Estimating and Interpreting Fine-Scale Gridded Population Using Random Forest Regression and Multisource Data

Estimating and Interpreting Fine-Scale Gridded Population Using Random Forest Regression and Multisource Data

Gridded population results at a fine resolution are important for optimizing the allocation of resources and researching population migration. For example, the data are crucial for epidemic control and natural disaster relief. In this study, the random forest model was applied to multisource data to...

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Bibliographic Details
Main Authors: Yun Zhou, Mingguo Ma, Kaifang Shi, Zhenyu Peng
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
population mapping
points of interest
random forest
urban area
Chongqing
Online Access:https://www.mdpi.com/2220-9964/9/6/369

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