Synergistic Classification of Multilevel Land Patches (SC-MLPs): Reducing Conflicts and Improving Mapping Results for Land Uses and Functional Spaces With Very-High-Resolution Satellite Imagery-Reference-Cited by-同舟云学术

Synergistic Classification of Multilevel Land Patches (SC-MLPs): Reducing Conflicts and Improving Mapping Results for Land Uses and Functional Spaces With Very-High-Resolution Satellite Imagery

Published:2023 Issue: Volume:61 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Xiuyuan¹^ORCID,Xiong Shuping¹^ORCID,Dong Xiaoyan²,Du Shihong¹^ORCID

Affiliation:

1. Institute of Remote Sensing and GIS, Peking University, Beijing, China

2. School of Geography and Information Engineering, China University of Geosciences, Wuhan, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10295482.pdf?arnumber=10295482

Reference67 articles.

1. Land Use and Ecological Change: A 12,000-Year History

2. The land use and land cover change database and its relative studies in China

3. A neural network approach using multi-scale textural metrics from very high-resolution panchromatic imagery for urban land-use classification

4. RESEARCH: Theory in Practice: Applying Participatory Democracy Theory to Public Land Planning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. STMNet: Scene Classification-Assisted and Texture Feature-Enhanced Multiscale Network for Large-Scale Urban Informal Settlement Extraction From Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024