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The Digital Agricultural Knowledge and information System(DAKIS):Employing digitalisation to encourage diversified and multifunctional agricultural systems

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Environmental Science and Ecotechnology 2023年第4期16卷 177-189页

作者： Ioanna Mouratiadou Nahleen Lemke Cheng Chen Ariani Wartenberg Ralf Bloch Marco Donat Thomas Gaiser Deepak Hanike Basavegowda Katharina Helming Seyed Ali Hosseini Yekani Marcos Krull Kai Lingemann Joseph Macpherson Marvin Melzer Claas Nendel Annette Piorr Mostafa Shaaban Peter Zander Cornelia Weltzien Sonoko Dorothea Bellingrath-Kimura Leibniz Centre for Agricultural Landscape Research(ZALF) Eberswalder Straße 8415374MünchebergGermany ISARA Laboratory of Rural Studies Research UnitLyon23 Rue Jean Baldassini69364Lyon Cedex 07France Faculty of Landscape Management and Nature Conservation University for Sustainable Development(HNEE)Schickler Straße 516225EberswaldeGermany Institute of Crop Science and Resource Conservation University of Bonn53115BonnGermany Leibniz Institute for Agricultural Engineering and Bioeconomy(ATB) Max-Eyth-Allee 10014469PotsdamGermany German Research center for Artificial Intelligence(DFKI) Trippstadter Strasse 12267663KaiserslauternGermany Institute of Biochemistry and Biology University of PotsdamAm Mühlenberg 314476Potsdam(Golm)Germany Global Change Research Institute The Czech Academy of ScienceBělidla 986/4a60300BrnoCzech Republic

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem *** use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural *** present the Digital Agricultural Knowledge and information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable *** develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of *** results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability *** overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various *** approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and ***,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.

关键词： Digital agriculture Ecosystem services Decision support system Farming practices Biodiversity Modelling Small-scale management

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基于MERIT DEM和DRT升尺度化算法的多分辨率全国河网数据集构建

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地理与地理信息科学 2020年第3期36卷 1-9页

作者：黄泽群李超群吴欢姜璐璐男顶汤秋鸿王爱慧赵世湖 Dai YAMAZAKI 中山大学大气科学学院广东珠海519082 广东省气候变化与自然灾害研究重点实验室广东广州510275 南方海洋科学与工程广东省实验室(珠海) 广东珠海510301 Earth System Science Interdisciplinary center University of MarylandCollege ParkMaryland MD 20742USA 北京大学地球与空间科学学院北京100871 中国科学院地理科学与资源研究所北京100101 中国科学院大气物理研究所北京100029 自然资源部国土卫星遥感应用中心北京101300 Institute of Industrial Science University of TokyoTokyo 113-8654Japan

相对较粗空间分辨率(>1 km)的水文网络或水文地理数据集是大尺度水文及陆面过程模型的基本输入数据,需要从数字高程模型中提取高分辨率河网并通过升尺度化获取。MERIT DEM是消除了复合误差的新版全球高分辨率(90 m)数字高程模型,提取的... 详细信息

相对较粗空间分辨率(>1 km)的水文网络或水文地理数据集是大尺度水文及陆面过程模型的基本输入数据,需要从数字高程模型中提取高分辨率河网并通过升尺度化获取。MERIT DEM是消除了复合误差的新版全球高分辨率(90 m)数字高程模型,提取的高分辨率河网信息更为精准。DRT是当前国际水文领域常用的高效河网自动升尺度化算法之一,可将高分辨率河网的结构特性完好地输出到粗分辨率河网。该文选取MERIT DEM的中国部分作为数据源,通过DRT升尺度化算法获取全国1°、1/2°、1/4°、1/8°、1/10°、1/16°分辨率的河网数据(流向、河网、流域面积、流距),并采用目视检验、流域面积一致性检验、流距评估等方法综合验证了DRT升尺度数据集的质量。结果表明,DRT算法性能优越,生产的大尺度数据集准确地保护了河道位置、流动方向和流域面积等在高分辨率DEM中描绘的水文特征,将有效降低我国境内流域水文模拟中由水文地形参数化引起的不确定性。

关键词：数字高程模型河流网络升尺度化流距流向水文模型

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Global carbon sequestration potential of agroforestry and increased tree cover on agricultural land

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Circular Agricultural Systems 2022年第1期2卷 38-47页

作者： Robert J.Zomer Deborah A.Bossio Antonio Trabucco Meine van Noordwijk Jianchu Xu center for Mountain Futures Kunming Institute of BotanyChinese Academy of Science(CAS)Kunming 650201China Centre for International Forestry Research and World Agroforestry(CIFOR-ICRAF) Kunming 650201China Global Evergreening Alliance Surat Thani 84280Thailand The Nature Conservatory(TNC) OaklandCalifornia 94609USA Centro Euro-Mediterraneo sui Cambiamenti Climatici(CMCC) Sardinia 73100Italy Centre for International Forestry Research and World Agroforestry(CIFOR-ICRAF) Bogor 16115Indonesia

Biomass is fundamental to circular agricultural *** of above-and below-ground biomass on agricultural land based upon IPCC Tier 1 estimates are compared with an updated carbon density map based on remote sensing,with results indicating the methodology and initial estimations are *** scenarios are evaluated to estimate carbon sequestration potential of increasing tree cover on agricultural land:1)incremental change and 2)a systemic change to *** of above-and below ground biomass carbon were combined with a tree cover analysis to estimate the increase in *** increases(4−6 PgC for incremental change;12−19 PgC for systemic change)highlight substantial mitigation *** global tree cover on agricultural land by 10%would sequester more than 18 *** America has the highest potential,followed by Southeast Asia,West and Central Africa,and North ***,Indonesia,Philippines,India,the United States and China are among the top countries with the highest carbon sequestration potential on agricultural land with increased tree cover.

关键词： carbon potential agricultural

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中国植被图(1:1000000)现实性更新（英文）

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Science Bulletin 2020年第13期65卷 1125-1136页

作者：苏艳军郭庆华胡天宇关宏灿金时超安沙舟陈学林郭柯郝占庆胡远满黄永梅江明喜李家湘李振基李先琨李小伟梁存柱刘仁林刘庆倪宏伟彭少麟沈泽昊唐志尧田兴军王希华王仁卿谢宗强谢应忠徐小牛杨小波杨永川喻理飞岳明张峰马克平 State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences University of Chinese Academy of Sciences College of Pratacultural and Environmental Sciences Xinjiang Agricultural University College of Life Science Northwest Normal University Key Laboratory of Forest Ecology and Management Institute of Applied Ecology Chinese Academy of Sciences College of Resources Science and Technology Beijing Normal University Key Laboratory of Aquatic Botany and Watershed Ecology Wuhan Botanical Garden Chinese Academy of Sciences College of Forestry Central South University of Forestry & Technology College of Life Sciences Xiamen University Guangxi Institute of Botany Chinese Academy of Sciences Agricultural College Ningxia University School of Ecology and Environment Inner Mongolia University Institute of Navel Orange School of Life and Environmental Science Gannan Normal University Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization Chengdu Institute of Biology Chinese Academy of Sciences Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of Biology Chinese Academy of Sciences Institute of Natural Resources and Ecology Heilongjiang Academy of Sciences State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources School of Life Sciences Sun Yat-sen University Institute of Ecology College of Urban and Environmental Science and Key Laboratory of Earth Surface Processes Peking University School of Life Sciences Nanjing University Zhejiang Tiantong Forest Ecosystem National Observation and Research Station School of Ecological and Environmental Sciences East China Normal University School of Life Sciences Shandong University Department of Forest Science Anhui Agricultural University Institute of Tropical agriculture and Forestry College of Material and Chemical Engineering Hainan University Key Laboratory of Three Gorges Reservoir Region’s Eco-Environment

植被图是生物多样性保护、生态学研究、植被管理与恢复和国家决策的重要辅助信息源.我国上一代植被图,即中国植被图(1:1000000),是由逾250位生态学家组成的团队自20世纪80年代花了20多年完成的.但是,随着过去30多年间的快速发展,我国的... 详细信息

植被图是生物多样性保护、生态学研究、植被管理与恢复和国家决策的重要辅助信息源.我国上一代植被图,即中国植被图(1:1000000),是由逾250位生态学家组成的团队自20世纪80年代花了20多年完成的.但是,随着过去30多年间的快速发展,我国的植被分布与植被类型发生了剧烈的变化,对上一代植被图进行现实性更新已成为迫在眉睫的需求.本文使用了一种"众源采集—变化检测—遥感分类—专家审核"的策略尝试对中国植被图(1:1000000)进行现实性更新.本研究共收集了203024条地面调查数据,并有50余位植被生态学家参与到专家审核的工作中.更新后的植被图包含12个植被型组、55个植被(亚)型和866个(亚)群系类别,精度在植被型组、植被(亚)型和(亚)群系水平上分别为64.8%, 61%和40%.与上一代植被图相比,过去30多年间的人类活动和气候变化导致了我国约330万km2植被类型发生了变化.更新后的植被图将会有助于理解和管理我国的陆地生态系统.

关键词： Vegetation map Crowdsource remote sensing Update

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