当前位置：
X-MOL 学术
›
GISci. Remote Sens.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China
GIScience & Remote Sensing ( IF 6.7 ) Pub Date : 2023-11-10 , DOI: 10.1080/15481603.2023.2271246 Ye Ma 1, 2 , Zhen Zhen 1, 3 , Fengri Li 1 , Fujuan Feng 2, 4 , Yinghui Zhao 1, 2
GIScience & Remote Sensing ( IF 6.7 ) Pub Date : 2023-11-10 , DOI: 10.1080/15481603.2023.2271246 Ye Ma 1, 2 , Zhen Zhen 1, 3 , Fengri Li 1 , Fujuan Feng 2, 4 , Yinghui Zhao 1, 2
Affiliation
Large-scale forest composition mapping and change monitoring are essential for regional and national forest resource management, monitoring, and carbon stock assessment. However, the existing large...
更新日期：2023-11-10
京公网安备 11010802027423号