Developing an annual building volume dataset at 1-km resolution from 2001 to 2019 in China-Reference-Cited by-同舟云学术

Developing an annual building volume dataset at 1-km resolution from 2001 to 2019 in China

Published:2024-03-25 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Yan Wenting¹²,Wu Jianping²,Zhang Chaoqun¹²,Chen Xiuzhi¹,Ren Jiashun¹²,Xiao Zhenzhen²,Liao Ziyin²,Lafortezza Raffaele³,Li Xueyan²,Su Yongxian²

Affiliation:

1. Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University (Zhuhai), Zhuhai, People’s Republic of China

2. Guangdong Provincial Key Lab of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, People’s Republic of China

3. Department of Agricultural and Environmental Sciences, University of Bari ‘A. Moro’, Bari, Italy

Funder

National Natural Science Foundation of China

Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

‘GDAS’ Project of Science and Technology Development

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2330690

Reference84 articles.

1. Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data

2. Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data

3. Will skyscrapers save the planet? Building height limits and urban greenhouse gas emissions

4. Breiman L. A. Cutler A. Liaw and M. Wiener. 2018. Package ‘randomForest’: Breiman and Cutler's Random Forests for Classification and Regression.