Big Earth Data in Support of the Sustainable Development Goals (2021)

Edited by Guo Huadong

Description

Big Earth Data in Support of the Sustainable Development Goals (2021): China showcases the innovative practice of applying Big Earth Data to the monitoring and evaluating indicators for six SDGs, i.e., SDG 2 Zero Hunger, SDG 6 Clean Water and Sanitation, SDG 11 Sustainable Cities and Communities, SDG 13 Climate Action, SDG14 Life below Water, SDG 15 Life on Land, and the analysis of the interactions among multiple SDG indicators. It presents 52 case studies on 27 targets. The report showcases the results of research, monitoring, and evaluation of SDGs and their indicators at two scales-local, national-totalling 36 data products, 25 methods and models, and 41 decision-support recommendations. These research results demonstrate China's exploration and practice in promoting the implementation of the UN 2030 Agenda for Sustainable Development through scientific and technological innovation, fully reveal the application value and broad prospects of Earth's big data technology in monitoring and evaluating the sustainable development goals, and open up new ways and methods to support the implementation of the UN 2030 Agenda for Sustainable Development through the use of advanced technologies and methods such as big data and artificial intelligence under the framework of the UN technology promotion mechanism. It can provide reference for countries to strengthen the implementation monitoring and evaluation of the agenda.This report can be read by researchers in related fields and decision makers in relevant national departments.

I. Pretace

V. Foreword

IX. Executive Summary

Chapter 1. Introduction/1

 Chapter 2. SDG 2 : Zero Hunger

Background / 8

Main Contributions / 9

Case Study / 11

2.1 Biomass development and food security in China underthe carbon neutral vision / 11

2.2 Precision agriculture based onSatellite-Aerial-Ground Integrated (SAGI) technology / 18

2.3 Spatiotemporal variations in cropping intensity in Chinain 2001-2020 / 24

2.4 Mapping crop distribution and spatiotemporal changesin China / 30

2.5 Evaluation of mitigating effects of irrigation onagricultural drought in the North China Plain / 35

2.6 Construction of an efficient ecological agricultureparadigm: An experiment in a low-medium yield region along the Lower Reaches ofthe Yellow River / 45

Summary / 51

Chapter 3. SDG6 : Clean Water and sanitation

Background / 56

Main Contributions / 57

Case Study / 59

3.1 Changes in sewage treatment capacity in China / 59

3.2 Monitoring and evaluating the changes in lake waterclarity in China / 68

3.3 Spatiotemporal differences in water stress in China /76

3.4 Evaluating water use efficiency in Lincang City,Y unnan Province, China, from 2010 to 2020 / 85

3.5 Assessment of China's integrated water resources management / 95

3.6 Change in natural and artificial water bodies in China from 2000 to 2020 / 100

3.7 Spatiotemporal changes in China's vegetated wetlands from 2010 to 2020 / 105

3.8 Environmental health status of Ramsar sites in China/ 111

Summary / 119

 Chapter 4 SDG 11 : Sustainable cities and communities

Main Contributions / 123

Case Study / 125

4.1 Assessing housing affordability in China (2010-2020)/ 125

4.2 Proportion of the population with convenient accessto public transportation in China / 130

4.3 Evaluation and projection of land use efficiency inChina's major cities / 135

4.4 Mapping spatial distribution of building height incities in China / 142

4.5 Response of land cover to extreme drought and itsclimate resilience at the Honghe Hani Rice Terraces world heritage site / 148

4.6 Interannual variation of the total loss from naturaldisasters at the prefecture level (2010-2020) / 157

4.7 Patterns and dynamies of UGS in China / 162

4.8 Community-scale urban landscape change and sustainable development indicators in major Chinese cities / 167

4.9 Integrated evaluation of SDG Il indicators in Chinesecities from 2015 to 2020 / 172

Summary/178

 Chapter 5. SDG13 : Climate action

Background/182

Main Contributions / 183

Case Study / 185

5.1 Interannual changes in sand and dust weather in China in 2010-2020 / 185

5.2 Risk assessment of maize yield reduction caused by drought in China from 2000 to 2020 / 190

5.3 Spatiotemporal distribution and changes in waterlogging in China / 195

5.4 Spatiotemporal variations in greenhouse gas concentration in China / 201

5.5 Impacts of climate change on net ecosystem productivity of forests in China / 205

5.6 Impacts of China's dietary model transformation on the sustainable development goals / 210

Summary/215

 Chapter 6.SDG 14 : Life below water

Background/218

Main Contributions / 218

Case Study / 221

6.1 Source apportionment of microplastics in Jiaozhou Bay, China / 221

6.2 Monitoring and forecasting macroalgal blooms in the Yellow Sea / 225

6.3 Simulating marine ecosystem health on China's const /230

6.4 Risk assessment of inundation in China's coastal zonecaused by sea-level rise / 235

6.5 Changes in mangrove forests in China / 243

6.6 Hypoxia, acidification and relations to phytoplanktonblooms in river-dominated continental shelves: A case study of the ChangjiangEstuary (2021) / 248

6.7 Mainland coastline changes and the major coastalreclamation in China from 2000 to 2020 / 255

6.8 Changes in costal aquaculture ponds in China / 262

6.9 Dynamic monitoring of raft culture in China's coastal waters / 267

Summary / 273

 Chapter 7 : SDG 15 : Life on land

Background / 276

Main Contributions / 276

Case Study / 279

7.1 Assessment of ecosystems and the dynamics of ecosystem quality in China / 279

7.2 Current status and gaps in grassland ecosystem conservation in China / 283

7.3 Big data simulation to generate a high-resolution distribution of rare and endangered plants / 287

7.4 Freeze-thaw desertification monitoring in the north eastern Qinghai-Tibet Plateau / 292

7.5 Spatial and temporal change patterns and driving forces of salinization in the Lower Reaches of the Yellow River and adjacent coastal areas from 2015 to 2020 / 298

7.6 Biodiversity conservation value of the land inhabitedby ethnic groups in the Qinghai-Tibet Plateau / 303

7.7 Monitoring spatiotemporal variations in winteringSiberian crane habitats / 309

Summary / 313

 Chapter 8. Interactions among SDG indicators

Background/316

Main Contributions / 319

Case Study / 321

8.I Synergies of water-food-ecology in North China / 321

8.2 Synergy between economie development and carbonemission reduction in Hainan / 327

8.3 Ecological compensation and multi-index synergy inthe Xin'an River Basin / 334

8.4 Simulation and analysis of land use evolution inChina under the constraints of multiple SDGs / 341

8.5 Interaction between water-food-ecology security andthe rebound effect: Impacts on multiple SDGs targets in the Heihe River Basin /346

8.6 Sustainable development of coal resource-based cites in China / 352

8.7 Spatio temporal characteristies of human settlements derived from time-series remote sensing data in Jinsha River Basin, Yunnan Province, China / 358

Summary / 368 

Chapter 9 Summary and Prospects / 371

References / 377

Acronyms / 394

 

Sujets

• Environmental Science
• Sciences et techniques
• UN
• Environment
• United Nations
• SDG
• China
• Science
• Environnement

Informations

• Publié par: EDP Sciences
• Date de parution: 31 octobre 2022
• Nombre de lectures: 0
• EAN13: 9782759829354
• Langue: English
• Poids de l'ouvrage: 210 Mo

Extrait

地球大数据支撑可持续发展目标报告2020：中国篇 英文版 扉页.pdf 1 2022-08-17 10:52:11
C
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CM
MY
CY
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Guo Huadong
International Research Center of Big Data for Sustainable Development Goals
Aerospace Information Research Institute, Chinese Academy of Sciences
China
Map Content Approval Number: GS 京(2022) 0855 号
ISBN: 978-7-03-071145-8
Science Press
ISBN(print): 978-2-7598-2934-7 ISBN (e Book): 978-2-7598-2935-4
EDP Sciences
© Science Press and EDP Sciences 2022
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deemed an infringement of copyright punishable under Articles 425 and following of the French
Penal Code.Big Earth Data in Support of the Sustainable
Development Goals (2021): China
Editorial Board
Editor-in-Chief: Guo Huadong
Associate Editors-in-Chief : (in alphabetical order of last name)
Chen Fang Chen Yu Dong Jinwei Han Qunli
Huang Chunlin Huang Lei Jia Gensuo Jia Li
Li Xiaosong Liang Dong Liu Jie Lu Shanlong
Sun Zhongchang Wang Futao Wu Bingfang Yu Rencheng
Zuo Lijun
Editorial Board : (in alphabetical order of last name)
Cao Min Cao Yun Chen Min Chen Xidong
Chen Yaxi Chen Zhengchao Cheng Qingping Cheng Yi
Dai Hancheng Dou Yinyin Du Shihong Fang Shibo
Feng Yaya Gai Yingchun Gao Feng Guo Yongxuan
Hong Mengmeng Hou Huping Hou Xiyong Hou Yanfang
Hu Bisong Hu Zaiyuan Jia Huicong Jia Mingming
Jiang Huiping Jiang Yunzhong Jiao Yuanmei Kong Lingqiao
Kong Xiangji Kuang Wenhui Lao Jieying Li Qingting
Li Yang Li Yifan Liao Huijuan Liu Haimeng
Liu Liangyun Liu Nanjiang Liu Ronggao Liu Wenliang
Liu Yujie Liu Zhe Lu Jing Luo Lei
Mao Dehua Mi Xiangcheng Niu Zhenguo Qian Jianping
Ren Ming Ren Yitong Shangguan Donghui Sun Song
Sun Tao Sun Xiaoxia Sun Zhigang Tian Yu
Wang Chengyi Wang Cheng Wang Jianghao Wang Juanle
Wang Lizhe Wang Meng Wang Yong Wang Yuhua
Wang Zongming Wei Qinsheng Wei Xianhu Wei Yanqiang
Wu Wenjin Xia Jisheng Xiang Haibing Xu He
Xu Jinyong Xu Weihua Xue Yong Yan Dongmei
Yan Feng Yan Nana Yang Dezhou Yang Xiaofeng
Yu Bo Yu Xiubo Yu Qiangyi Zhang Jie
Zhang Miao Zhang Xiuyuan Zhao Junfang Zheng Chaolei
Zheng Shan Zheng Zhenwei Zhou Yan Zhu Jinfeng
Zhuang HuifuPreface i
Preface
n 2015, the United Nations adopted the 2030 Agenda for ISustainable Development, which includes 17 sustainable
development goals (SDGs) to be achieved by 2030. The SDGs
are about achieving economic, social and environmental
sustainability on a global scale. Since the launch of the 2030
Agenda, China has worked to promote the SDGs while
embracing a new philosophy of innovative, coordinated, green,
open and shared development, achieving impressive results
in eradicating absolute poverty, addressing climate change,
improving ecological environment, promoting public health
service and ensuring food security. Steady progress has been
made in achieving high-quality development. At the same
time, China has actively engaged in and promoted international
development cooperation, and has provided reliable public goods
for the realization of SDGs across the world.
The experience of the past six years, however, has shown
that there remain a number of major challenges to scientifically
evaluating the implementation of the 2030 Agenda, the most
serious ones being the lack of data, the incompleteness of the
indicator system, and the gap in capacity of having and using
data as a result of development disparity. As China’s national Big Earth Data in Support of the Sustainable Development Goals (2021): Chinaii
scientific institute, the Chinese Academy of Sciences (CAS)
has long been devoted to promoting SDGs through big data.
In recent years, CAS has been working with universities,
research institutes and enterprises at home and abroad to explore
the application of combined new technologies such as cloud
computing, artificial intelligence, space technology and network
communication technology to improve the evaluation system
for SDGs, develop public data products and inform
decisionmaking.
Chinese President Xi Jinping announced on September
22, 2020, at the 75th session of the United Nations General
Assembly, that China will establish an International Research
Center of Big Data for Sustainable Development Goals (CBAS),
to provide new impetus for the implementation of the 2030
Agenda. Subsequently, CBAS was officially launched in Beijing
on September 6, 2021. President Xi Jinping sent a congratulatory
letter, and United Nations Secretary-General António Guterres
delivered a video message to congratulate on the establishment
of the Center. I believe that CBAS will use big data to give
support to the sustainable development of China and the world.
In recent years, CAS has, based on its advantages, done
demonstration studies on monitoring and evaluation of indicators
for the goals of Zero Hunger, Clean Water and Sanitation,
Sustainable Cities and Communities, Climate Action, Life below
Water and Life on Land, and issued annual reports on big earth Preface iii
data in support of the sustainable development goals. The 2021
report continues to focus on the practical scenarios for these
SDGs’ realization, and presents research results including single
indicator progress evaluation and integrated multi-indicator
evaluation. These results provide stronger scientific basis
for understanding the dynamic trends of SDG indicators and
analyzing the problems hindering sustainable development, and
they can inform decision on SDG realization in different scales
and regions.
2021 marks the 50th anniversary of the restoration of the
People’s Republic of China’s lawful seat in the United Nations.
This CAS report is part of China’s sustained contribution in the
form of science and technology to the implementation of the
2030 Agenda. CAS will further strengthen the collaborations
with international counterparts to address new challenges to
sustainable development through science, technology and
innovation.
Hou Jianguo
President, Chinese Academy of SciencesForeword
he COVID-19 pandemic has brought unprecedented Tchallenges to the implementation of the 2030 Agenda for
Sustainable Development across the world, to a large extent
affecting existing achievements and resulting in stagnation
or even regression. Recognizing the important role scientific
and technological innovation can play in promoting economic
and social development, the United Nations established
the Technology Facilitation Mechanism (TFM) for SDGs in
2015. In the Sustainable Development Goals Report 2020, the
United Nations Secretary-General António Guterres called for a
coordinated and comprehensive international response and recovery
efort based on sound data and science guided by the SDGs.
More effective ways need to be explored to address the data
challenge facing SDGs. Thanks to the development of science
and technology, the global data volume is growing exponentially.
Advances in computing and data technologies have made
realtime processing and analysis of big data a reality, while new
types of data combined with traditional data, such as statistical
and survey data, can create more detailed, timely and
highquality information. Big Earth Data technology, through its
extensive use and further innovation, can be an effective way
to address the data divide and the lack of information and tools
available for sustainable development.Big Earth Data in Support of the Sustainable Development Goals (2021): Chinavi
The International Research Center of Big Data for Sustainable
Development Goals, building upon the strength of CAS, will
use big data to support the SDGs. A full-fledged center will
have the potential to carry out functions that include building
an SDG big data technology service system capable of storage,
calculation, analysis, and service, conducting scientific research
on monitoring and evaluating SDG indicators, developing and
operating SDG science satellites, constructing a think tank
on science and technology for sustainable development, and
promoting personnel training and capacity building using big
data for SDGs.
In recent years, CAS has conducted case studies that use Big
Earth Data technology to monitor and evaluate indicators for six
SDGs—Zero Hunger, Clean Water and Sanitation, Sustainable
Cities and Communities, Climate Action, Life below Water, and
Life on Land. CAS issued reports on “Big Earth Data in Support
of the Sustainable Development Goals” for two consecutive
years during the 74th and 75th Sessions of the United Nations
General Assembly, highlighting the important value and role
of Big Earth Data technology in addressing challenges for
sustainable development.
The 2021 report integrates innovations in the past three years
in the practice of using Big Earth Data technology to monitor
and evaluate the SDGs. Focusing on the six SDGs, the report
presents 52 typical cases on two scales—local, national—
detailing the results of research, monitoring and evaluating SDGs
indicators from the perspectives of data, methods, models and
decision support. Furthermore, the report demonstrates methods Foreword vii
for monitoring, evaluating and analyzing the interactions among
multiple SDGs, thus laying a good foundation for the future
coordinated pursuit of multiple SDGs in different scenarios. The
findings of the report can provide new analyt