北京林业大学学报2016，Vol.38Issue(3)：64-72,9.DOI:10.13332/j.1000-1522.20150209
基于多源数据的根河实验区生物量反演研究
Retrieval of forest above-ground biomass using multi-source data in Genhe, Inner Mongolia
摘要
Abstract
Forest is an important component of terrestrial ecosystems;therefore, it is necessary to estimate the forest above-ground biomass ( AGB) accurately in order to reduce the uncertainty of the carbon stock in forest ecosystem. We estimated forest AGB of the Genhe forest reserve which is located in Inner Mongolia using Landsat 8 OLI image, P-band PolSAR image and ASTER GDEM product based on the multiple linear stepwise regression model and k-nearest neighbors ( k-NN ) model. In particular, the Random Forest ( RF) was applied to select the features for constructing the optimized k-NN. The results estimated by single-sensor and multi-sensor data were compared by the accuracy indicators of R2 and RMSE, aiming to understand the effects of data source on the estimation of forest AGB. Then regional forest AGB over the Genhe forest reserve was estimated by the optimal method. Validated against the field forest measurement, the estimation of forest AGB obtained from multi-sensor outperformed those obtained from single-sensor based on the multiple linear stepwise regression model and k-nearest neighbors ( k-NN ) model;the estimation of forest AGB obtained from k-NN (R2 =0. 65, RMSE=17. 49 t/ha) agreed better with the field forest measurement than that obtained from the multiple linear stepwise regression model (R2 =0. 36, RMSE=22. 08 t/ha) using multi-sensor data. The ability of estimating forest AGB using remote-sensing-based method was improved attributed to the integration of the advantages of multi sensor;The k-NN model is a more appropriate method to estimate the forest AGB over regional area than the multiple linear stepwise regression model, because the k-NN model focuses on the nonlinear dependence between forest parameters and spectral values, and it can avoid the problem of over learning and sample imbalances.关键词
森林地上生物量/多元线性逐步回归/k-最近邻/单传感器遥感数据/多传感器遥感数据Key words
forest above-ground biomass ( AGB )/multiple linear stepwise regression/k-NN/single-sensor data/multi-sensor data分类
农业科技引用本文复制引用
李春梅,张王菲,李增元,陈尔学,田昕..基于多源数据的根河实验区生物量反演研究[J].北京林业大学学报,2016,38(3):64-72,9.基金项目
中央级公益性科研院所基本科研业务费专项(IFRIT201302)、“973”国家重点基础研究发展计划项目(2013CB733404)、国家青年自然科学基金项目(41101379)。 （IFRIT201302）
