首页|基于局部回归模型的森林生物量动态变化分析

基于局部回归模型的森林生物量动态变化分析

扫码查看
原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
基于丰林县地区4期Landsat影像和对应气象站点数据,结合该地区248块固定样地数据,利用全局回归模型(多元线性模型)和2种局部回归模型(地理加权回归模型、时空地理加权回归模型)建立研究区乔木地上生物量和遥感因子之间的关系,选出最优模型来研究丰林县乔木地上生物量时空变化.结果表明:根据3种模型的模拟结果数据与实测值的分析对比可以发现,局部回归模型的拟合效果要优于全局模型,加入时间特征的时空地理加权回归模型的拟合效果最好,模型评价指标与地理加权回归模型相比更为理想.统计得到研究区4个时期内总的乔木地上生物量分别为1.63 × 107、2.05 × 107、2.32 × 107、3.37 × 107 t,4个时期的平均乔木地上生物量分别为54.82、68.98、77.87、113.46t/hm2,乔木地上生物量呈现出逐期增加的趋势.利用遥感因子估测丰林地区的地上生物量,为未来该地区生物量分布的估计提供了依据.
Analysis of Forest Biomass Dynamics Based on Local Regression Model
This study based on the 4-period Landsat remote sensing images and the meteorological station data in Fenglin County,the global regression model(multiple linear model)and 2 local regression models(geo-graphically weighted regression model and geographically and time weighted regression model)were used to es-tablish the relationship between above-ground biomass of trees and remote sensing factors in the study area.The optimal model was selected to study the spatial and temporal variation of above-ground biomass in Fenglin County.The results showed that the simulation results of the 3 models were better than the global model,and the geographically temporal weighted regression model with the addition of temporal characteristics had the best fit-ting effect,and the model evaluation indexes were better compared with the geo-weighted regression model.The total above-ground biomass of trees in the study area was 1.63 x 107,2.05 x 107,2.32 x 107,3.37 x i07 t.The average above-ground biomass of trees in the 4 periods was 54.82,68.98,77.87,113.46 t/hm2.The total above-ground biomass of trees in the study area showed a trend of increasing from period to period.The use of re-mote sensing factors to estimate the above-ground biomass in the rich forest area provides a basis for estimating the future biomass distribution in the area.

geographically and time weighted regression modelabove ground biomassspatiotemporal dy-namicsremote sensing estimation

卢士欣、贾炜玮、孙毓蔓、张小勇、吴思敏、肖锐

展开 >

东北林业大学林学院,森林生态系统可持续经营教育部重点实验室,黑龙江哈尔滨 150040

黑龙江省林业科学研究所,黑龙江哈尔滨 150040

时空地理加权回归模型 地上生物量 时空动态变化 遥感估算

国家重点研发计划项目中央高校基本科研业务费专项资金项目中央高校基本科研业务费专项资金项目

2022YFD2201003-022572019CP082572022DT03

2024

10.11929/j.swfu.202212025

西南林业大学学报
西南林业大学

西南林业大学学报

CSTPCD北大核心
影响因子：0.773
ISSN：2095-1914
年,卷(期)：2024.44(5)
  • 6