When Centroids Mislead: Quantifying the Consequences of Sub-Optimally Aggregating Gridded Raster Data to Polygons
Point data, such as population, disease incidence, and greenhouse gas emissions, are commonly aggregated to a uniform grid of raster data for storage and representation. In many remote sensing applications, polygons are instead used to describe regions of interest (e.g., countries and cities) which...
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| Autori principali: | , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2026-06-01
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| Serie: | ISPRS International Journal of Geo-Information |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2220-9964/15/6/244 |
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