High-resolution mapping of GDP using multi-scale feature fusion by integrating remote sensing and POI data-Reference-Cited by-同舟云学术

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High-resolution mapping of GDP using multi-scale feature fusion by integrating remote sensing and POI data

Published:2024-05 Issue: Volume:129 Page:103812
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Wu Nan^ORCID,Yan Jining^ORCID,Liang Dong^ORCID,Sun Zhongchang^ORCID,Ranjan Rajiv^ORCID,Li Jun^ORCID

Publisher

Elsevier BV

Reference47 articles.

1. Geographic mapping with unsupervised multi-modal representation learning from VHR images and POIs;Bai;ISPRS J. Photogramm. Remote Sens.,2023

2. Random forests;Breiman;Mach. Learn.,2001

3. Chen, T., Guestrin, C., 2016. Xgboost: A scalable tree boosting system. In: Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining. pp. 785–794.

4. Mapping gridded gross domestic product distribution of China using deep learning with multiple geospatial big data;Chen;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2022

5. The assessment of industrial agglomeration in China based on NPP-VIIRS nighttime light imagery and POI data;Chen;Remote Sens.,2024

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