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Peng Gong
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China

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Model description paper
Published: 23 July 2021 in Geoscientific Model Development
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Oil palm is the most productive oil crop that provides ∼ 40 % of the global vegetable oil supply, with 7 % of the cultivated land devoted to oil plants. The rapid expansion of oil palm cultivation is seen as one of the major causes for deforestation emissions and threatens the conservation of rain forest and swamp areas and their associated ecosystem services in tropical areas. Given the importance of oil palm in oil production and its adverse environmental consequences, it is important to understand the physiological and phenological processes of oil palm and its impacts on the carbon, water and energy cycles. In most global vegetation models, oil palm is represented by generic plant functional types (PFTs) without specific representation of its morphological, physical and physiological traits. This would cause biases in the subsequent simulations. In this study, we introduced a new specific PFT for oil palm in the global land surface model ORCHIDEE-MICT (v8.4.2, Organising Carbon and Hydrology in Dynamic Ecosystems–aMeliorated Interactions between Carbon and Temperature). The specific morphology, phenology and harvest process of oil palm were implemented, and the plant carbon allocation scheme was modified to support the growth of the branch and fruit component of each phytomer. A new age-specific parameterization scheme for photosynthesis, autotrophic respiration and carbon allocation was also developed for the oil palm PFT, based on observed physiology, and was calibrated by observations. The improved model generally reproduces the leaf area index, biomass density and fruit yield during the life cycle at 14 observation sites. Photosynthesis, carbon allocation and biomass components for oil palm also agree well with observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.

ACS Style

Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. Oil palm modelling in the global land surface model ORCHIDEE-MICT. Geoscientific Model Development 2021, 14, 4573 -4592.

AMA Style

Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, Peng Gong. Oil palm modelling in the global land surface model ORCHIDEE-MICT. Geoscientific Model Development. 2021; 14 (7):4573-4592.

Chicago/Turabian Style

Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. 2021. "Oil palm modelling in the global land surface model ORCHIDEE-MICT." Geoscientific Model Development 14, no. 7: 4573-4592.

Journal article
Published: 04 July 2021 in Land
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Biodiversity conservation is the cornerstone for sustainable development. Bold conservation targets provide the last opportunities to halt the human-driven mass extinction. Recently, bold conservation targets have been proposed to protect 30% or 50% of Earth. However, little is known about its potential impacts on cropland. We identify potential cropland losses when 30% and 50% of global terrestrial area is given back to nature by 2030/2050, at three spatial scales (global, biome and country) and using two approaches (“nature-only landscapes” and “shared landscapes”). We find that different targets, applied scales and approaches will lead to different cropland losses: (1) At the global scale, it is possible to protect 50% of the Earth while having minimum cropland losses. (2) At biome scale, 0.64% and 8.54% cropland will be lost globally in 2030 and 2050 under the nature-only approach while by contrast, the shared approach substantially reduces the number of countries confronted by cropland losses, demanding only 0% and 2.59% of global cropland losses in 2030 and 2050. (3) At the national scale, the nature-only approach causes losses of 3.58% and 10.73% of global cropland in 2030 and 2050, while the shared approach requires 0.77% and 7.55% cropland in 2030 and 2050. Our results indicate that bold conservation targets could be considered, especially when adopting the shared approach, and we suggest adopting ambitious targets (protecting at least 30% by 2030) at the UN Biodiversity Conference (COP 15) to ensure a sustainable future for Earth.

ACS Style

Jianqiao Zhao; Yue Cao; Le Yu; Xiaoxuan Liu; Yichuan Shi; Xiaoping Liu; Rui Yang; Peng Gong. Identifying Potential Cropland Losses When Conserving 30% and 50% Earth with Different Approaches and Spatial Scales. Land 2021, 10, 704 .

AMA Style

Jianqiao Zhao, Yue Cao, Le Yu, Xiaoxuan Liu, Yichuan Shi, Xiaoping Liu, Rui Yang, Peng Gong. Identifying Potential Cropland Losses When Conserving 30% and 50% Earth with Different Approaches and Spatial Scales. Land. 2021; 10 (7):704.

Chicago/Turabian Style

Jianqiao Zhao; Yue Cao; Le Yu; Xiaoxuan Liu; Yichuan Shi; Xiaoping Liu; Rui Yang; Peng Gong. 2021. "Identifying Potential Cropland Losses When Conserving 30% and 50% Earth with Different Approaches and Spatial Scales." Land 10, no. 7: 704.

Data description paper
Published: 01 June 2021 in Earth System Science Data
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The construction of terraces is a key soil conservation practice on agricultural land in China providing multiple valuable ecosystem services. Accurate spatial information on terraces is needed for both management and research. In this study, the first 30 m resolution terracing map of the entire territory of China is produced by a supervised pixel-based classification using multisource and multi-temporal data based on the Google Earth Engine (GEE) platform. We extracted time-series spectral features and topographic features from Landsat 8 images and the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) data, classifying cropland area (cultivated land of Globeland30) into terraced and non-terraced types through a random forest classifier. The overall accuracy and kappa coefficient were evaluated by 10 875 test samples and achieved values of 94 % and 0.72, respectively. For terrace class, the producer's accuracy (PA) was 79.945 %, and the user's accuracy (UA) was 71.149 %. The classification performed best in the Loess Plateau and southwestern China, where terraces are most numerous. Some northeastern, eastern-central, and southern areas had relatively high uncertainty. Typical errors in the mapping results are from the sloping cropland (non-terrace cropland with a slope of ≥ 5∘), low-slope terraces, and non-crop vegetation. Terraces are widely distributed in China, and the total terraced area was estimated to be 53.55 Mha (i.e., 26.43 % of China's cropland area) by pixel counting (PC) method and 58.46 ± 2.99 Mha (i.e., 28.85 % ± 1.48 % of China's cropland area) by error-matrix-based model-assisted estimation (EM) method. Elevation and slope were identified as the main features in the terrace/non-terrace classification, and multi-temporal spectral features (such as percentiles of NDVI, TIRS2, and BSI) were also essential. Terraces are more challenging to identify than other land use types because of the intra-class feature heterogeneity, interclass feature similarity, and fragmented patches, which should be the focus of future research. Our terrace mapping algorithm can be used to map large-scale terraces in other regions globally, and our terrace map will serve as a landmark for studies on multiple ecosystem service assessments including erosion control, carbon sequestration, and biodiversity conservation. The China terrace map is available to the public at https://doi.org/10.5281/zenodo.3895585 (Cao et al., 2020).

ACS Style

Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine. Earth System Science Data 2021, 13, 2437 -2456.

AMA Style

Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, Peng Gong. A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine. Earth System Science Data. 2021; 13 (5):2437-2456.

Chicago/Turabian Style

Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. 2021. "A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine." Earth System Science Data 13, no. 5: 2437-2456.

Journal article
Published: 17 April 2021 in International Journal of Environmental Research and Public Health
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Cities around the globe are embracing the Healthy Cities approach to address urban health challenges. Public awareness is vital for successfully deploying this approach but is rarely assessed. In this study, we used internet search queries to evaluate the public awareness of the Healthy Cities approach applied in Shenzhen, China. The overall situation at the city level and the intercity variations were both analyzed. Additionally, we explored the factors that might affect the internet search queries of the Healthy Cities approach. Our results showed that the public awareness of the approach in Shenzhen was low. There was a high intercity heterogeneity in terms of interest in the various components of the Healthy Cities approach. However, we did not find a significant effect of the selected demographic, environmental, and health factors on the search queries. Based on our findings, we recommend that the city raise public awareness of healthy cities and take actions tailored to health concerns in different city zones. Our study showed that internet search queries can be a valuable data source for assessing the public awareness of the Healthy Cities approach.

ACS Style

Jun Yang; Yutong Zhang; Yixiong Xiao; Shaoqing Shen; Mo Su; Yuqi Bai; Jingbo Zhou; Peng Gong. Using Internet Search Queries to Assess Public Awareness of the Healthy Cities Approach: A Case Study in Shenzhen, China. International Journal of Environmental Research and Public Health 2021, 18, 4264 .

AMA Style

Jun Yang, Yutong Zhang, Yixiong Xiao, Shaoqing Shen, Mo Su, Yuqi Bai, Jingbo Zhou, Peng Gong. Using Internet Search Queries to Assess Public Awareness of the Healthy Cities Approach: A Case Study in Shenzhen, China. International Journal of Environmental Research and Public Health. 2021; 18 (8):4264.

Chicago/Turabian Style

Jun Yang; Yutong Zhang; Yixiong Xiao; Shaoqing Shen; Mo Su; Yuqi Bai; Jingbo Zhou; Peng Gong. 2021. "Using Internet Search Queries to Assess Public Awareness of the Healthy Cities Approach: A Case Study in Shenzhen, China." International Journal of Environmental Research and Public Health 18, no. 8: 4264.

Commentary
Published: 05 April 2021 in Earth's Future
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Keeping the Earth system in a stable and resilient state, in order to safeguard Earth's life support systems while ensuring that Earth's benefits, risks and related responsibilities are equitably shared, constitutes the grand challenge for human development in the Anthropocene. Here, we describe a framework that the recently formed Earth Commission will use to define and quantify target ranges for a ‘safe and just corridor’ that meets these goals. Although ‘safe’ and ‘just’ Earth system targets are interrelated, we see safe as primarily referring to a stable Earth system and just targets as being associated with meeting human needs and reducing exposure to risks. To align safe and just dimensions, we propose to address the equity dimensions of each safe target for Earth system regulating systems and processes. The more stringent of the safe or just target ranges then defines the corridor. Identifying levers of social transformation aimed at meeting the safe and just targets and challenges associated with translating the corridor to actors at multiple scales present scope for future work.

ACS Style

Johan Rockström; Joyeeta Gupta; Timothy M. Lenton; Dahe Qin; Steven J. Lade; Jesse F. Abrams; Lisa Jacobson; Juan C. Rocha; Caroline Zimm; Xuemei Bai; Govindasamy Bala; Stefan Bringezu; Wendy Broadgate; Stuart E. Bunn; Fabrice DeClerck; Kristie L. Ebi; Peng Gong; Chris Gordon; Norichika Kanie; Diana M. Liverman; Nebojsa Nakicenovic; David Obura; Veerabhadran Ramanathan; Peter H. Verburg; Detlef P. van Vuuren; Ricarda Winkelmann. Identifying a Safe and Just Corridor for People and the Planet. Earth's Future 2021, 9, 1 .

AMA Style

Johan Rockström, Joyeeta Gupta, Timothy M. Lenton, Dahe Qin, Steven J. Lade, Jesse F. Abrams, Lisa Jacobson, Juan C. Rocha, Caroline Zimm, Xuemei Bai, Govindasamy Bala, Stefan Bringezu, Wendy Broadgate, Stuart E. Bunn, Fabrice DeClerck, Kristie L. Ebi, Peng Gong, Chris Gordon, Norichika Kanie, Diana M. Liverman, Nebojsa Nakicenovic, David Obura, Veerabhadran Ramanathan, Peter H. Verburg, Detlef P. van Vuuren, Ricarda Winkelmann. Identifying a Safe and Just Corridor for People and the Planet. Earth's Future. 2021; 9 (4):1.

Chicago/Turabian Style

Johan Rockström; Joyeeta Gupta; Timothy M. Lenton; Dahe Qin; Steven J. Lade; Jesse F. Abrams; Lisa Jacobson; Juan C. Rocha; Caroline Zimm; Xuemei Bai; Govindasamy Bala; Stefan Bringezu; Wendy Broadgate; Stuart E. Bunn; Fabrice DeClerck; Kristie L. Ebi; Peng Gong; Chris Gordon; Norichika Kanie; Diana M. Liverman; Nebojsa Nakicenovic; David Obura; Veerabhadran Ramanathan; Peter H. Verburg; Detlef P. van Vuuren; Ricarda Winkelmann. 2021. "Identifying a Safe and Just Corridor for People and the Planet." Earth's Future 9, no. 4: 1.

Journal article
Published: 01 April 2021 in Chinese Science Bulletin
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气候变化对人群健康造成巨大的威胁正在日益严峻,急需全球各国密切协作。为了评估气候变化对人群健康的影响,并寻找保障人群健康的应对措施,2015年《柳叶刀》杂志发表了《健康与气候变化:保护公众健康的政策响应》特邀报告,并启动了“柳叶刀倒计时:追踪健康与气候变化进展”项目,追踪全球在应对气候变化和保护人群健康方面的年度进展。清华大学受柳叶刀委员会邀请,联合国内外相关机构,首次共同发布了针对中国的2020柳叶刀倒计时报告,评估进展的指标涉及五大领域23个指标,并编写中国政策简报。从中国2020柳叶刀倒计时报告的所有指标中选取对中国最为迫切或者与中国的政策进展最为相关的内容,帮助决策者和公众了解中国应对气候变化和改善公众健康的最新进展。2020年的中国政策简报根据省级数据及省级结果进行评述,并提出以下政策建议:(1)强化部门间合作,将健康纳入各项气候变化政策,仍迫切需要卫生、环境、能源、经济、金融和教育等各个部门之间展开实质性合作。(2)增强突发卫生事件应急准备。新冠疫情过后,中国应同时加强对气候在健康卫生领域所造成的或即将造成的威胁的重视,并完全纳入应急防范和响应系统之内,以便于为未来的健康服务、医疗供应及基础设施需求事先做好准备。(3)强化科研支撑,提升认知水平,应充分调动媒体和学术界的力量以提升公众以及政界的认知程度。中国政府应及时更新《健康中国行动计划(2019-2030年)》,尽快应对气候变化所带来的健康挑战。(4)提升减缓气候变化的行动力度。加速煤炭淘汰进程对实现2060碳中和承诺非常必要,对中国继续推进大气污染防治也至关重要。中国政府应当取消化石燃料补贴。(5)确保新冠疫情后的经济复苏政策是对当前及未来我国人群健康的保障。中国为新冠疫情后经济复苏所作的各项决策将决定未来几年内公共卫生领域的整体局势,应将气候变化作为首要事项纳入其干预措施。

ACS Style

Wenjia Cai; Chi Zhang; Kaiping Sun; Siqi Ai; Yuqi Bai; Junzhe Bao; Bin Chen; Liangliang Cheng; Xueqin Cui; Hancheng Dai; Qian Di; Wenxuan Dong; Dejing Dou; Weicheng Fan; Xing Fan; Tong Gao; Yang Geng; Dabo Guan; Yafei Guo; Yixin Hu; Junyi Hua; Cunrui Huang; Hong Huang; Jianbin Huang; Kedi Jiao; Tingting Jiang; Gregor Kiesewetter; Zbigniew Klimont; Pete Lampard; Chuanxi Li; Qiwei Li; Tiantian Li; Ruiqi Li; Borong Lin; Hualiang Lin; Huan Liu; Qiyong Liu; Xiaobo Liu; Yufu Liu; Zhao Liu; Zhidong Liu; Zhu Liu; Shuhan Lou; Chenxi Lu; Yong Luo; Wei Ma; Alice McGushin; Yanlin Niu; Chao Ren; Zhehao Ren; Zengliang Ruan; Wolfgang Schöpp; Jing Su; Ying Tu; Jie Wang; Qiong Wang; Yaqi Wang; Yu Wang; Nick Watts; Congxi Xiao; Yang Xie; Hui Xiong; Mingfang Xu; Bing Xu; Lei Xu; Jun Yang; Lianping Yang; Le Yu; Yujuan Yue; Shaohui Zhang; Zhongchen Zhang; Jiyao Zhao; Liang Zhao; Mengzhen Zhao; Zhe Zhao; Jingbo Zhou; Peng Gong. 因地而异的气候变化健康影响需要因地而异的应对措施. Chinese Science Bulletin 2021, 1 .

AMA Style

Wenjia Cai, Chi Zhang, Kaiping Sun, Siqi Ai, Yuqi Bai, Junzhe Bao, Bin Chen, Liangliang Cheng, Xueqin Cui, Hancheng Dai, Qian Di, Wenxuan Dong, Dejing Dou, Weicheng Fan, Xing Fan, Tong Gao, Yang Geng, Dabo Guan, Yafei Guo, Yixin Hu, Junyi Hua, Cunrui Huang, Hong Huang, Jianbin Huang, Kedi Jiao, Tingting Jiang, Gregor Kiesewetter, Zbigniew Klimont, Pete Lampard, Chuanxi Li, Qiwei Li, Tiantian Li, Ruiqi Li, Borong Lin, Hualiang Lin, Huan Liu, Qiyong Liu, Xiaobo Liu, Yufu Liu, Zhao Liu, Zhidong Liu, Zhu Liu, Shuhan Lou, Chenxi Lu, Yong Luo, Wei Ma, Alice McGushin, Yanlin Niu, Chao Ren, Zhehao Ren, Zengliang Ruan, Wolfgang Schöpp, Jing Su, Ying Tu, Jie Wang, Qiong Wang, Yaqi Wang, Yu Wang, Nick Watts, Congxi Xiao, Yang Xie, Hui Xiong, Mingfang Xu, Bing Xu, Lei Xu, Jun Yang, Lianping Yang, Le Yu, Yujuan Yue, Shaohui Zhang, Zhongchen Zhang, Jiyao Zhao, Liang Zhao, Mengzhen Zhao, Zhe Zhao, Jingbo Zhou, Peng Gong. 因地而异的气候变化健康影响需要因地而异的应对措施. Chinese Science Bulletin. 2021; ():1.

Chicago/Turabian Style

Wenjia Cai; Chi Zhang; Kaiping Sun; Siqi Ai; Yuqi Bai; Junzhe Bao; Bin Chen; Liangliang Cheng; Xueqin Cui; Hancheng Dai; Qian Di; Wenxuan Dong; Dejing Dou; Weicheng Fan; Xing Fan; Tong Gao; Yang Geng; Dabo Guan; Yafei Guo; Yixin Hu; Junyi Hua; Cunrui Huang; Hong Huang; Jianbin Huang; Kedi Jiao; Tingting Jiang; Gregor Kiesewetter; Zbigniew Klimont; Pete Lampard; Chuanxi Li; Qiwei Li; Tiantian Li; Ruiqi Li; Borong Lin; Hualiang Lin; Huan Liu; Qiyong Liu; Xiaobo Liu; Yufu Liu; Zhao Liu; Zhidong Liu; Zhu Liu; Shuhan Lou; Chenxi Lu; Yong Luo; Wei Ma; Alice McGushin; Yanlin Niu; Chao Ren; Zhehao Ren; Zengliang Ruan; Wolfgang Schöpp; Jing Su; Ying Tu; Jie Wang; Qiong Wang; Yaqi Wang; Yu Wang; Nick Watts; Congxi Xiao; Yang Xie; Hui Xiong; Mingfang Xu; Bing Xu; Lei Xu; Jun Yang; Lianping Yang; Le Yu; Yujuan Yue; Shaohui Zhang; Zhongchen Zhang; Jiyao Zhao; Liang Zhao; Mengzhen Zhao; Zhe Zhao; Jingbo Zhou; Peng Gong. 2021. "因地而异的气候变化健康影响需要因地而异的应对措施." Chinese Science Bulletin , no. : 1.

Preprint content
Published: 01 April 2021
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Urbanicity is a growing environmental challenge for mental-health. While the impact of urban life on brain and behavior might be distinct in different sociocultural conditions and geographies, there might exist features shared between regions. To investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe, we developed a remote-sensing satellite-measure termed ‘UrbanSat’ quantifying population-density, a general measure of urbanicity. UrbanSat is correlated with brain volume, surface area and brain-network-connectivity in the medial prefrontal cortex and cerebellum, which mediate its effect on perspective-taking and depression- symptoms. Susceptibility to high population-density is greatest during childhood for the cerebellum and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it will enable assessing the impact of urbanicity on mental illness and resilience globally, especially in young people where prevention and early interventions are most effective.

ACS Style

Gunter Schumann; Jiayuan Xu; Xiaoxuan Liu; Alex Ing; Qiaojun Li; Wen Qin; Lining Guo; Conghong Huang; Jingliang Chen; Meiyun Wang; Zuojun Geng; Wenzhen Zhu; Bing Zhang; Weihua Liao; Shijun Qiu; Hui Zhang; Xiaojun Xu; Yongqiang Yu; Bo Gao; Tong Han; Guang-Bin Cui; Feng Chen; Junfang Xian; Jiance Li; Xi-Nian Zuo; Dawei Wang; Wen Shen; Yanwei Miao; Fei Yuan; Su Lui; Xiaochu Zhang; Kai Xu; Long Jiang Zhang; Zhaoxiang Ye; Tobias Banaschewski; Gareth Barker; Arun Bokde; Erin Quinlan; Herta Flor; Antoine Grigis; Hugh Garavan; Penny Gowland; Andreas Heinz; Rüdiger Brühl; Jean-Luc Martinot; Eric Artiges; Frauke Nees; Dimitri Papadopoulos Orfanos; Herve Lemaitre; Tomas Paus; Luise Poustka; Sarah Hohmann; Juliane Fröhner; Michael Smolka; Henrik Walter; Robert Whelan; Ran Goldblatt; Kevin Patrick; Vince Calhoun; Mulin Lijun; Meng Liang; Peng Gong; Edward Barker; Nicholas Clinton; Le Yu; Chunshui Yu; Qiang Luo; Huaigui Liu; Congying Chu; Feng Liu; IMAGEN Consortium. Satellite Imaging of Global Urbanicity relates to Brain and Behavior in Young People. 2021, 1 .

AMA Style

Gunter Schumann, Jiayuan Xu, Xiaoxuan Liu, Alex Ing, Qiaojun Li, Wen Qin, Lining Guo, Conghong Huang, Jingliang Chen, Meiyun Wang, Zuojun Geng, Wenzhen Zhu, Bing Zhang, Weihua Liao, Shijun Qiu, Hui Zhang, Xiaojun Xu, Yongqiang Yu, Bo Gao, Tong Han, Guang-Bin Cui, Feng Chen, Junfang Xian, Jiance Li, Xi-Nian Zuo, Dawei Wang, Wen Shen, Yanwei Miao, Fei Yuan, Su Lui, Xiaochu Zhang, Kai Xu, Long Jiang Zhang, Zhaoxiang Ye, Tobias Banaschewski, Gareth Barker, Arun Bokde, Erin Quinlan, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Herve Lemaitre, Tomas Paus, Luise Poustka, Sarah Hohmann, Juliane Fröhner, Michael Smolka, Henrik Walter, Robert Whelan, Ran Goldblatt, Kevin Patrick, Vince Calhoun, Mulin Lijun, Meng Liang, Peng Gong, Edward Barker, Nicholas Clinton, Le Yu, Chunshui Yu, Qiang Luo, Huaigui Liu, Congying Chu, Feng Liu, IMAGEN Consortium. Satellite Imaging of Global Urbanicity relates to Brain and Behavior in Young People. . 2021; ():1.

Chicago/Turabian Style

Gunter Schumann; Jiayuan Xu; Xiaoxuan Liu; Alex Ing; Qiaojun Li; Wen Qin; Lining Guo; Conghong Huang; Jingliang Chen; Meiyun Wang; Zuojun Geng; Wenzhen Zhu; Bing Zhang; Weihua Liao; Shijun Qiu; Hui Zhang; Xiaojun Xu; Yongqiang Yu; Bo Gao; Tong Han; Guang-Bin Cui; Feng Chen; Junfang Xian; Jiance Li; Xi-Nian Zuo; Dawei Wang; Wen Shen; Yanwei Miao; Fei Yuan; Su Lui; Xiaochu Zhang; Kai Xu; Long Jiang Zhang; Zhaoxiang Ye; Tobias Banaschewski; Gareth Barker; Arun Bokde; Erin Quinlan; Herta Flor; Antoine Grigis; Hugh Garavan; Penny Gowland; Andreas Heinz; Rüdiger Brühl; Jean-Luc Martinot; Eric Artiges; Frauke Nees; Dimitri Papadopoulos Orfanos; Herve Lemaitre; Tomas Paus; Luise Poustka; Sarah Hohmann; Juliane Fröhner; Michael Smolka; Henrik Walter; Robert Whelan; Ran Goldblatt; Kevin Patrick; Vince Calhoun; Mulin Lijun; Meng Liang; Peng Gong; Edward Barker; Nicholas Clinton; Le Yu; Chunshui Yu; Qiang Luo; Huaigui Liu; Congying Chu; Feng Liu; IMAGEN Consortium. 2021. "Satellite Imaging of Global Urbanicity relates to Brain and Behavior in Young People." , no. : 1.

Research article
Published: 26 March 2021 in Journal of Applied Ecology
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Direct effects of climate change (i.e., temperature rise, changes in seasonal precipitation, wind patterns, and atmospheric stability) affect fire regimes of boreal forests by altering fire behavior, fire seasons, and fuel moisture. Climate change also alters species composition and fuel characteristics, which subsequently alter fire regimes. However, indirect effects of climate change are often simplified or neglected in the direct climate‐fire relationship models and dynamic global vegetation models. This may result in high uncertainties associated with existing projections of fire regimes for climate change scenarios. Moreover, few studies have examined fire regime predictions beyond the 21st century, and consequently, how the fire regimes of boreal forests would respond to climate change at the long‐term (>100 years) is not clear. We develop a coupled modeling framework integrating direct and indirect effects of climate change to predict fire occurrence probability and burned area for boreal forests in northeastern China. We applied repeated‐measures ANOVA to quantify direct and indirect effects of climate change on fire regimes in the short (0‐50 years), medium (60‐100 years), and long‐term (150‐200 years). Results showed that for the 21st century, direct effects of climate change are likely to exert a stronger influence on fire regimes than indirect effects. However, increases in fire occurrence probability and burned area will accelerate the transition of boreal forests to temperate forests in the period 2100‐2200, and thereby reduce fire occurrence probability and burned area. This suggests that vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long‐term. Synthesis and applications. Vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long‐term. This finding suggested that policy makers may consider adaptive management by planting deciduous species to reduce fire occurrence probability and resistant management by reducing competition to promote boreal species under changing climate conditions.

ACS Style

Chao Huang; Hong S. He; Yu Liang; Todd J. Hawbaker; Paul D. Henne; Wenru Xu; Peng Gong; Zhiliang Zhu. The changes in species composition mediate direct effects of climate change on future fire regimes of boreal forests in northeastern China. Journal of Applied Ecology 2021, 58, 1336 -1345.

AMA Style

Chao Huang, Hong S. He, Yu Liang, Todd J. Hawbaker, Paul D. Henne, Wenru Xu, Peng Gong, Zhiliang Zhu. The changes in species composition mediate direct effects of climate change on future fire regimes of boreal forests in northeastern China. Journal of Applied Ecology. 2021; 58 (6):1336-1345.

Chicago/Turabian Style

Chao Huang; Hong S. He; Yu Liang; Todd J. Hawbaker; Paul D. Henne; Wenru Xu; Peng Gong; Zhiliang Zhu. 2021. "The changes in species composition mediate direct effects of climate change on future fire regimes of boreal forests in northeastern China." Journal of Applied Ecology 58, no. 6: 1336-1345.

Journal article
Published: 10 March 2021 in International Journal of Environmental Research and Public Health
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Mobility restrictions have been a heated topic during the global pandemic of coronavirus disease 2019 (COVID-19). However, multiple recent findings have verified its importance in blocking virus spread. Evidence on the association between mobility, cases imported from abroad and local medical resource supplies is limited. To reveal the association, this study quantified the importance of inter- and intra-country mobility in containing virus spread and avoiding hospitalizations during early stages of COVID-19 outbreaks in India, Japan, and China. We calculated the time-varying reproductive number (R t) and duration from illness onset to diagnosis confirmation (D oc), to represent conditions of virus spread and hospital bed shortages, respectively. Results showed that inter-country mobility fluctuation could explain 80%, 35%, and 12% of the variance in imported cases and could prevent 20 million, 5 million, and 40 million imported cases in India, Japan and China, respectively. The critical time for screening and monitoring of imported cases is 2 weeks at minimum and 4 weeks at maximum, according to the time when the Pearson’s Rs between R t and imported cases reaches a peak (>0.8). We also found that if local transmission is initiated, a 1% increase in intra-country mobility would result in 1430 (±501), 109 (±181), and 10 (±1) additional bed shortages, as estimated using the D oc in India, Japan, and China, respectively. Our findings provide vital reference for governments to tailor their pre-vaccination policies regarding mobility, especially during future epidemic waves of COVID-19 or similar severe epidemic outbreaks.

ACS Style

Zhehao Ren; Ruiyun Li; Tao Zhang; Bin Chen; Che Wang; Miao Li; Shuang Song; Yixiong Xiao; Bo Xu; Zhaoyang Liu; Chong Shen; Dabo Guan; Lin Hou; Ke Deng; Yuqi Bai; Peng Gong; Bing Xu. Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China. International Journal of Environmental Research and Public Health 2021, 18, 2826 .

AMA Style

Zhehao Ren, Ruiyun Li, Tao Zhang, Bin Chen, Che Wang, Miao Li, Shuang Song, Yixiong Xiao, Bo Xu, Zhaoyang Liu, Chong Shen, Dabo Guan, Lin Hou, Ke Deng, Yuqi Bai, Peng Gong, Bing Xu. Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China. International Journal of Environmental Research and Public Health. 2021; 18 (6):2826.

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Zhehao Ren; Ruiyun Li; Tao Zhang; Bin Chen; Che Wang; Miao Li; Shuang Song; Yixiong Xiao; Bo Xu; Zhaoyang Liu; Chong Shen; Dabo Guan; Lin Hou; Ke Deng; Yuqi Bai; Peng Gong; Bing Xu. 2021. "Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China." International Journal of Environmental Research and Public Health 18, no. 6: 2826.

Journal article
Published: 29 January 2021 in Remote Sensing
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Urban land use mapping is critical to understanding human activities in space. The first national mapping result of essential urban land use categories of China (EULUC-China) was released in 2019. However, the overall accuracies in some of the plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based mapping units are large with mixed land uses. To address this shortcoming, we proposed an area of interest (AOI)-based mapping approach, choosing Beijing as our study area. The mapping process includes two major steps. First, grids with different sizes (i.e., 300 m, 200 m, and 100 m) were derived from original land parcels to obtain classification units with a suitable size. Then, features within these grids were extracted from Sentinel-2 spectral data, point of interest (POI), and Tencent Easygo crowdedness data. These features were classified using a random forest (RF) classifier with AOI data, resulting in a 10-category map of EULUC. Second, we superimposed the AOIs layer on classified units to do some rectification and offer more details at the building scale. The overall accuracy of the AOI layer reached 98%, and the overall accuracy of the mapping results reached 77%. This study provides a fast method for accurate geographic sample collection, which substantially reduces the amount of fieldwork for sample collection and improves the classification accuracy compared to previous EULUC mapping. The detailed urban land use map could offer more support for urban planning and environmental policymaking.

ACS Style

Xiaoting Li; Tengyun Hu; Peng Gong; Shihong Du; Bin Chen; Xuecao Li; Qi Dai. Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method. Remote Sensing 2021, 13, 477 .

AMA Style

Xiaoting Li, Tengyun Hu, Peng Gong, Shihong Du, Bin Chen, Xuecao Li, Qi Dai. Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method. Remote Sensing. 2021; 13 (3):477.

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Xiaoting Li; Tengyun Hu; Peng Gong; Shihong Du; Bin Chen; Xuecao Li; Qi Dai. 2021. "Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method." Remote Sensing 13, no. 3: 477.

Discussion
Published: 28 January 2021 in Science Bulletin
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Yali Si; Fei Xu; Jie Wei; Lin Zhang; Nicholas Murray; Rui Yang; Keping Ma; Peng Gong. A systematic network-based migratory bird monitoring and protection system is needed in China. Science Bulletin 2021, 66, 955 -957.

AMA Style

Yali Si, Fei Xu, Jie Wei, Lin Zhang, Nicholas Murray, Rui Yang, Keping Ma, Peng Gong. A systematic network-based migratory bird monitoring and protection system is needed in China. Science Bulletin. 2021; 66 (10):955-957.

Chicago/Turabian Style

Yali Si; Fei Xu; Jie Wei; Lin Zhang; Nicholas Murray; Rui Yang; Keping Ma; Peng Gong. 2021. "A systematic network-based migratory bird monitoring and protection system is needed in China." Science Bulletin 66, no. 10: 955-957.

Health policy
Published: 02 December 2020 in The Lancet Public Health
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Wenjia Cai; Chi Zhang; Hoi Ping Suen; Siqi Ai; Yuqi Bai; Junzhe Bao; Bin Chen; Liangliang Cheng; Xueqin Cui; Hancheng Dai; Qian Di; Wenxuan Dong; Dejing Dou; Weicheng Fan; Xing Fan; Tong Gao; Yang Geng; Dabo Guan; Yafei Guo; Yixin Hu; Junyi Hua; Cunrui Huang; Hong Huang; Jianbin Huang; Tingting Jiang; Kedi Jiao; Gregor Kiesewetter; Zbigniew Klimont; Pete Lampard; Chuanxi Li; Qiwei Li; Ruiqi Li; Tiantian Li; Borong Lin; Hualiang Lin; Huan Liu; Qiyong Liu; Xiaobo Liu; Yufu Liu; Zhao Liu; Zhidong Liu; Zhu Liu; Shuhan Lou; Chenxi Lu; Yong Luo; Wei Ma; Alice McGushin; Yanlin Niu; Chao Ren; Zhehao Ren; Zengliang Ruan; Wolfgang Schöpp; Jing Su; Ying Tu; Jie Wang; Qiong Wang; Yaqi Wang; Yu Wang; Nick Watts; Congxi Xiao; Yang Xie; Hui Xiong; Mingfang Xu; Bing Xu; Lei Xu; Jun Yang; Lianping Yang; Le Yu; Yujuan Yue; Shaohui Zhang; Zhongchen Zhang; Jiyao Zhao; Liang Zhao; Mengzhen Zhao; Zhe Zhao; Jingbo Zhou; Peng Gong. The 2020 China report of the Lancet Countdown on health and climate change. The Lancet Public Health 2020, 6, e64 -e81.

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Wenjia Cai, Chi Zhang, Hoi Ping Suen, Siqi Ai, Yuqi Bai, Junzhe Bao, Bin Chen, Liangliang Cheng, Xueqin Cui, Hancheng Dai, Qian Di, Wenxuan Dong, Dejing Dou, Weicheng Fan, Xing Fan, Tong Gao, Yang Geng, Dabo Guan, Yafei Guo, Yixin Hu, Junyi Hua, Cunrui Huang, Hong Huang, Jianbin Huang, Tingting Jiang, Kedi Jiao, Gregor Kiesewetter, Zbigniew Klimont, Pete Lampard, Chuanxi Li, Qiwei Li, Ruiqi Li, Tiantian Li, Borong Lin, Hualiang Lin, Huan Liu, Qiyong Liu, Xiaobo Liu, Yufu Liu, Zhao Liu, Zhidong Liu, Zhu Liu, Shuhan Lou, Chenxi Lu, Yong Luo, Wei Ma, Alice McGushin, Yanlin Niu, Chao Ren, Zhehao Ren, Zengliang Ruan, Wolfgang Schöpp, Jing Su, Ying Tu, Jie Wang, Qiong Wang, Yaqi Wang, Yu Wang, Nick Watts, Congxi Xiao, Yang Xie, Hui Xiong, Mingfang Xu, Bing Xu, Lei Xu, Jun Yang, Lianping Yang, Le Yu, Yujuan Yue, Shaohui Zhang, Zhongchen Zhang, Jiyao Zhao, Liang Zhao, Mengzhen Zhao, Zhe Zhao, Jingbo Zhou, Peng Gong. The 2020 China report of the Lancet Countdown on health and climate change. The Lancet Public Health. 2020; 6 (1):e64-e81.

Chicago/Turabian Style

Wenjia Cai; Chi Zhang; Hoi Ping Suen; Siqi Ai; Yuqi Bai; Junzhe Bao; Bin Chen; Liangliang Cheng; Xueqin Cui; Hancheng Dai; Qian Di; Wenxuan Dong; Dejing Dou; Weicheng Fan; Xing Fan; Tong Gao; Yang Geng; Dabo Guan; Yafei Guo; Yixin Hu; Junyi Hua; Cunrui Huang; Hong Huang; Jianbin Huang; Tingting Jiang; Kedi Jiao; Gregor Kiesewetter; Zbigniew Klimont; Pete Lampard; Chuanxi Li; Qiwei Li; Ruiqi Li; Tiantian Li; Borong Lin; Hualiang Lin; Huan Liu; Qiyong Liu; Xiaobo Liu; Yufu Liu; Zhao Liu; Zhidong Liu; Zhu Liu; Shuhan Lou; Chenxi Lu; Yong Luo; Wei Ma; Alice McGushin; Yanlin Niu; Chao Ren; Zhehao Ren; Zengliang Ruan; Wolfgang Schöpp; Jing Su; Ying Tu; Jie Wang; Qiong Wang; Yaqi Wang; Yu Wang; Nick Watts; Congxi Xiao; Yang Xie; Hui Xiong; Mingfang Xu; Bing Xu; Lei Xu; Jun Yang; Lianping Yang; Le Yu; Yujuan Yue; Shaohui Zhang; Zhongchen Zhang; Jiyao Zhao; Liang Zhao; Mengzhen Zhao; Zhe Zhao; Jingbo Zhou; Peng Gong. 2020. "The 2020 China report of the Lancet Countdown on health and climate change." The Lancet Public Health 6, no. 1: e64-e81.

Author correction
Published: 02 December 2020 in Nature Communications
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A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5

ACS Style

Zhu Liu; Philippe Ciais; Zhu Deng; Ruixue Lei; Steven J. Davis; Sha Feng; Bo Zheng; Duo Cui; Xinyu Dou; Biqing Zhu; Rui Guo; Piyu Ke; Taochun Sun; Chenxi Lu; Pan He; Yuan Wang; Xu Yue; Yilong Wang; Yadong Lei; Hao Zhou; Zhaonan Cai; Yuhui Wu; Runtao Guo; Tingxuan Han; Jinjun Xue; Olivier Boucher; Eulalie Boucher; Frédéric Chevallier; Katsumasa Tanaka; Yiming Wei; Haiwang Zhong; Chongqing Kang; Ning Zhang; Bin Chen; Fengming Xi; Miaomiao Liu; François-Marie Bréon; Yonglong Lu; Qiang Zhang; Dabo Guan; Peng Gong; Daniel M. Kammen; Kebin He; Hans Joachim Schellnhuber. Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic. Nature Communications 2020, 11, 1 -1.

AMA Style

Zhu Liu, Philippe Ciais, Zhu Deng, Ruixue Lei, Steven J. Davis, Sha Feng, Bo Zheng, Duo Cui, Xinyu Dou, Biqing Zhu, Rui Guo, Piyu Ke, Taochun Sun, Chenxi Lu, Pan He, Yuan Wang, Xu Yue, Yilong Wang, Yadong Lei, Hao Zhou, Zhaonan Cai, Yuhui Wu, Runtao Guo, Tingxuan Han, Jinjun Xue, Olivier Boucher, Eulalie Boucher, Frédéric Chevallier, Katsumasa Tanaka, Yiming Wei, Haiwang Zhong, Chongqing Kang, Ning Zhang, Bin Chen, Fengming Xi, Miaomiao Liu, François-Marie Bréon, Yonglong Lu, Qiang Zhang, Dabo Guan, Peng Gong, Daniel M. Kammen, Kebin He, Hans Joachim Schellnhuber. Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic. Nature Communications. 2020; 11 (1):1-1.

Chicago/Turabian Style

Zhu Liu; Philippe Ciais; Zhu Deng; Ruixue Lei; Steven J. Davis; Sha Feng; Bo Zheng; Duo Cui; Xinyu Dou; Biqing Zhu; Rui Guo; Piyu Ke; Taochun Sun; Chenxi Lu; Pan He; Yuan Wang; Xu Yue; Yilong Wang; Yadong Lei; Hao Zhou; Zhaonan Cai; Yuhui Wu; Runtao Guo; Tingxuan Han; Jinjun Xue; Olivier Boucher; Eulalie Boucher; Frédéric Chevallier; Katsumasa Tanaka; Yiming Wei; Haiwang Zhong; Chongqing Kang; Ning Zhang; Bin Chen; Fengming Xi; Miaomiao Liu; François-Marie Bréon; Yonglong Lu; Qiang Zhang; Dabo Guan; Peng Gong; Daniel M. Kammen; Kebin He; Hans Joachim Schellnhuber. 2020. "Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic." Nature Communications 11, no. 1: 1-1.

Journal article
Published: 30 November 2020 in Remote Sensing
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Abundant data sets produced from long-term series of high-resolution remote sensing data have made it possible to explore urban issues across different spatiotemporal scales. Based on a 40-year impervious area data set released by Tsinghua University, a method was developed to map the speed and acceleration of urban built-up areas. With the mapping results of the two indices, we characterised the spatiotemporal dynamics of built-up area expansion and captured different types of expansion. Combined with socioeconomic data, we examined the temporal changes and spatial heterogeneity of driving forces with an ordinary least square (OLS) model and a panel data model, as well as exploring the environmental effects of the expansion. Our results reveal that China has experienced drastic urban expansion over the last four decades. Among all cities, megacities and large cities in eastern China, as well as megacities in central and northeast China have experienced the most dramatic urban expansion. A growing number of cities are categorised as thriving, which means that they have both high expansion speed and acceleration. The overall driving force of urban expansion has significantly increased. More specifically, it was associated with population increase in the early stages; however, since 2000, it has been substantially associated with increases in GDP and fixed asset investments. The major driving factors also differ between regions and urban sizes. Urban expansion is identified as being closely associated with environmental deterioration; thus, speed and acceleration should be included as key indicators in exploring the environmental effects of urban expansion. In summary, the results of the presented case study, based on a data set of China, indicate that speed and acceleration are useful in analysing the driving forces of urban expansion and its environmental effects, and may generate more interest in related research.

ACS Style

Lan Wang; Yinghui Jia; Xinhu Li; Peng Gong. Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017. Remote Sensing 2020, 12, 3929 .

AMA Style

Lan Wang, Yinghui Jia, Xinhu Li, Peng Gong. Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017. Remote Sensing. 2020; 12 (23):3929.

Chicago/Turabian Style

Lan Wang; Yinghui Jia; Xinhu Li; Peng Gong. 2020. "Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017." Remote Sensing 12, no. 23: 3929.

Journal article
Published: 08 November 2020 in Remote Sensing
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Madagascar, one of Earth’s biodiversity hotpots, is characterized by heterogeneous landscapes and huge land cover change. To date, fine, reliable and timely land cover information is scarce in Madagascar. However, mapping high-resolution land cover map in the tropics has been challenging due to limitations associated with heterogeneous landscapes, the volume of satellite data used, and the design of methodology. In this study, we proposed an automatic approach in which the tile-based model was used on each tile (defining an extent of 1° × 1° as a tile) for mapping land cover in Madagascar. We combined spectral-temporal, textural and topographical features derived from all available Sentinel-2 observations (i.e., 11,083 images) on Google Earth Engine (GEE). We generated a 10-m land cover map for Madagascar, with an overall accuracy of 89.2% based on independent validation samples obtained from a field survey and visual interpretation of very high-resolution (0.5–5 m) images. Compared with the conventional approach (i.e., the overall model used in the entire study area), our method enables reduce the misclassifications between several land cover types, including impervious land, grassland and wetland. The proposed approach demonstrates a great potential for mapping land cover in other tropical or subtropical regions.

ACS Style

Meinan Zhang; Huabing Huang; Zhichao Li; Kwame Hackman; Chong Liu; Roger Andriamiarisoa; Tahiry Ny Aina Nomenjanahary Raherivelo; Yanxia Li; Peng Gong. Automatic High-Resolution Land Cover Production in Madagascar Using Sentinel-2 Time Series, Tile-Based Image Classification and Google Earth Engine. Remote Sensing 2020, 12, 3663 .

AMA Style

Meinan Zhang, Huabing Huang, Zhichao Li, Kwame Hackman, Chong Liu, Roger Andriamiarisoa, Tahiry Ny Aina Nomenjanahary Raherivelo, Yanxia Li, Peng Gong. Automatic High-Resolution Land Cover Production in Madagascar Using Sentinel-2 Time Series, Tile-Based Image Classification and Google Earth Engine. Remote Sensing. 2020; 12 (21):3663.

Chicago/Turabian Style

Meinan Zhang; Huabing Huang; Zhichao Li; Kwame Hackman; Chong Liu; Roger Andriamiarisoa; Tahiry Ny Aina Nomenjanahary Raherivelo; Yanxia Li; Peng Gong. 2020. "Automatic High-Resolution Land Cover Production in Madagascar Using Sentinel-2 Time Series, Tile-Based Image Classification and Google Earth Engine." Remote Sensing 12, no. 21: 3663.

Preprint content
Published: 22 October 2020
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Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. Supplementary material to "Oil palm modelling in the global land-surface model ORCHIDEE-MICT". 2020, 1 .

AMA Style

Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, Peng Gong. Supplementary material to "Oil palm modelling in the global land-surface model ORCHIDEE-MICT". . 2020; ():1.

Chicago/Turabian Style

Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. 2020. "Supplementary material to "Oil palm modelling in the global land-surface model ORCHIDEE-MICT"." , no. : 1.

Preprint content
Published: 22 October 2020
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Oil palm is the most productive oil crop that provides ~40 % of the global vegetable oil supply, with 7 % of the cultivated land devoted to oil plants. The rapid expansion of oil palm cultivation is seen as one of the major cause for deforestation emissions and threatens the conservation of rain forest and swamp areas and their associated ecosystem services in tropical areas. Given the importance of oil palm in oil production and its adverse environmental consequences, it is important to understand the physiological and phenological processes of oil palm and its impacts on the carbon, water and energy cycles. In most global vegetation models, oil palm is represented by generic plant functional types (PFT) without specific representation of its morphological, physical and physiological traits. This would cause biases in the subsequent simulations. In this study, we introduced a new specific PFT for oil palm in the global land surface model ORCHIDEE-MICT (v8.4.2). The specific morphology, phenology and harvest process of oil palm were implemented, and the plant carbon allocation scheme was modified to support the growth of branch, leaf and fruit component of each phytomer. A new age-specific parameterization scheme for photosynthesis, autotrophic respiration, and carbon allocation was also developed for the oil palm PFT, based on observed physiology, and was calibrated by observations. The improved model generally reproduces the leaf area index, biomass density and fruit yield during the life cycle at 14 observation sites. Photosynthesis, carbon allocation and biomass components for oil palm also agree well with observations. This explicit representation of oil palm in global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.

ACS Style

Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. Oil palm modelling in the global land-surface model ORCHIDEE-MICT. 2020, 2020, 1 -32.

AMA Style

Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, Peng Gong. Oil palm modelling in the global land-surface model ORCHIDEE-MICT. . 2020; 2020 ():1-32.

Chicago/Turabian Style

Yidi Xu; Philippe Ciais; Le Yu; Wei Li; Xiuzhi Chen; Haicheng Zhang; Chao Yue; Kasturi Kanniah; Arthur P. Cracknell; Peng Gong. 2020. "Oil palm modelling in the global land-surface model ORCHIDEE-MICT." 2020, no. : 1-32.

Preprint content
Published: 20 October 2020
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Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. Supplementary material to "A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine". 2020, 1 .

AMA Style

Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, Peng Gong. Supplementary material to "A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine". . 2020; ():1.

Chicago/Turabian Style

Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. 2020. "Supplementary material to "A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine"." , no. : 1.

Preprint content
Published: 20 October 2020
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The construction of terraces is a key soil conservation practice on agricultural land in China, providing multiple valuable ecosystem services. Accurate spatial information on terraces is needed for both management and research. In this study, the first 30 m resolution terracing map of the entire territory of China is produced by a supervised pixel-based classification using multi-source and multi-temporal data based on the Google Earth Engine (GEE) platform. We extracted time-series spectral features and topographic features from Landsat 8 images and the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) data, classifying cropland area (cultivated land of Globeland30) into terraced and non-terraced type through a random forest classifier. The overall accuracy and kappa coefficient were evaluated by 10875 test samples and achieved values of 94 % and 0.72, respectively. The classification performed best in the Loess Plateau and southwestern China, where terraces are most numerous. Some northeastern, central eastern and southern area had relatively high uncertainty. Typical errors in the mapping results from the sloping cropland (non-terrace cropland with a slope of ≥ 5°), low-slope terraces, and non-crop vegetation. Terraces are widely distributed in China and the total terraced area was estimated to be 53.55 Mha (i.e., 26.43 % of China's cropland area) by pixel counting (PC) method and 58.46 ± 2.99 Mha (i.e., 28.85 % ± 1.48 % of China's cropland area) by error matrix-based model-assisted estimation (EM) method. Elevation and slope were identified as the main features in the terrace/non-terrace classification, and multi-temporal spectral features (such as percentiles of NDVI, TIRS2, BSI) were also essential. Terraces are more challenging to identify than other land use types because of the intra-class feature heterogeneity, inter-class feature similarity and fragmented patches, which should be the focus of future research. Our terrace mapping algorithm can be used to map large-scale terraces in other regions globally, and our terrace map will serve as a landmark for studies on multiple ecosystem services assessments including erosion control, carbon sequestration, and biodiversity conservation. The China terrace map is available to the public at https://doi.org/10.5281/zenodo.3895585 (Cao et al., 2020).

ACS Style

Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine. 2020, 2020, 1 -35.

AMA Style

Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, Peng Gong. A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine. . 2020; 2020 ():1-35.

Chicago/Turabian Style

Bowen Cao; Le Yu; Victoria Naipal; Philippe Ciais; Wei Li; Yuanyuan Zhao; Wei Wei; Die Chen; Zhuang Liu; Peng Gong. 2020. "A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine." 2020, no. : 1-35.

Journal article
Published: 14 October 2020 in Nature Communications
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The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

ACS Style

Zhu Liu; Philippe Ciais; Zhu Deng; Ruixue Lei; Steven J. Davis; Sha Feng; Bo Zheng; Duo Cui; Xinyu Dou; Biqing Zhu; Rui Guo; Piyu Ke; Taochun Sun; Chenxi Lu; Pan He; Yuan Wang; Xu Yue; Yilong Wang; Yadong Lei; Hao Zhou; Zhaonan Cai; Yuhui Wu; Runtao Guo; Tingxuan Han; Jinjun Xue; Olivier Boucher; Eulalie Boucher; Frédéric Chevallier; Katsumasa Tanaka; Yiming Wei; Haiwang Zhong; Chongqing Kang; Ning Zhang; Bin Chen; Fengming Xi; Miaomiao Liu; François-Marie Bréon; Yonglong Lu; Qiang Zhang; Dabo Guan; Peng Gong; Daniel M. Kammen; Kebin He; Hans Joachim Schellnhuber. Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic. Nature Communications 2020, 11, 1 -12.

AMA Style

Zhu Liu, Philippe Ciais, Zhu Deng, Ruixue Lei, Steven J. Davis, Sha Feng, Bo Zheng, Duo Cui, Xinyu Dou, Biqing Zhu, Rui Guo, Piyu Ke, Taochun Sun, Chenxi Lu, Pan He, Yuan Wang, Xu Yue, Yilong Wang, Yadong Lei, Hao Zhou, Zhaonan Cai, Yuhui Wu, Runtao Guo, Tingxuan Han, Jinjun Xue, Olivier Boucher, Eulalie Boucher, Frédéric Chevallier, Katsumasa Tanaka, Yiming Wei, Haiwang Zhong, Chongqing Kang, Ning Zhang, Bin Chen, Fengming Xi, Miaomiao Liu, François-Marie Bréon, Yonglong Lu, Qiang Zhang, Dabo Guan, Peng Gong, Daniel M. Kammen, Kebin He, Hans Joachim Schellnhuber. Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic. Nature Communications. 2020; 11 (1):1-12.

Chicago/Turabian Style

Zhu Liu; Philippe Ciais; Zhu Deng; Ruixue Lei; Steven J. Davis; Sha Feng; Bo Zheng; Duo Cui; Xinyu Dou; Biqing Zhu; Rui Guo; Piyu Ke; Taochun Sun; Chenxi Lu; Pan He; Yuan Wang; Xu Yue; Yilong Wang; Yadong Lei; Hao Zhou; Zhaonan Cai; Yuhui Wu; Runtao Guo; Tingxuan Han; Jinjun Xue; Olivier Boucher; Eulalie Boucher; Frédéric Chevallier; Katsumasa Tanaka; Yiming Wei; Haiwang Zhong; Chongqing Kang; Ning Zhang; Bin Chen; Fengming Xi; Miaomiao Liu; François-Marie Bréon; Yonglong Lu; Qiang Zhang; Dabo Guan; Peng Gong; Daniel M. Kammen; Kebin He; Hans Joachim Schellnhuber. 2020. "Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic." Nature Communications 11, no. 1: 1-12.