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Inferring Nighttime Satellite Imagery from Human Mobility [article]

Brian Dickinson, Gourab Ghoshal, Xerxes Dotiwalla, Adam Sadilek, Henry Kautz
2020 arXiv   pre-print
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

Brian Dickinson, Gourab Ghoshal, Xerxes Dotiwalla, Adam Sadilek, Henry Kautz
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

Brian Min, Kwawu Gaba
2014 Remote Sensing  
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]

Tomas Sako, Arturo Jr M. Martinez
2021 arXiv   pre-print
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

Deren Li, Wei Guo, Xiaomeng Chang, Xi Li
2020 Journal of Geographical Sciences  
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


X. Niu
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
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

Christopher Yeh, Anthony Perez, Anne Driscoll, George Azzari, Zhongyi Tang, David Lobell, Stefano Ermon, Marshall Burke
2020 Nature Communications  
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

Bin Chen, Yimeng Song, Bo Huang, Bing Xu
2020 Science of Remote Sensing  
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]

Christopher Yeh, Chenlin Meng, Sherrie Wang, Anne Driscoll, Erik Rozi, Patrick Liu, Jihyeon Lee, Marshall Burke, David B. Lobell, Stefano Ermon
2021 arXiv   pre-print
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

N. Jean, M. Burke, M. Xie, W. M. Davis, D. B. Lobell, S. Ermon
2016 Science  
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

Anais Dahmani-Scuitti, Walker Kosmidou-Bradley, Johanna Lee Belanger, Erwin Knippenberg
2021 Zenodo  
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]

Adel Daoud, Felipe Jordan, Makkunda Sharma, Fredrik Johansson, Devdatt Dubhashi, Sourabh Paul, Subhashis Banerjee
2021 arXiv   pre-print
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]

Takahiro Yabe, Nicholas K W Jones, P Suresh C Rao, Marta C Gonzalez, Satish V Ukkusuri
2021 arXiv   pre-print
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

David Shim
2012 Social Science Research Network  
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

Rafael Ch, Diego A. Martin, Juan F. Vargas
2020 Journal of Urban Economics  
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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