区域森林生物量遥感信息模型构建研究  

A Study on Remote Sensing Information Model of Regional Forest Biomass

作　　者：程鹏飞[1] 王金亮[2] 徐申[2] 程峰[3] 王小花 

机构地区：[1]云南省一九八煤田地质勘探队,云南昆明650208 [2]云南师范大学旅游与地理科学学院,云南昆明650092 [3]中国科学院对地观测与数字地球科学中心,北京100094 [4]重庆市梁平县规划与地理信息中心,重庆405227

出　　处：《遥感技术与应用》2012年第5期722-727,共6页Remote Sensing Technology and Application

基　　金：国家自然科学基金项目(40861009)

摘　　要：森林是陆地生态系统中最大的碳汇,在调节全球碳平衡、减缓大气CO2等方面具有不可替代的作用。森林生物量是陆地生态系统碳循环过程中最主要的参数,准确估算森林生物量及森林的变动引起的生物量变化受到科学家的普遍关注,并成为碳循环科学研究中的焦点。以生态敏感区滇西北香格里拉县为研究区,在野外森林样方调查数据的支持下,综合3S技术、地理学、生态学、气象学等相关知识,筛选了9个植被指数、2波段灰度值、生长季降水、生长季积温、生长季总辐射量、海拔、坡度、坡向、坡位和土壤有机质含量等多个因子,组合成遥感综合因子层、地理综合因子层与水、光、热共同构成变量,建立了区域森林生物量估算模型,并进行了检验,模型的R、R2、aR2及F统计量分别为0.809、0.655、0.661、101.436;样地实测值与模型估测值建立线性回归方程常数项(a)和回归系数(b)分别为0.09和1.021;用22个野外实测样点生物量数据对估算模型进行独立性检验,平均估算精度达到76.43%。说明模型的估算精度总体稳定,基本满足生物量估算精度要求,可用于该区域的森林生物量估算研究。The forest is the largest carbon sink in terrestrial ecosystems. It has an irreplaceable role in adjusting the global carbon balance and slowing clown CO2. Forest biomass is the most important parameters in the terrestrial e- cosystem carbon cycle and becomes more and more universal concern by the scientists in forest biomass estimation and changes and the focus of carbon cycle research. Taking the ecologically sensitive areas in Northwest Yunnan Shangri-La County as a study area,in the support of survey data in the wild forest,combined with 3S technology, geography, ecology,meteorology and other related knowledge,the variable of 9 vegetation index,2-band gray data, growth season precipitation, growth season accumulated temperature, growth season total radiation, elevation, slope, aspect, slope position and soil organic matter content were selected, which combine the layer of remote sens- ing integrated factors and the layer of geographic comprehensive factor with water, light, heat into the variables, and then establish the regional forest biomass estimation model and be tested. The statistic of model R,R2 ,aR2 and F is 0. 809,0. 655,0. 661 and 101. 436. The linear regression equation constant （a） and regression coefficient （b） which established by sample measured data and model is 0.09,1. 021. The independence test of estimation model had done by 22 biomass data of field sample; the average estimation accuracy is 76.43 %. The result shows that the estimation accuracy of the model is generally stable,and basically meets the accuracy requirements of biomass estimation. It can be used to the study of estimating the forest biomass in this area.

关 键 词：生物量估算 遥感信息模型 香格里拉 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]