INTERNATIONAL RESEARCH CENTER OF BIG DATA FOR SUSTAINABLE DEVELOPMENT GOALS Digital Earth in Facilitating of Sustainable Development Goals Huadong Guo hdguo(5) radi.ac.cn 18 November 2022 United Nation's Stratigic Framework The humankind are facing the global challenges SUSTAIN ABLE /"^"'a A I C DEVELOPMENT WwMLO PARIS2015 UN CLIMATE CHANGE CONFERENCE COP21-CMP11 SENDAI FRAMEWORK FOR DISASTER RISK REDUCTION 2015-2030 Sustainable Development UN SDGs 5* Measuring Status & Progress Climate Action Paris Agreement Monitoring & Understanding Disaster Risk Reduction Sendai Framework The 2030 Agenda for Sustainable Development In 2015, 193 countries around the world adopted the 2030 Agenda for Sustainable Development, which includes 17 Sustainable Development Goals (SDGs) and 169 sub-goals. FIN DE LA POBREZA Mf*' 7ENERGIA ASEQDIBLE ■ Q TRABAIQ DECENT Y NO CDNTAMINAN1E I 0 ¥ CRECIMIENTD ACCIDN ■ iyi VIDA PGR EL CLIMA ■ l*t SUBM/ SALUD T BIENESTAR V* Hi VIDA DE ECOSISTEMAS TERRESTRES 4 Z ► REDUCCION DE LAS ■ "11 CIUDADES V DESIGUALDADES ■ I I COMUNIDADES » ■ SOSTENIBLES PAZ, JUSTICIA ■17 ALIANZAS PARA EINSTITUCIONES I If LOGRAR SOLIDAS ■ I OS OBIETIVOS AGUA LIM PI A VSANEAMIENTD 2PRQDUCCI0N YCDNSUMO RESPONSABLES oo 17 Goals for a Changing World UN Sustainable Development Summit 2015 Outline ami) Technology Facilitation Mechanism A Digital Earth Platform: CAS Earth §>j CASEarth for SDGs Evaluation Jul) In't Center of Big Data for SDGs SDG Challenges The Global Indicator Framework for Sustainable Development is a concrete implementation guideline of the UN 2030 Agenda and is used to assess the progress of global SDGs. It faces many challenges, such as lack of data, insufficient research on indicator systems, and uneven development in regional areas. 40% indicators lack of data support /Method Data Year 2017 Year 2018 Year 2020 17 Goals 169 Specific Goals 240+ Indicators © © © © © O 36% 40% 59% 26% 31% 39% 38% 29% 2% Non-suitable spatial coverage and timeless Proportion of countries or areas with available data, by Goal (percentage) loo n Gl G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 G13 G14 G15 G16 G17 i The United Nations SDG Report (2021) I states that national coverage data are not available for more than half of the countries in at least five SDGs Only 4 global maps in the UN SDG Report 2020 UN Technology Facilitation Mechanism (TFM) TECHNOLOGY FACILITATION MECHANISM SUSTAINABLE DEVELOPMENT GOALS UNITED NATIONS INTERAGENCY TASK TEAM ON STI FOR THE SDGS (IATT) 10-MEMBER GROUP TO SUPPORT THE TECHNOLOGY FACILITATION MECHANISM MULTI-STAKEHOLDER FORUM ON SCIENCE, TECHNOLOGY AND INNOVATION FOR THE SDGS (STI FORUM) ONLINE PLATFORM (2030 Connect) - GATEWAY FOR INFORMATION ON EXISTING STI INITIATIVES, MECHANISMS AND PROGRAMS 10-MEMBER GROUP TO SUPPORT THE TECHNOLOGY FACILITATION MECHANISM ■ 10-MemberGroup2016-2017 2018-2019 iL Dr. Paulo Gadelha (Brazil), Coordinator of the FIOCRUZ Strategy for the 2030 Agenda, Oswaldo Cruz Foundation (FIOCRUZ) Prof. Huadong Guo (China), Chairman of Academic Committee, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (CAS) Dr. Heide Hackmann (South Africa), Executive Director, International Council for Science (ICSU) Dr. Agnes Lawrence Kijazi (United Republic of Tanzania), Director General, Tanzania Meteorological Agency (TMA) Dr.Jos£ Ramön Löpez-Portilio Romano (Mexico), Chairman, Q Element Ltd. Dr. Michiharu Nakamura (Japan), Senior Advisor (Former President), Japan Science and Technology Agency Dr. Anne-Christine Ritschkoff (Finland), Senior Advisor VTT Technical Research Centre of Finland Ltd. Dr. §peia Stres (Slovenia), Head of Innovation and Technology Transfer Center forjozef Stefan Institute Dr. Vaughan Turekian (USA), Senior Director at the National Academies of Sciences, Engineering, and Medicine Dr. Ada Yonath (Israel), Director and Nobel Laureate, the Helen and Milton A. Kimmelman Center for Biomolecular Structure and Assembly of the Weizmann Institute of Science. September, 2022 1999-2022 Digital Earth Roadmap International Society toi Digital Earth Digital Earth ______Global Eai- :ion System of Systems (GEOSS) in the Plenary Session. June, 2001 The 2nd International Symposium on Digital Earth September, 2012 2012 Digital Earth Summit • Place: Wellington, New March, 2012 ISDE participated in GEO Post-2015 Working Group Meeting a the Headquarters of the world Meteorological Organization (WMO) in Geneva. January, 2014 Digital Earth Research Ir on disciplinary development was approved by the Acadei Divisions of the Chinese Acs of Sciences. The workshop for thi initiative, aiming at Digital Earth researches, was held in China. November, 2014 2014 Digital Earth Summit • Theme: Digital Earth for ESD July, 2014 IJDE obtained IF 2.212 for year <- June, 2015 IJDE Impact Factor Breaks 3X The impact factor of IJDE has reached 3.291, ranking 4th a t- '2 H I, e sensing and 7th in the •riiationjI geographical Is, which indicates thai the d the Ql zone UDE Received Impact Factor 3.98S August, 2019 ISDE became a member of UN-GGIM Geospatial Societies September, 2019 The 11th International Symposium on Digiial Earth - Place; Florence. Italy • Theme: Digital Earth in a Transformed Society I&LJE11™ November, 2019 The first China Digital Earth Conference (CDEC) held in Beijing Manual of Digital Earth was launched • rher : Beyond Infor April, 2012 ISDE organized Digital Eart Special Session in the High Lc-vel Academic Forum of Academy of Sciences. the Proceedings of the National Academy of Sciences of the United States of America (PNAS). Manual of Digital Earth Outline jSk) Technology Facilitation Mechanism A Digital Earth Platform: CAS Earth §>j CASEarth for SDGs Evaluation m) In't Center of Big Data for SDGs CASEarth: A Digital Earth Platform • Build a modern, technological and international comprehensive display and integration system of Digital Earth; • An integrated visualization environment with immersive, experiential, 16K ultra-high-resolution, automatic natural interaction and intelligent analysis capabilities; • Provide a comprehensive visual analysis system platform for SDG research work, and support national sustainable development. Digital Earth Infrastructure Data as a service Infrastructure as a Service Analysis as a Service Application as a Service CASEarth DataBank The platform provides: Time-series EO products Chinese satellite data: ZY, GF, HJ, CBERS, FY, HY USGS Landsat data since 1986, with 12 products Resolution: from kilometer to sub-meter Other data sources: DEM, vector Infrastructure and services Data engine: Databox for time-series data, global tiling Computation engine: algorithms, distributed parallel computing, intelligent services Data visualization PHIä: LSR TI & fisg mm mm nm & m: ' $m- Kj 11«: i \ yyyy-mm-dd - yyyy-mm-dd L5-TM-120-038-19840507-LSR Bft: 120, 38 ■MnS: 118.8903, 31.7303 Bffl: 19840507 L5-TM-117-039-19840822-LSR fi?R: 117, 39 ■Kwg: 122.9003 , 30.3282 19840822 m-, m L5-TM-118-038-19840914-LSR ÍŤ^J§: 118, 38 ■KwS: 121.778, 31.7659 BW: 19840914 m-, m I SÍR: L5-TM-120-039-19841030-LSR !SS1S20«, tt692SE», Bail 0 § i IIhuiíi ^j[iiJi^M|B|M|M Earth Data Miner 'J Earth Data Miner prefect private sdgfiriimng srig661long en app ► r- r *og£6iiang mam py Q «dgft6ltang di app A «3v«"w»gLenapp II imapp \ imooi ; rwjvt _p»uOutt_zf\app i«poi-t OS import ogr import ui import M*p !«!'"»•• ntmv f .. import uuid from morn impor import Export from »dm., lib from ui.runt in import ui.evwn 1 9d0G61lunQ_ctLupp EarthDataMiner: A cloud-based online interactive data analysis environment Iaage, Reducer, Geo«etry «por-t ...»l«u.il. Oil IliiCsvtlrl, DBoatol i fUrl , SOC.Pj iapiirt cllmt, Stor-e ui .evwrt . *end( ' '.y^ . 1 anß ' , 'en-US') mji_x ■ S »iie_ratio a 17.393S/!OOeeee ui .djlu.vtiirr. -ft (*Ro%ul 11) i • I " , {}) /pnvate/sdg661k> /pnvate/sdyhoiio /pnvakWsdg1531/ /pnvatB/sdg1S31/ /pnvafcVsdglMI/ .. /pnvatessdg1531/ /pnvate/sdgt531/ .'pnvala/sdgfio1 k> pi •■>'■-• sdgbt■ l o /privat n nt n JVC . . ^ - Satellite Image Data 7.6PB Biological and ecological data 5.8PB EO Data Satellite image products geographic data groun data Atmospheric and 490,000 3.6 million Items GBDB data record 1.6 million 420,000 Items Catalogue of items Microbial Data Life China record 1 billion pieces Omics data © Each year, about 3PB will be updated on the Platform ® Released on 15,Jan,2019. As of November 2022, more than 570,000 IP users in 174 countries have accessed the system, with total online traffic exceeding 98.79million SDGSAT-1: The World's first Science Satellite for SDGs Provide datasets for SDCs that repre activities and natural environment • Thermal infrared + nighttime-light + multi-spectral • Wide scale (300 km) ^ . • High-resolution (10 m) Explore new methods to sense Earth9s environment Outline jSk) Technology Facilitation Mechanism A Digital Earth Platform: CAS Earth §>) CASEarth for SDGs Evaluation m) In't Center of Big Data for SDGs SDG 2 Zero Hunger Spatial pattern of cropping intensity and gaps at global scale In 2020, about 85.2% of global cropland is single cropping, and double cropping pattern mainly concentrated in the Indus Ganges Plain, Huang-Huai-Hai Plain, Parana River Basin, Mato Grosso and Nile River Delta. It is expected to increase 0.23 billion tonnes of grain production by closing the cropping intensity gaps, equivalent to 6.4% of the current global production. 16 day interval 30m resolution NDVI sources • Quality band Smoother 7^ (b 1 ••v \ \ * \ J < ( 1 «•"> } \ JßJ V % r *\ W! ...J Jan-16 Jul-lfi Feb-17 Aug-17 Mar-lS Sep-18 -50% NDVI amplitude Smoothed NDVI -----Phase Flow chart of methodologies Single cropping Double cropping Triple cropping or above Global cropping intensity CLEAN WATER AND SANITATION SDG 6 Clean Water and Sanitation z Temporal and spatial variations in water clarity in global large lakes during 2000-2021 1/3 of the large lakes are with water clarity lower than 0.5 m in 2021. Temporally, lakes in high latitude generally have higher water clarity, while lakes in lower latitude have lower water clarity. From 2000 to 2021, the water clarity in global large lakes has an overall increasing trend. 44.2% significant increase while only 10.6% significant decrease. Large lakes with significant increasing trend are mainly concentrated in the Cold Temperature and Polar zones in the globe. Average lake clarity map for global large lakes in the year of 2021-> Lake clarity (m) • <0.5 o 0.5-1.0 e 1.0-2.0 • 2.0^5.0 • >5.0 Climate zone Tropical Zone Arid Zone Tcmpcraturc Zone- — ■ Cold Zone Polar Zone 42 4 f z s. e Annual chancing rate (cm/vr) V -5-o - : *v%'- • * A 0-2 W - • ' : 5 ▲ >5 Climate zone Tropical Zone Arid Zone Temperature Zone,—.... < Cold Zone Polai Zone 0 2.000 4,000 8,000 km Annual changing rate of water clarity for global large lakes during «-2000-2021 AFFORDABLE AND GLEAN ENERGY SDG 7 Affordable and Clean Energy Global identification of unelectrified built-up areas by big data 2014-2020, the global electrified building area was increased significantly by 2.91 xlO4 km2 The global un-electrified buildings are mainly distributed in Africa and Asia, especially in sub Saharan Africa. More than half of the countries (regions) where un-electrified built-up areas increased are in fragile and conflict environments. 0 4,800 km . » Changes in the percentage of electrified built-up areas(%} ■ 633.51 ~H1.OOCDH1.00~HO.10 CDH0.10~0.10 CDO.10~10.00 ™»10.00 CDNodata Figure 4-2. ■ * A Percentage of unelectrified built-up areas(%) ■K1.00 □1.00-3.00 1=13.00 -10.00 r~B>lC00 CZSNodata Proportion of global un-electrified building area in 2020 In 2020, Global electrified built-up areas increased l , 29.108.62 knr, from 96.95% to 98.68%. 415 power stations ® Change in percentage of global electrified built-up areas in 2020 compared to 2014 9999999 9999999 9999999 9999999 999 117 countries (regions) Increased share of electrified built-up area SDG 11 Sustainable Cities and Communities Changes of urban greenness and beneficiary population in global large cities China has the largest greening urban area in the world China accounted for 28% of greening built-up areas (BUAs) with only 19% of the total BUA throughout the world China accounts for nearly half ( 47% ) of the world' s beneficiary population in greening built-up area The improvement of urban ecology is closely related to income level, and urban greening has increased significantly in upper-middle-income ( UM ) countries in XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX X XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx Beneficiary population (BP) in China:147 M xxxxxxxxx xxxxxxxxx BP in PRD:17.92 M xxxxxxxxx xxxxxxx BP in YRD:16.38 M xxxxxxxxx X BP in Beijing:9.74 M Rl R2 R3 R4 <10K 10- 100K 100K-1M F 70 ^ | 40 c TO .2 a. -g J 30 Q-'zj a- s« 20 It) AS Average population from 0 3 population datasets • WorldPop 2020 ■ GWPV4 2020 ► LandScan2020 EU NA SA AF AO |b) 25 UM LM 0.50 0.00 (a) Percentage of population living in significant greening built-up area (BUA) across continents, (b) Percentage of significant greening BUA and urban average value of annual maximum greenness under different income levels. SDG 13 Climate Action Global terrestrial and ocean carbon sink estimated from big data Net annual ecosystem productivity (gC m 2* a-1) < 100 Wn -20 - 0 □50-120 □-100 --50 ^0-20 I I 120 - 200 I -50- -20 I 120 - 50 I 1200 - 350 1350 -400 1400 -450 I ^450 ^ Global terrestrial average NEP during 2000-2020 Global ocean carbon sink accelerated since 2008, and the increasing rate reaches 0.075 Pg C/a during 2008-2020. Terrestrial net ecosystem productivity (NEP) and carbon dioxide partial pressure (PC02) of surface seawater are important parameters for quantitative estimation of carbon sink intensity of terrestrial and marine ecosystems, respectively. Global terrestrial NEP showed a significantly increased trend from 2000 to 2020 (0.05 Pg C/a, p<0.05). Average -> distribution of global ocean C02 flux during 1992-2020 MLIFE BELOW WATER SDG 14 Life below Water Monitoring the extent and dynamic change in mangrove forests Asia: 84.2% of mangrove areas have continued to decrease. Africa: 57.8% of mangrove areas have increased. Human activities have a greater impact on mangroves in Asian countries, while the impact is less in African countries. GDP growth has a greater impact on mangroves than population growth. 1990-2000 2000-2010 2010-2015 2015-2020 I .™„H 1990 ™ 2010 J Legend H 2000 H 2015 B 2020 II 1250 2500 SDG 15 Life on Land Interannual changes of global tree cover ■ Global tree area increased by 673 million hm2 from 2000 to 2020 The global tree area increased at a rate of 24,108,100 hm2/a, with a rapid increase rate from 2008 to 2015 and gradually stabilizing after 2015. ■ Significant regional discrepancy exists in tree cover change, showing increase trends in temperate and boreal forests and heterogeneous patterns in tropical areas. r. 2000-2020 Global tree area increased 673 million hm2 2000-2020 Tree cover slope (%/a) : : I I I Non-Significant Non-Forest -3 -2 -1 -0.5 -0.2 -0.05 0.05 0.2 0.5 1 2 3 Change trend of global tree cover from 2000 to 2020 (%/a) ******** *******+ Global tree area increased at a rate of 24,108,100 hm2/a a rapid increase rate from 2008 to 2015 and gradually stabilizing after 2015 Outline jSk) Technology Facilitation Mechanism A Digital Earth Platform: CAS Earth §>j CASEarth for SDGs Evaluation m) In't Center of Big Data for SDGs Big Earth Data in Support of SDGs China has released 4 Reports in UN GA written by the CBAS The Reports have showcased the results of research, monitoring and evaluation of relevant SDGs and their indicators at local, national, regional and global scales. ftbicutpci smj 2019 Report 2020 Report 2021 Report 2022 Report CBAS Mission BIG EARTH Data Changes ainableSocialil Adaptation Economy "<•■<■« Fooc Wellbeing Consumption Population Develop SDG data infrastructure and information and data products Provide new knowledges for SDG monitoring and evaluations Develop and launch a series of SDG Satellites Establish a think tank for STI to promote SDGs Capacity development for SDGs in developing countries CASEarth: a Partner of UN Online Platform Compendium 2020 Winners COVID-19 About 2030 CONNECT a United Nations online technology platform for the SDGs Search 2030 Connect is a dynamic new tool for entrepreneurs, innovators, students and leaders from around the world seeking to exchange ideas and technology, build networks, and work to advance the Sustainable Development Goals (SDGs). DCTCN ET (g) r?OpeoA.RE UNITTO NATIONS UNIVERSITY UNU -MERIT UNOSSC ~ UPMTCD M*TK>Nt OFFlCC f Ott iMMIMÍM m c 0O« ka i io* Ľnite ideas C©)t7:CLEAR fi) whs stocktaking 7 S Ur!!JIL CeSa ►li^HANGE ^'AEA CONNECT £jg Green Technology Bank )/e^ GSSD EXPO Nil! SOUTH-SOUTH WORLD Narrow WIPO j HL LH WIPO Re Search The Innovation Policy Platform CASEarth CASEarth was adopted into 2030 CONNECT as one of the 24 partners, and one of 6 in the category of Publications and Knowledge Resources. CBAS offered 6 Global Data Products for SDGs to UN Global 30-m spatial distribution of cropland in 2020 * Total cropland area is 2.015 billion ha, of which Asia occupies the largest cropland area of 735 million ha. * Top eight countries (U.S., China, India, Russia, Canada, Brazil, Australia and Argentina) account for over 50.03% of the world's total cropland. Cropland 9- >v Global spatial distribution of cropping intensity in 2020 * Cropping intensity index, with 85.2% of cropland in single cropping, 14.4% in double cropping and only 0.4% in triple cropping or above. v V • Cropland in multiple cropping pattern is mainly in East Asia, Southeast Asia, South Asia, and South America. I Single cropping Double cropping ■ Triple cropping Global 30-m map of forest cover in 2020 * Total global forest area was 3.684 billion hectares, accounting for 28.03% of the total global land area, equivalent to 0.47 hectares per person. CBAS offered 6 Global Data Products for SDGs to UN Global 30-m burned area distribution in 2020 * The burned areas are concentrated mainly in central and southern Africa, northern Australia, and central and southern South America. * The total area of burned land in the world was 3,419,900 km2. Africa had t: _„ the largest burned area, accounting for 79.99% of the globe. Global 30-m spatial distribution of mangroves 2000-2020 • The results evidence an overall net decrease of 8.76% in mangrove forests. • Mangrove decline has slowed down since 2000 with an increase in public awareness of mangrove protection. Global 30-m impervious-surface dynamic dataset 2000-2020 * It revealed a significant increase in global impervious surface from 696,000 km2 in 2000 to 1,107,300 km2 in 2020, a 59.08% increase about 411,300 km2. i.000 6.000 SDGSAT-1 Open Science Program RESEARCH CENTER OF BIG DATA CMS I OR SUSTAINABLE DEVELOPMENT GOALS B O Q SAT- 1 QPEN^BCIENCE PHQBRAM SDCSAT for UN Sustain*"*" Development Goal SDGSAT-1 Mission User Guide v (~_. Access Portals Links IS'BAR IRDR TTTTM SDGSAT-1 On Sept. 20, 2022, data collected by SDGSAT-1 are accessed globally free-of-charge to support the implementation of UN 2030 Agenda. Please visit "SDGSAT-1 Open Science Program" website: www.sdgsat.ac.cn ^SUSTAINABLE DEVELOPMENT a GOALS Digital Earth: a Tool to Drive SDGs 9 Digital Earth allows us to better understand our world in order to optimize our actions and better pursue sustainable development. 9 Digital Earth systems can provide powerful tools to understand and link complex interactions between human activity and earth systems at multiple scales to quantify social and environmental interactions. 9 It can therefore be an invaluable platform for decision support and policy development, in addition to the monitoring and assessment of progress and implementation gaps. INTERNATIONAL RESEARCH CENTER OF BIG DATA FOR SUSTAINABLE DEVELOPMENT GOALS Thanks No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China Tel: +86-10-82178985 Fax: +86-10-82178980