Estimating and Interpreting Fine-Scale Gridded Population Using Random Forest Regression and Multisource Data
Bibliographic Data
| ID | 22034281 |
|---|---|
| Authors | Yun Zhou (0000-0002-3396-5867, Southwest University), Mingguo Ma (0000-0002-6397-2929, Southwest University, corresponding author), Kaifang Shi (0000-0001-9047-2885, Southwest University), Zhenyu Peng (0000-0003-4574-425X, Chongqing Municipal Health Commission) |
| Year | 2020 |
| Volume | 9 |
| Issue | 6 |
| Pages | 369 |
| Publication date | 2020-06-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi9060369 |
| OpenAlex | W3032953096 |
| Language | EN |
| Citations received | 4 |
| References cited | 65 |
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 estimate the population distribution in impervious areas at a 30 m spatial resolution in Chongqing, Southwest China. The community population data from the Chinese government were used to validate the estimation accuracy. Compared with the other regression techniques, the random forest regression method produced more accurate results (R2 = 0.7469, RMSE = 2785.04 and p
Cartography · Estimation · Geography · Impervious surface · Population · Random forest · Regression · Regression analysis · Statistics · Computer Science · Demography · Environmental Science · Human Mobility and Location-Based Analysis · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Mathematics · Artificial Intelligence · Ecology
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MGWR
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Geographically Weighted Regression
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A new look at the statistical model identification
Greedy function approximation
Random Forests
Geographically Weighted Regression
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Causal Interpretations of Black-Box Models
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Impacts of land finance on urban sprawl in China
Spatiotemporal distribution characteristics and mechanism analysis of urban population density
City profile
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Social Sensing
A Framework for the Areal Interpolation of Socioeconomic Data
Mapping the results of local statistics
Multimodel Inference
| Unique citing works | 4 |
|---|---|
| Citations per year | 0,67 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 4 |