Spatially granular poverty index (SGPI) for urban poverty mapping in Jakarta metropolitan area (JMA): a remote sensing satellite imageries and geospatial big data approach.
Nasiya Alifah UtamiArie Wahyu WijayantoSetia PramanaErni Tri AstutiPublished in: Earth Sci. Informatics (2023)
Keyphrases
- remote sensing
- big data
- urban areas
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- satellite images
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- land cover
- geographical information systems
- big data analytics
- digital image analysis
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- satellite imagery
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- business intelligence
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- social media
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- multi spectral images
- database
- data warehousing