机构

• 植物研究所 [5]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [5]

发表日期

• 2022 [1]
• 2021 [1]
• 2020 [2]
• 2019 [1]

学科主题

• Geoscience... [5]
• Environmen... [2]
• Imaging Sc... [2]
• Remote Sen... [2]
• Geography,... [1]
• Meteorolog... [1]
• 更多

筛选

浏览/检索结果: 共5条，第1-5条 帮助 限定条件 学科主题：Geosciences, Multidisciplinary    专题：植物研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序题名升序题名降序作者升序作者降序发表日期升序发表日期降序 Human-Climate Coupled Changes in Vegetation Community Complexity of China Since 1980s 期刊论文  OAI收割 EARTHS FUTURE, 2022, 卷号: 10, 期号: 7 作者:  Su, Yanjun;  Guo, Qinghua;  Guan, Hongcan;  Hu, Tianyu;  Jin, Shichao   |  收藏  |  浏览/下载：16/0  |  提交时间：2024/03/07 vegetation community complexity  human activities  climate change  vegetation map   Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations 期刊论文  OAI收割 ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2021, 卷号: 171, 页码: 36-48 作者:  Wu, Shengbiao;  Wang, Jing;  Yan, Zhengbing;  Song, Guangqin;  Chen, Yang   |  收藏  |  浏览/下载：8/0  |  提交时间：2023/02/24 Multi-scale remote sensing  Phenocam  High-resolution satellite  MODIS  Individual tree-crown  Leaf phenology   Application of deep learning in ecological resource research: Theories, methods, and challenges 期刊论文  OAI收割 SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474 作者:  Guo, Qinghua;  Jin, Shichao;  Li, Min;  Yang, Qiuli;  Xu, Kexin   |  收藏  |  浏览/下载：14/0  |  提交时间：2022/01/06 Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge   Application of deep learning in ecological resource research: Theories, methods, and challenges 期刊论文  OAI收割 SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474 作者:  Guo, Qinghua;  Jin, Shichao;  Li, Min;  Yang, Qiuli;  Xu, Kexin   |  收藏  |  浏览/下载：7/0  |  提交时间：2022/03/01 Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge   The Influence of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne LiDAR Data 期刊论文  OAI收割 REMOTE SENSING, 2019, 卷号: 11, 期号: 23 作者:     |  收藏  |  浏览/下载：35/0  |  提交时间：2022/01/06 individual segmentation method  leaf area index  canopy cover  tree density  coefficient of variation of tree height