A correlation analysis study on satellite image nightlight features and development of Africa regional economy

Nightlight intensity has become an important factor of measuring the wealthiness of a country or an area, it mostly relies on extracting the feature from the satellite images and it becomes a dominate factor that determines the economic development. This study used CNN based deep learning model to e...

Full description

Saved in:
Bibliographic Details
Published in:E3S web of conferences 2021-01, Vol.257, p.3032
Main Author: Li, Xizhi
Format: Article
Language:English
Subjects:
Correlation analysis
Economic development
Economic models
Feature extraction
Image processing
Light intensity
Luminous intensity
Machine learning
Optimization
Polls & surveys
Regional development
Regression analysis
Regression models
Regularization
Satellite imagery
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Nightlight intensity has become an important factor of measuring the wealthiness of a country or an area, it mostly relies on extracting the feature from the satellite images and it becomes a dominate factor that determines the economic development. This study used CNN based deep learning model to extract the light intensity feature from the satellite images and associate it with additional survey information. CNN has been wildly used for image feature extraction. Then, the study combined the survey data and light intensity feature together and conducted comprehensive experiments on different regression models that using different regularizations and optimization approaches. The paper studied the influence of regularization and optimization approaches to the model. Through the feature selection, hyper-parameter tuning, and model evaluation, the study can select the best model. This paper compares different linear regression models. They utilize different regularization and optimization. The experiment results indicate that Lasso regression model is the best model.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202125703032