和地理学“三主三分”方法,构建了自上而下的现代人地系统识别-诊断-评估科学认知体系,综合土地利用、人口密度、夜间灯光指数、感兴趣点等多源空间数据,利用决策树、空间聚类、人类足迹强度指数等定量模型方法,开展了2000~2020年中国人地系统地域空间分区、主要类型分类和作用强度分级探测研究.结果表明:(1)中国人地系统面积占比由53.9%增至54.1%,基本稳定在54%左右,空间上呈东南高、西北低的分异特征,平原地区、耕地和城市集中分布区的占比明显高于山地丘陵区和地广人稀地区.人地系统中生活功能区的面积占比由3.61%增至5.24%,生产和生态功能区占比分别由35.19%和61.20%降至34.66%和60.10%.(2)快速城镇化和乡村振兴发展促使城市型、村镇型人地系统面积扩大,分别增长了135.45%和9.59%,但新增主要源于农业型人地系统;受生态退耕和耕地扩张共同影响,农业型和生态型人地系统间存在相互转换,其面积分别减少1.06%和1.37%.(3)中国人地系统的人类足迹强度由9.28增至10.25,增幅为10%,呈现出高值区扩张、低值区缩减,人类活动持续加强且空间集聚化的特征.本研究分层次回答了人地系统分布、类型、等级等关键问题,深化了现代人地系统耦合过程-机理-格局的科学认知,可为人地系统协调和可持续发展决策提供参考依据. | 刘彦随 刘亚群 欧聪 | 2024 | 科学通报2024，69，3： | 0 |
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