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用于大规模森林成分有效监测的创新型轻量级1D-CNN模型——以黑龙江省为例

IF 6 2区 地球科学 Q1 GEOGRAPHY, PHYSICAL
GIScience & Remote Sensing Pub Date : 2023-11-10 DOI:10.1080/15481603.2023.2271246
Ye Ma, Zhen Zhen, Fengri Li, Fujuan Feng, Yinghui Zhao
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引用次数: 0

摘要

大尺度森林组成制图和变化监测对于区域和国家森林资源管理、监测和碳储量评估至关重要。然而，现有的大型……
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An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China
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...
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来源期刊
GIScience & Remote Sensing
GIScience & Remote Sensing 地学-遥感
CiteScore
11.20
自引率
9.00%
发文量
84
审稿时长
6 months
期刊介绍： GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.
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