人民长江Issue(3)：17-22,6.DOI:10.16232/j.cnki.1001-4179.2016.03.005
基于多源遥感数据的森林生物量估算模型研究
Study on forest biomass estimation model based on multisource remote sensing data
摘要
Abstract
The development of forest above-ground biomass (AGB) estimation model by using multispectral HJ1B and multi-polarization L band ALOS/PALSAR remote sensing data is discussed, based on which, four estimation models were established by statistical regression method, including the model to estimate the biomass by using radar image ALOS/PALSAR backscattering coefficients and measured biomass, by fusing the fraction image from HJ1B spectral mixture analysis and ALOS/PALSAR data, by using the fraction image from HJ1B spectral mixture analysis and field-measured data and by NDVI index derived from HJ1B images and field-measured biomass. The estimated results of the four models were compared. It showed that the image fusion of the fraction image and ALOS/PALSAR data is quantitatively related with filed-measured biomass. A good fit could be found be-tween the estimated AGB and ground-measured biomass with a R2 ( Coefficient of Determination) and RMSE ( Root Mean-Square Error) of 0. 60 and 10. 45 t/hm2 , respectively and its estimated accuracy is superior to that of other models. Integrating the optical and microwave sensing remote images can effectively improve the accuracy of biomass estimation, but not all fused im-ages can significantly improve the accuracy. Consequently, it demonstrated a good application potential for monitoring vegetation ecosystem by the use of radar image and spectral mixture analysis of optical image.关键词
图像融合/HJ1B/ALOS/PALSAR/地上生物量/遥感估算Key words
image fusion/HJ1B/ALOS/PALSAR/above-ground biomass/remote sensing estimation分类
信息技术与安全科学引用本文复制引用
郭艺歌,王新云,何杰,杜灵通..基于多源遥感数据的森林生物量估算模型研究[J].人民长江,2016,(3):17-22,6.基金项目
宁夏自然科学基金资助项目(NZ12146) （NZ12146）
