Big Earth Data in Support of the Sustainable Development Goals (2019)
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- Nombre de pages210
- FormatPDF
- ISBN978-2-7598-2442-7
- EAN9782759824427
- Date de parution09/02/2021
- Protection num.Digital Watermarking
- Taille9 Mo
- Infos supplémentairespdf
- ÉditeurEDP Sciences
Résumé
Big Earth Data in Support of the Sustainable Development Goals 2019 presents 27 case studies of "Big Earth Data Science Engineering Program" (CASEarth) on the development of the Sustainable Development Goals (SDGs) indicators and sustainability assessments in six SDGs, including: SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), SDG 14 (Life below Water), and SDG 15 (Life on Land).
These cases provide in-depth, systematic research and evaluation results on the selected SDGs and indicators by means of data, method models, and decision support at global, regional, national and local scales. The 27 case studies covered 20 indicators, with focus varying from constructing databases, building index systems, and evaluating indicator progress. Each case study first clearly lists the corresponding SDG targets and indicators it addresses, and then proceeds with the research methods, data, analysis results, and prospects for future research.
It can be seen that Big Earth Data as a new scientific methodology has started demonstrating its great value and potential for applications in monitoring and evaluating SDGs for China and developing countries around the world. The report concludes with a summary of the major progress in Big Earth Data for SDGs and future research priorities.
These cases provide in-depth, systematic research and evaluation results on the selected SDGs and indicators by means of data, method models, and decision support at global, regional, national and local scales. The 27 case studies covered 20 indicators, with focus varying from constructing databases, building index systems, and evaluating indicator progress. Each case study first clearly lists the corresponding SDG targets and indicators it addresses, and then proceeds with the research methods, data, analysis results, and prospects for future research.
It can be seen that Big Earth Data as a new scientific methodology has started demonstrating its great value and potential for applications in monitoring and evaluating SDGs for China and developing countries around the world. The report concludes with a summary of the major progress in Big Earth Data for SDGs and future research priorities.
Big Earth Data in Support of the Sustainable Development Goals 2019 presents 27 case studies of "Big Earth Data Science Engineering Program" (CASEarth) on the development of the Sustainable Development Goals (SDGs) indicators and sustainability assessments in six SDGs, including: SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), SDG 14 (Life below Water), and SDG 15 (Life on Land).
These cases provide in-depth, systematic research and evaluation results on the selected SDGs and indicators by means of data, method models, and decision support at global, regional, national and local scales. The 27 case studies covered 20 indicators, with focus varying from constructing databases, building index systems, and evaluating indicator progress. Each case study first clearly lists the corresponding SDG targets and indicators it addresses, and then proceeds with the research methods, data, analysis results, and prospects for future research.
It can be seen that Big Earth Data as a new scientific methodology has started demonstrating its great value and potential for applications in monitoring and evaluating SDGs for China and developing countries around the world. The report concludes with a summary of the major progress in Big Earth Data for SDGs and future research priorities.
These cases provide in-depth, systematic research and evaluation results on the selected SDGs and indicators by means of data, method models, and decision support at global, regional, national and local scales. The 27 case studies covered 20 indicators, with focus varying from constructing databases, building index systems, and evaluating indicator progress. Each case study first clearly lists the corresponding SDG targets and indicators it addresses, and then proceeds with the research methods, data, analysis results, and prospects for future research.
It can be seen that Big Earth Data as a new scientific methodology has started demonstrating its great value and potential for applications in monitoring and evaluating SDGs for China and developing countries around the world. The report concludes with a summary of the major progress in Big Earth Data for SDGs and future research priorities.
