[1]王书贤,张加龙*,鲍瑞,等. 香格里拉高山松地上生物量及遥感因子的时空变化特征研究[J].西北林学院学报,2023,38(5):43-48.[doi:10.3969/j.issn.1001-7461.2023.05.06]
　WANG Shu-xian,ZHANG Jia-long*,BAO Rui,et al. Temporal and Spatial Variation Characteristics of Above Ground Biomass of Pinus densata Forest and Remote Sensing Factors in Shangri-La[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2023,38(5):43-48.[doi:10.3969/j.issn.1001-7461.2023.05.06]
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 香格里拉高山松地上生物量及遥感因子的时空变化特征研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第38卷
期数:
2023年第5期
页码:
43-48
栏目:
出版日期:
2023-09-30

文章信息/Info

Title:
 Temporal and Spatial Variation Characteristics of Above Ground Biomass of Pinus densata Forest and Remote Sensing Factors in Shangri-La
文章编号:
1001-7461(2023)05-0043-06
作者:
 王书贤1; 2; 张加龙1*; 鲍瑞3; 韩东阳1; 廖易1
 （1.西南林业大学 林学院，云南 昆明 650224；2.云南省遥感中心，云南 昆明 650034；3.国家林业和草原局 西南调查规划院，云南 昆明 650031)
Author(s):
 WANG Shu-xian1; 2; ZHANG Jia-long1*; BAO Rui3; HAN Dong-yang1; LIAO Yi1
 （1.College of Forestry,Southwest Forestry University,Kunming 650224,Yunnan,China; 2.Yunnan Remote Sensing Center,Kunming 650034,Yunnan,China; 3.Southwest Investigation and Planning Institute of National Forestry and Grassland Administration,Kunming 650031,Yunnan,China）
关键词:
 ; 高山松; 生物量; 遥感因子
Keywords:
Pinus densata;  biomass;  remote sensing factor
分类号:
S791.24
DOI:
10.3969/j.issn.1001-7461.2023.05.06
文献标志码:
A
摘要:
 分析香格里拉市高山松单位面积地上生物量（AGB）的时空变化特征，为日后监测AGB空间变化和模拟预测提供理论依据。采用1987-2017年经过BSTS滤波算法处理的Landsat遥感影像和反演得到的高山松AGB数据，运用Moran’s I系数和半变异方差函数对7个时期的高山松AGB及遥感因子进行空间自相关性和空间异质性分析。结果表明：1）1987-1997年高山松AGB随分布面积的减小而减小，1997年后的高山松AGB并未随分布面积的增加而增加，而是呈减少趋势；2）1987-1992年高山松AGB在南北方向60 000 m范围内呈聚集状态，1997-2007年的高山松AGB整体呈破碎化状态，而2017年高山松AGB在全局25 000 m范围内呈聚集状态；3）1987-2012年的最优半变异函数模型为指数模型、2017年为球型模型，高山松AGB的结构比C0/(C0+C)都接近0，其中2017年最接近0，空间自相关较好；与生物量具有相似空间分异特征的遥感因子为NBR和B3/Albedo。分析表明，1992-1997年的高山松AGB空间分布主要受人为干扰，不具有整体性，空间分布呈破碎化状态；1987年和2002-2017年的高山松AGB主要受立地条件因素影响，空间分布呈聚集状态；遥感因子时空变化特征分析结果可为高山松AGB时空模拟和制图提供依据。
Abstract:
 The objective of this study was to provide theoretical basis for monitoring the spatial variation of AGB and simulation prediction in the future by analyzing the temporal and spatial variation characteristics of the aboveground biomass (AGB) per unit area of Pinus densata forest in Shangri-La City.Using the Landsat remote sensing images processed by the BSTS filtering algorithm from 1987 to 2017 and the AGB data obtained by inversion.The Moran’s I coefficient and the semivariogram function were used to analyze the spatial autocorrelation and spatial heterogeneity of the AGB and the remote sensing factors in 7 periods.The results showed that:1) from 1987 to 1992,the AGB of P.densata forest formed an aggregated state within a range of 60 000 m in the north-south direction.From 1997 to 2007,the AGB was in a state of fragmentation as a whole,and in 2017,the AGB gathered in a global range of 25 000 m.2) The optimal semivariogram model from 1987 to 2012 was an exponential type and a spherical one in 2017.The structure ratio C0/(C0+C) of AGB was close to 0,of which the ratio in 2017 was the closest to 0.The spatial autocorrelation was good.3) The remote sensing factors with similar spatial differentiation characteristics to biomass were NBR and B3/Albedo.It was concluded during 1992-1997,the spatial distribution of the AGB of P.densata was mainly affected by human interference,which was not integrated,and the spatial distribution was fragmented; the AGB in 1987 and 2002-2017 was mainly affected by site conditions,and the spatial distribution was clustered.The analysis results of the temporal and spatial variation characteristics of remote sensing factors can provide a basis for the temporal and spatial simulation and mapping of the AGB of P.densata.

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备注/Memo

备注/Memo:
 收稿日期：2022-03-12修回日期：2023-04-10
基金项目：国家自然科学基金（31860207）；2020 年云南省高层次人才培养支持计划 “青年拔尖人才”专项（81210468）；西南林业大学科研启动基金（111932） 。
第一作者：王书贤。研究方向:资源与环境遥感。E-mail：esther@swfu.edu.cn
*通信作者：张加龙，博士，教授。研究方向:林业遥感。E-mail：jialongzhang@swfu.edu.cn
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