This report presents the results of a feasibility study on generating high-quality poverty statistics in the Philippines using satellite imagery, geospatial data, and powerful machine-learning algorithms.
The leave no one behind principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a countrys population. Conducted by ADB in collaboration with the Philippine Statistics Authority and the World Data Lab, the study aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines.
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This report presents the results of a feasibility study on generating high-quality poverty statistics in the Philippines using satellite imagery, geospatial data, and powerful machine-learning algorithms.The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country's population. Conducted by ADB in collaboration with the Philippine Statistics Authority and the World Data Lab, the study aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines. Artikel-Nr. 37397961/1
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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This report presents the results of a feasibility study on generating high-quality poverty statistics in the Philippines using satellite imagery, geospatial data, and powerful machine-learning algorithms.The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country's population. Conducted by ADB in collaboration with the Philippine Statistics Authority and the World Data Lab, the study aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines. Artikel-Nr. 37397961/2
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