The contribution of data-driven technologies in achieving the sustainable development goals
The United Nations' Sustainable Development Goals (SDGs) set out to improve the quality of
life of people in developed, emerging, and developing countries by covering social and …
life of people in developed, emerging, and developing countries by covering social and …
A review of explainable AI in the satellite data, deep machine learning, and human poverty domain
Recent advances in artificial intelligence and deep machine learning have created a step
change in how to measure human development indicators, in particular asset-based …
change in how to measure human development indicators, in particular asset-based …
Wheat crop yield prediction using deep LSTM model
S Sharma, S Rai, NC Krishnan - arXiv preprint arXiv:2011.01498, 2020 - arxiv.org
An in-season early crop yield forecast before harvest can benefit the farmers to improve the
production and enable various agencies to devise plans accordingly. We introduce a …
production and enable various agencies to devise plans accordingly. We introduce a …
Boundary-aware 3D building reconstruction from a single overhead image
We propose a boundary-aware multi-task deep-learning-based framework for fast 3D
building modeling from a single overhead image. Unlike most existing techniques which rely …
building modeling from a single overhead image. Unlike most existing techniques which rely …
Multi-source satellite imagery and point of interest data for poverty mapping in East Java, Indonesia: Machine learning and deep learning approaches
This study proposes a novel approach to provide a more granular poverty map in terms of
coverage (up to a grid level with the spatial resolution of 1.5 km) with less cost and time to …
coverage (up to a grid level with the spatial resolution of 1.5 km) with less cost and time to …
Predicting multi-level socioeconomic indicators from structural urban imagery
Understanding economic development and designing government policies requires
accurate and timely measurements of socioeconomic activities. In this paper, we show how …
accurate and timely measurements of socioeconomic activities. In this paper, we show how …
Predicting socioeconomic indicators using transfer learning on imagery data: an application in Brazil
DA Castro, MA Álvarez - GeoJournal, 2023 - Springer
Censuses and other surveys responsible for gathering socioeconomic data are expensive
and time consuming. For this reason, in poor and developing countries there often is a long …
and time consuming. For this reason, in poor and developing countries there often is a long …
Estimation of GDP using deep learning with NPP-VIIRS imagery and land cover data at the county level in CONUS
Accurate estimation of gross domestic product (GDP) at small geographies is of great
significance to evaluate the distribution and dynamics of socio-economic development …
significance to evaluate the distribution and dynamics of socio-economic development …
Estimating city-level poverty rate based on e-commerce data with machine learning
There are many big data sources in Indonesia, for example, data from social media, financial
transactions, transportation, call detail records, and e-commerce. These types of data have …
transactions, transportation, call detail records, and e-commerce. These types of data have …
Using satellite images and deep learning to measure health and living standards in india
Using deep learning with satellite images enhances our understanding of human
development at a granular spatial and temporal level. Most studies have focused on Africa …
development at a granular spatial and temporal level. Most studies have focused on Africa …