[go: up one dir, main page]
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Computer Vision and Pattern Recognition

arXiv:1905.02196 (cs)
[Submitted on 4 May 2019]

Title:Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery

Authors:Wenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David Lobell, Stefano Ermon
View PDF
Abstract:Millions of people worldwide are absent from their country's census. Accurate, current, and granular population metrics are critical to improving government allocation of resources, to measuring disease control, to responding to natural disasters, and to studying any aspect of human life in these communities. Satellite imagery can provide sufficient information to build a population map without the cost and time of a government census. We present two Convolutional Neural Network (CNN) architectures which efficiently and effectively combine satellite imagery inputs from multiple sources to accurately predict the population density of a region. In this paper, we use satellite imagery from rural villages in India and population labels from the 2011 SECC census. Our best model achieves better performance than previous papers as well as LandScan, a community standard for global population distribution.
Comments: 7 pages
Subjects: Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV)
ACM classes: I.2.10; I.2.6; J.2; J.4
Cite as: arXiv:1905.02196 [cs.CV]
  (or arXiv:1905.02196v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.1905.02196
Journal reference: AAAI/ACM Conference on AI, Ethics, and Society (AIES '19), January 27-28, 2019, Honolulu, HI, USA
Related DOI: https://doi.org/10.1145/3306618.3314263

Submission history

From: Wenjie Hu [view email]
[v1] Sat, 4 May 2019 18:33:22 UTC (3,684 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.CV
< prev   |   next >
new | recent | 2019-05
Change to browse by:
cs
eess
eess.IV

References & Citations

DBLP - CS Bibliography

listing | bibtex
Wenjie Hu
Jay Harshadbhai Patel
Zoe-Alanah Robert
Paul Novosad
Samuel Asher
…
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)