Modelling agricultural drought: a review of latest advances in big data technologies
This article reviews the main recent applications of multi-sensor remote sensing and Artificial
Intelligence techniques in multivariate modelling of agricultural drought. The study focused …
Intelligence techniques in multivariate modelling of agricultural drought. The study focused …
A systematic review of mobile phone data in crime applications: a coherent taxonomy based on data types and analysis perspectives, challenges, and future research …
Digital technologies have recently become more advanced, allowing for the development of
social networking sites and applications. Despite these advancements, phone calls and text …
social networking sites and applications. Despite these advancements, phone calls and text …
An adversarial generative network for crop classification from remote sensing timeseries images
Due to the increasing demand for the monitoring of crop conditions and food production, it is
a challenging and meaningful task to identify crops from remote sensing images. The state …
a challenging and meaningful task to identify crops from remote sensing images. The state …
Comparing deep learning and statistical methods in forecasting crowd distribution from aggregated mobile phone data
Accurately forecasting how crowds of people are distributed in urban areas during daily
activities is of key importance for the smart city vision and related applications. In this work …
activities is of key importance for the smart city vision and related applications. In this work …
A Framework to Predict High-Resolution Spatiotemporal PM2.5 Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China
Air-borne particulate matter, PM2. 5 (PM having a diameter of less than 2.5 micrometers),
has aroused widespread concern and is a core indicator of severe air pollution in many …
has aroused widespread concern and is a core indicator of severe air pollution in many …
A method for the estimation of finely-grained temporal spatial human population density distributions based on cell phone call detail records
Estimating and map** population distributions dynamically at a city-wide spatial scale,
including those covering suburban areas, has profound, practical, applications such as …
including those covering suburban areas, has profound, practical, applications such as …
Exploring methods for map** seasonal population changes using mobile phone data
D Woods, A Cunningham, CE Utazi… - Humanities and Social …, 2022 - nature.com
Data accurately representing the population distribution at the subnational level within
countries is critical to policy and decision makers for many applications. Call data records …
countries is critical to policy and decision makers for many applications. Call data records …
Using an Internet of Behaviours to study how air pollution can affect people's activities of daily living: a case study of Bei**g, China
This study aims to quantitatively model rather than to presuppose whether or not air pollution
in Bei**g (China) affects people's activities of daily living (ADLs) based on an Internet of …
in Bei**g (China) affects people's activities of daily living (ADLs) based on an Internet of …
An urban crowd flow model integrating geographic characteristics
Y Zhang, S Wu, Z Zhao, X Yang, Z Fang - Scientific reports, 2023 - nature.com
Predicting urban crowd flow spatial distributions plays a critical role in optimizing urban
public safety and traffic congestion management. The spatial dependency between regions …
public safety and traffic congestion management. The spatial dependency between regions …
A better way to monitor haze through image based upon the adjusted LeNet-5 CNN model
Recognition of haze images is a prerequisite for appropriately realizing image dehazing
algorithms, which play an important role in detecting various types of outdoor environments …
algorithms, which play an important role in detecting various types of outdoor environments …