https://scholars.lib.ntu.edu.tw/handle/123456789/604775
標題: | Adaptive Non-Negative Geographically Weighted Regression for Population Density Estimation Based on Nighttime Light | 作者: | Hone-Jay Chu Chen-Han Yang Chelsea C. CHOU |
關鍵字: | nighttime light; population density; GWR; nonnegative constraint; LAND-USE; CHINA | 公開日期: | 2019 | 出版社: | MDPI | 卷: | 8 | 期: | 1 | 來源出版物: | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION | 摘要: | Nighttime light imagery provides a perspective for studying urbanization and socioeconomic changes. Traditional global regression models have been applied to explore the nonspatial relationship between nighttime lights and population density. In this study, geographically weighted regression (GWR) identifies the spatially varying relationships between population density and nighttime lights in mainland China. However, the rural population does not have a strong relationship with remote-sensing spectral features. The rural population estimation using nighttime light data alone easily identifies meaningless negative population density in the rural area. This study proposes an adaptive non-negative GWR (ANNGWR) to explore the spatial pattern of population density by using nonnegative constraints with an adaptive bandwidth of kernel. The ANNGWR solves the negative value of population density and serious overestimation of the western boundary. The result shows that the ANNGWR provides the best goodness-of-fit compared with linear regression and original GWR. This study applies Moran's I index to prove that the ANNGWR substantially decreases the spatial autocorrelation of the model residual. The model offers a robust and effective approach for estimating the spatial patterns of regional population density solely on the basis of nighttime light imagery. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/604775 | ISSN: | 2220-9964 | DOI: | 10.3390/ijgi8010026 |
顯示於: | 國家發展研究所 |
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