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Inferring Nighttime Satellite Imagery from Human Mobility
[article]
2020
arXiv
pre-print
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In this study we demonstrate that it is possible to accelerate this process by inferring artificial nighttime satellite imagery from human mobility data, while maintaining a strong differential privacy ...
Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for studying a wide range of socioeconomic factors. ...
: Inferred nighttime lights satellite imagery. ...
arXiv:2003.07691v1
fatcat:g72ah7lfn5habhv7izqxtrao4e
Inferring Nighttime Satellite Imagery from Human Mobility
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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In this study we demonstrate that it is possible to accelerate this process by inferring artificial nighttime satellite imagery from human mobility data, while maintaining a strong differential privacy ...
Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for studying a wide range of socioeconomic factors. ...
inferred nighttime satellite imagery (2016 VIIRS and "All-Weeks" predicted). ...
doi:10.1609/aaai.v34i01.5375
fatcat:ekrn4v6yszcfjgscsosp3qgpiu
Tracking Electrification in Vietnam Using Nighttime Lights
2014
Remote Sensing
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Based on an original survey of village-level units in Vietnam, this study compares nighttime light output from the U.S. ...
We report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural electrification in Vietnam. ...
the help of the National Oceanic and Adtmospheric Administration's (NOAA) National Geophysical Data Center, particularly the expertise of Chris Elvidge and his team in processing and interpreting the satellite ...
doi:10.3390/rs6109511
fatcat:aqzxe5qjbzdy5ljghkpbpvimwa
Seeing poverty from space, how much can it be tuned?
[article]
2021
arXiv
pre-print
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The approach builds upon several pioneering efforts over the last five years related to mapping poverty by deep learning to process satellite imagery and "ground-truth" data from the field to link features ...
The results of the project could therefore certainly be strengthened further through the integration of proprietary data from social networks, mobile phone providers, and other sources. ...
Bank CNES -Centre National d'Etudes Spatiales (CNES), France VHR -very high resolution satellite imagery, 0.3m per pixel in this article TIF -Tagged Image Format used in geolocated imagery ETL -extract-transform-load ...
arXiv:2107.14700v1
fatcat:jt67rulvobgx7ilci3fybu4q44
From earth observation to human observation: Geocomputation for social science
2020
Journal of Geographical Sciences
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In this context, geography, with the human-nature relationship as its core, is undergoing a transition from strictly earth observations to the observation of human activities. ...
It is possible to obtain vast amounts of spatiotemporal data related to human activities to support the study of human behavior and social evolution. ...
RS satellite imagery is an objective and accurate data source. To some extent, nighttime light images can be regarded as a representation of human activities and social economies. ...
doi:10.1007/s11442-020-1725-8
fatcat:es7yawfp6ja4zp4k7tju2oclyu
ESTIMATING HOUSING VACANCY RATE IN QINGDAO CITY WITH NPP-VIIRS NIGHTTIME LIGHT AND GEOGRAPHICAL NATIONAL CONDITIONS MONITORING DATA
2018
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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This paper proposed a practical model for estimating the HVR in Qingdao city using NPP-VIIRS nighttime light composed data, Geographic National Conditions Monitoring data (GNCMD) and resident population ...
We integrated nighttime light, GNCM and mobile operator data together, established and validated a machine learning model of HVR in Qingdao. ...
Nighttime light are related to both houses and people, so their intensity is a major variable in the vacancy rate model. Building data can be used for inferring the number of house units. ...
doi:10.5194/isprs-archives-xlii-3-1319-2018
fatcat:bqypwhx5dvgw7hcymudt3ne5vi
Using publicly available satellite imagery and deep learning to understand economic well-being in Africa
2020
Nature Communications
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Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery. ...
independent wealth measurements from censuses suggests that errors in satellite estimates are comparable to errors in existing ground data. ...
data from other passive sensors such as mobile phones 17 or social media platforms 24 . ...
doi:10.1038/s41467-020-16185-w
pmid:32444658
fatcat:rcxzkndlivcfde3j5cufmsdes4
A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations
2020
Science of Remote Sensing
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A novel method to extract urban human settlements by 1 integrating remote sensing and mobile phone locations 2 3 Abstract 19 Satellite-based human settlement extraction methods have limited practical 20 ...
Compared with 32 the widely used nighttime-light-based methods, the proposed method could solve the 33 long-existing problems such as data saturation or blooming effects, as well as 34 characterizing human ...
settlements characterized by nighttime light data (NTL) 537 and vegetation-adjusted nighttime light data (VANTL) derived from DMSP/OLS and 538 VIIRS, mobile-phone locating-time data (MPL), and NDVI-adjusted ...
doi:10.1016/j.srs.2020.100003
fatcat:ciugtlrribai7pxnp7zrb6tc2q
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning
[article]
2021
arXiv
pre-print
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Recent advances in machine learning have made it possible to utilize abundant, frequently-updated, and globally available data, such as from satellites or social media, to provide insights into progress ...
Furthermore, processing satellite and ground survey data requires domain knowledge that many in the machine learning community lack. ...
Acknowledgments The authors would like to thank everyone from the Stanford Sustainability and AI Lab for constructive feedback and discussion; the Mapillary team for technical support on the dataset; Rose ...
arXiv:2111.04724v1
fatcat:55nfc47fvveilj5bmhitzz5gbq
Combining satellite imagery and machine learning to predict poverty
2016
Science
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Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. ...
Using survey and satellite data from five African countries-Nigeria, Tanzania, Uganda, Malawi, and Rwanda-we show how a convolutional neural network can be trained to identify image features that can explain ...
ACKNOWLEDGMENTS We gratefully acknowledge support from NVIDIA Corporation through an NVIDIA Academic Hardware Grant Statistical mechanics relies on the maximization of entropy in a system at thermal equilibrium ...
doi:10.1126/science.aaf7894
pmid:27540167
fatcat:fh3ijmur6rhehna4tcaxtxlsli
Geospatial analysis of displacement in Afghanistan, a case study
2021
Zenodo
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Indeed, the IDMC 2020 report based their estimation of the total number of IDPs in Egypt on data from a Human Right Watch 2018 report, which analyzed satellite imagery of housing destruction (complemented ...
and flooding gathered through satellite and aerial imagery. ...
doi:10.5281/zenodo.5222692
fatcat:ju6fbzyrfbd67hfga64vxrapzu
Using satellites and artificial intelligence to measure health and material-living standards in India
[article]
2021
arXiv
pre-print
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The application of deep learning methods to survey human development in remote areas with satellite imagery at high temporal frequency can significantly enhance our understanding of spatial and temporal ...
annual composites of Landsat 7 imagery. ...
As reliable satellite imagery have existed since the 1980s (Young et al., 2017) , remote surveying using such imagery provides a low-cost, yet reliable alternative to track human development at a fine ...
arXiv:2202.00109v1
fatcat:qofhmdxkmzck5jcobownk7m2eq
Mobile Phone Location Data for Disasters: A Review from Natural Hazards and Epidemics
[article]
2021
arXiv
pre-print
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Mobile phone location data have enabled us to observe, estimate, and model human mobility dynamics at an unprecedented spatio-temporal granularity and scale. ...
While regions around the world face urgent demands to prepare for, respond to, and to recover from such disasters, large-scale location data collected from mobile phone devices have opened up novel approaches ...
, including satellite imagery (for a review article, see 14 ) and social media data (for review articles, see 12, 122 ). ...
arXiv:2108.02849v1
fatcat:6yqdxwjmxbcd3djng6yymq7vh4
Seeing from Above: The Geopolitics of Satellite Vision and North Korea
2012
Social Science Research Network
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Abstract Satellite imagery plays an important role in contemporary geopolitics. ...
Since satellites are deployed to reveal what should be invisible, their ability to detect and expose, or "see from above," implies a particular power. ...
The regular references made by the US State Department's annual report on North Korean human rights to the accounts and imagery of ). ...
doi:10.2139/ssrn.2145851
fatcat:b2bbcybs2nfstdrsy5b5dtgkwa
Measuring the Size and Growth of Cities Using Nighttime Light
2020
Journal of Urban Economics
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light images across satellites and across time. ...
This paper uses high-resolution images of nighttime luminosity to estimate a globally comparable measure of the size of metropolitan areas around the world for the years 2000 and 2010. ...
The future of remote sensing tools and nighttime light appears to be promising as an increasing number of satellites become available to follow human migration and urban built-up patterns. ...
doi:10.1016/j.jue.2020.103254
fatcat:kidvln23lnathn3npqxuwr3qhu
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