Comparison of Vehicle Detection Using Very High-Resolution Satellite Images

Golej, Peter; Horák, Jiří

doi:10.31490/9788024846026-17

Cited by 1 publication

(1 citation statement)

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“…In this study, although we included a framework for the extraction of satellite images spatially and temporally, this framework is limited to the maximum temporal resolution provided by Sentinel 2, which is 5 days 48 . A similar problem occurs in terms of spatial resolution, where the maximum spatial resolution obtained is 10 meters per pixel, limiting applications to applications with a temporality greater than 5 days and that do not require a spatial resolution of less than 10 meters such as people 49 or vehicle detection 50 .…”

Section: Technical Challengesmentioning

confidence: 99%

A multimodal framework for extraction and fusion of satellite images and public health data

Moukheiber,

Restrepo,

Cajas

et al. 2024

Sci Data

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In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health.

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Section: Technical Challengesmentioning

confidence: 99%