建模邻居协会衰变效应 通过无人机激光雷达和光学数据改进森林库存量估计
Zilong Qin1, Jinling Fang2, Na Jiang3
1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, China. zilongqin@whu.edu.cn.
Carbon balance and management
|December 23, 2025
概括
本研究引入了一种新的方法,通过结合邻居协会衰变 (NAD) 效应来估计森林库存量 (FSV). 这种基于NAD的模型显著提高了FSV估计的准确性,这对于评估森林碳捕获潜力至关重要.
科学领域:
- 林业林业 林业 林业 林业
- 遥感 遥感 遥感 遥感
- 地理空间分析是什么
背景情况:
- 森林库存量 (FSV) 是森林碳捕获潜力的关键指标.
- 现有的FSV估计方法往往忽略了空间邻近效应和距离衰减.
研究的目的:
- 开发和验证一种新的FSV估计方法,以解释邻居协会衰变 (NAD).
- 量化NAD效应并优化其集成到FSV建模中.
主要方法:
- 在FSV估计中开发了一个表达和量化NAD效应的框架.
- 设计了NAD模型,确定了最佳的社区大小,并优化了NAD策略.
- 在中国孟县利用无人机LiDAR和光学遥感数据进行FSV估计.
主要成果:
- 与传统基于像素的模型相比,基于NAD的FSV模型显著提高了估计准确性 (R2 = 0.750.96).
- 在孟县 (15.47242.82 m3/ha) 观察到FSV的高空间异质性.
- 该研究发现了森林碳捕获潜力显著.
结论:
- 基于NAD的建模方法有效地提高了森林库存量估计的准确性.
- 了解空间邻居衰变对于精确的森林资源评估至关重要.
- 这些发现支持改善森林管理和碳核算策略.
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