An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China

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

引用次数: 0

Abstract

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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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

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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来源期刊

GIScience & Remote Sensing 地学-遥感

CiteScore

11.20

自引率

9.00%

发文量

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.