摘要
植被光合有效辐射吸收比例(FPAR)是湿地生态系统碳收支和气候变化的关键参量,直接反映湿地植被生长发育状况。基于植被指数的经验统计方法简单高效,被广泛运用于草原、森林及作物等植被FPAR的模拟,却较少用于湿地,缺乏不同植被指数对湿地FPAR估算适应性的系统研究。研究对比了14种常见的植被指数,选出最优植被指数用于反演若尔盖高原湿地生长季FPAR。结果表明:常见的植被指数中,MSAVI指数动态考虑了土壤信息,能较好地适应湿地植被FPAR的估算,误差和R~2均优于其他植被指数。若尔盖高原湿地生长季FPAR取值在0.22—0.80之间,整体分布较为均匀,泥炭湿地、湿草甸及沼泽湿地平均FPAR分别为0.46、0.63和0.58;生长季期间若尔盖高原不同类型湿地FPAR随时间呈现先增加后降低趋势。
The Fraction of absorbed Photosynthetically Active Radiation(FPAR)is a key parameter for carbon balance and climate change in wetland ecosystems,which directly reflects the growth and development of wetland vegetation.The empirical statistical method based on vegetation indexes is simple and efficient,and which has been widely used in the simulation of FPAR of grassland,forest and crop vegetation,but it is rarely used in wetlands.There is a lack of systematic research on the adaptability of different vegetation indexes to wetland FPAR estimation.In this paper,14 common vegetation indexes are compared,and the optimal vegetation index is selected to invert the FPAR of the wetland in the Zoige Plateau during the growing season.The results indicate that the MSAVI index dynamically considers soil information,and can better adapt to the estimation of wetland vegetation FPAR among the common vegetation indexes,and its error and R2are better than other vegetation indexes.The FPAR value of the Zoige Plateau wetland in the growing season is between 0.22 and 0.8,and the overall distribution is relatively uniform.The average FPAR of peat wetland,wet meadow and marsh wetland are 0.46,0.63 and 0.58 respectively.During the growing season,the FPAR of different types of wetlands on the Zoige Plateau showed a trend of first increasing and then decreasing with time.
作者
袁艺溶
王继燕
杨嘉葳
熊俊楠
Yuan Yirong;Wang Jiyan;Yang Jiawei;Xiong Junnan(School of Civil Engineering and Geomatics,Southwest Petroleum University,Surveying and Mapping Remote Sensing Geographic Information Disaster Prevention Emergency Research Center,Chengdu 610500,China)
出处
《遥感技术与应用》
CSCD
北大核心
2022年第5期1267-1276,共10页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(41701428)
四川省应用基础研究项目(2022NSFSC1179)
西南石油大学科研“启航计划”项目(2017QHZ026)
西南石油大学测绘遥感青年科技创新团队(2017CXTD09)联合资助
