西南林业大学学报2024，Vol.44Issue(5)：148-156,9.DOI:10.11929/j.swfu.202212025
基于局部回归模型的森林生物量动态变化分析
Analysis of Forest Biomass Dynamics Based on Local Regression Model
摘要
Abstract
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.关键词
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Key words
geographically and time weighted regression model/above ground biomass/spatiotemporal dy-namics/remote sensing estimation分类
农业科技引用本文复制引用
卢士欣,贾炜玮,孙毓蔓,张小勇,吴思敏,肖锐..基于局部回归模型的森林生物量动态变化分析[J].西南林业大学学报,2024,44(5):148-156,9.基金项目
国家重点研发计划项目(2022YFD2201003-02)资助 （2022YFD2201003-02）
中央高校基本科研业务费专项资金项目(2572019CP08)资助 （2572019CP08）
中央高校基本科研业务费专项资金项目(2572022DT03)资助. （2572022DT03）
