This report shows how Indonesia can combine satellite imagery and geospatial data with machine learning to create maps showing areas of poverty, which could help shape targeted support for vulnerable communities.
Based on a collaborative study with Statistics Indonesia (BPS) and World Data Lab, the report shows how Indonesia can develop a grid-like poverty map. Computer vision and machine learning can help identify roads, buildings, and vegetation, and that information can be harnessed to estimate poverty levels. The report details poverty reduction efforts in the diverse archipelago and shows how geospatial data can help improve social protection and resource allocation.
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Paperback. Condition: new. Paperback. This report shows how Indonesia can combine satellite imagery and geospatial data with machine learning to create maps showing areas of poverty, which could help shape targeted support for vulnerable communities. Based on a collaborative study with Statistics Indonesia (BPS) and World Data Lab, the report shows how Indonesia can develop a grid-like poverty map. Computer vision and machine learning can help identify roads, buildings, and vegetation, and that information can be harnessed to estimate poverty levels. The report details poverty reduction efforts in the diverse archipelago and shows how geospatial data can help improve social protection and resource allocation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789292775643
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Paperback. Condition: new. Paperback. This report shows how Indonesia can combine satellite imagery and geospatial data with machine learning to create maps showing areas of poverty, which could help shape targeted support for vulnerable communities. Based on a collaborative study with Statistics Indonesia (BPS) and World Data Lab, the report shows how Indonesia can develop a grid-like poverty map. Computer vision and machine learning can help identify roads, buildings, and vegetation, and that information can be harnessed to estimate poverty levels. The report details poverty reduction efforts in the diverse archipelago and shows how geospatial data can help improve social protection and resource allocation. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9789292775643
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Paperback. Condition: new. Paperback. This report shows how Indonesia can combine satellite imagery and geospatial data with machine learning to create maps showing areas of poverty, which could help shape targeted support for vulnerable communities. Based on a collaborative study with Statistics Indonesia (BPS) and World Data Lab, the report shows how Indonesia can develop a grid-like poverty map. Computer vision and machine learning can help identify roads, buildings, and vegetation, and that information can be harnessed to estimate poverty levels. The report details poverty reduction efforts in the diverse archipelago and shows how geospatial data can help improve social protection and resource allocation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789292775643
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Taschenbuch. Condition: Neu. Mapping the Spatial Distribution of Poverty | Using Satellite Imagery and Other Geospatial Data in Indonesia | Asian Development Bank | Taschenbuch | Englisch | 2025 | Asian Development Bank | EAN 9789292775643 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 134451300
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