Application of Nighttime Light Data Simulation Based on Multi-Indicator System and Machine Learning Model in Predicting Potentially Suitable Economic Development Areas: A Case Study of the Turpan–Hami Region

Application of Nighttime Light Data Simulation Based on Multi-Indicator System and Machine Learning Model in Predicting Potentially Suitable Economic Development Areas: A Case Study of the Turpan–Hami Region

In recent years, the accelerated urbanization process in China has led to increased land resource constraints and unregulated expansion, imposing significant pressure on ecosystems and the environment. As a critical node along the Silk Road Economic Belt, the Turpan–Hami region has experienced rapid...

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Bibliographic Details
Main Authors: Guangpeng Zhang, Li Zhang, Yiyang Chen, Meng Chen, Jingjing Tian, Yin Wu
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
urban economic development
machine learning
nighttime light data
SHAP analysis
Turpan–Hami region
Online Access:https://www.mdpi.com/2072-4292/17/2/240
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