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基于ALOS PALSAR雷达影像的人工林蓄积量估算——以塞罕坝机械林场华北落叶松人工林为例

黄丽艳1,2,3,闫巧玲1,2**,高添1,2,朱教君1,2   

  1. 1中国科学院清原森林生态系统观测研究站, 沈阳 110016;  2中国科学院沈阳应用生态研究所森林与土壤国家重点实验室, 沈阳 110164;  3中国科学院大学, 北京 100049)
  • 出版日期:2015-09-10 发布日期:2015-09-10

Estimation on stock volume of  plantation forests using ALOS PALSAR images:  A case study of Larix principisrupprechtii plantations in Saihanba Forest Farm.

HUANG Li-yan1,2,3, YAN Qiao-ling1,2**, GAO Tian1,2, ZHU Jiao-jun1,2   

  1. (1Qingyuan Forest CERN, Chinese Academy of Sciences, Shenyang 110016, China; 2State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China; 3University of Chinese Academy of Sciences, Beijing 100049, China)
  • Online:2015-09-10 Published:2015-09-10

摘要:

基于遥感影像精确估算区域人工林蓄积量对于人工林的管理具有重要意义。本研究以北半球面积最大的华北落叶松(Larix principisrupprechtii)人工林林场——塞罕坝机械林场为研究区,采用逐步回归方法分别建立了华北落叶松人工林地面实测蓄积量与L波段ALOS PALSAR雷达数据、Landsat-8 OLI数据、以及共用ALOS PALSAR数据与Landsat8 OLI数据之间的不同模型,提出了一种基于雷达影像准确估算人工林蓄积量的方法。通过模型精度验证,找到落叶松人工林蓄积量估算最佳模型,并据此获得研究区不同林龄华北落叶松人工林蓄积量空间分布。结果表明:在建立的4个回归模型中,ALOS PALSAR雷达数据HV极化模式归一化后向散射系数与华北落叶松人工林蓄积量指数形式的回归模型预测精度最高(R2=0.67,相对RMSE=26.78%,P<0.01);据此模型估算获得研究区2010年华北落叶松人工林总蓄积量为4.7×106 m3及其相应的空间分布图;当单位蓄积量达到250~300 m3·hm-2时,ALOS PALSAR雷达数据HV极化模式归一化后向散射系数对蓄积量的变化不敏感,达到了饱和;林龄<20 a、20~30 a、30~40 a和>40 a的华北落叶松人工林单位蓄积量分别为78、97、136和127 m3·hm-2。本研究提出了一种基于雷达影像准确估算人工林蓄积量的方法。

 

关键词: 黄土丘陵区, 土壤水分, 液流通量, 辽东栎, 边材面积

Abstract: Accurately estimating stock volume of plantation forests based on remote sensing images is important for regional forest management. In this study, stepwise multiple regression models were developed to describe the relationships between different remote sensing datasets \[Advanced Land Observing Satellite (ALOS) Phased Array Lband SAR (PALSAR) normalized backscatter data, Landsat-8 Operational Land Imager (OLI) data, Lband ALOS PALSAR data and Landsat-8 OLI data\] and fieldbased stock volume in a Larix principisrupprechtii plantation forest landscape (Saihanba Forest Farm) in North China, and an approach to estimating stock volume of plantation forests was provided in this study. The regression models were assessed based on the reserved samples and the optimal model was selected to estimate the distribution of stock volume of larch plantation. Our results showed that the exponential model regressed by HV normalized backscatter of PALSAR had the highest estimation accuracy (R2=0.67, the relative RMSE=26.78%, P<0.01), and the total stock volume was estimated to be 4.7×106 m3 by using this model. A saturation effect of HV normalized backscatter was observed when the stock volume was greater than 250-300 m3·hm-2. The stock volume of larch plantation forests increased with stand ages; the stock volumes were 78, 97, 136 and 127 m3·hm-2 for <20, 20-30, 30-40 and >40 years old stands, respectively.

Key words: sap flux, Quercus liaotungensis, sapwood area, loess hilly region, soil moisture