基于Landsat影像的梭磨乡冷杉林地上碳储量估测及其时空动态
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摘要
森林碳储量研究对森林质量评价、林业资源科学管理及森林生态结构保护具有重要意义。以四川省马尔康县梭磨乡冷杉林为研究对象,以2010年森林资源调查实测数据和同年Landsat遥感影像数据为基础,采用逐步线性回归方法,构建2010年地面冷杉林地上碳储量和遥感因子的多元线性回归模型。然后,基于伪不变特征原理的相对辐射校正法计算2010年冷杉林地上碳储量估测模型与1995年、2000年、2005年和2015年四期影像数据的相关关系,分别估测了1995年、2000年、2005年、2010年和2015年研究区冷杉林地上碳储量,从而揭示出近20年来马尔康县梭磨乡冷杉林地上碳储量的时空动态变化特征。研究结果表明:从空间分布看,研究区冷杉林地上碳储量主要分布在贯穿全区东西方向且海拔3000—4000米的区域;从时间分布看,1995—2015年间,研究区冷杉林地上碳储量总量和碳密度呈持续上升趋势,森林碳储量结构处于良性发展阶段。该研究结果对高山峡谷地区森林碳储量的后续研究有一定参考价值。
Study on the forest carbon storage is significant for evaluating the quality of forest resources, scientific management of forest resources and protection of forest ecological structure. This paper took fir forest in Suomo Township of Sichuan province as an example. Based on forest resources survey data in 2010 and Landsat remote sensing data in the same year, using step wise linear regression, multiple linear regression model, we built a new estimation model especially for obtaining carbon storage above the fir forest ground in 2010. Then, based on the estimation model, we used Pseudo invariant feature principle to search the relationship between estimation model in 2010 with remote sensing image in other 4 years, and respectively estimated the carbon storage of fir forest land in 1995, 2000, 2005, 2010 and 2015 in study area, thus revealed the temporal and spatial variation characteristics above the fir forest ground in Barkam County Suomo Township. The results showed that from the perspective of spatial distribution, the carbon storage of fir forest land was mainly distributed in the east-west direction of the study area whose altitude was between 3000 and 4000 meters. From the perspective of temporal distribution, the total carbon storage and carbon density of the fir forest land increased continuously from 1995 to 2015, and the forest carbon storage structure was in the stage of benign development. The results could provide some reference for further study on forest carbon storage in alpine gorge region.
Study on the forest carbon storage is significant for evaluating the quality of forest resources, scientific management of forest resources and protection of forest ecological structure. This paper took fir forest in Suomo Township of Sichuan province as an example. Based on forest resources survey data in 2010 and Landsat remote sensing data in the same year, using step wise linear regression, multiple linear regression model, we built a new estimation model especially for obtaining carbon storage above the fir forest ground in 2010. Then, based on the estimation model, we used Pseudo invariant feature principle to search the relationship between estimation model in 2010 with remote sensing image in other 4 years, and respectively estimated the carbon storage of fir forest land in 1995, 2000, 2005, 2010 and 2015 in study area, thus revealed the temporal and spatial variation characteristics above the fir forest ground in Barkam County Suomo Township. The results showed that from the perspective of spatial distribution, the carbon storage of fir forest land was mainly distributed in the east-west direction of the study area whose altitude was between 3000 and 4000 meters. From the perspective of temporal distribution, the total carbon storage and carbon density of the fir forest land increased continuously from 1995 to 2015, and the forest carbon storage structure was in the stage of benign development. The results could provide some reference for further study on forest carbon storage in alpine gorge region.
引文
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[27]王新云,郭艺歌,何杰.基于HJ1B和ALOS/PALSAR数据的森林地上生物量遥感估算[J].生态学报,2016,36(13):2-13.
[2]ZIANIS D,MENCUCCINI M.Aboveground net primary productivity of a beech(Fagus moesiaca)forest:a case study of Naousa forest,northern Greece.[J].Tree Physiology,2005,25(6):713-722.
[3]BIRDSEY R,PREGITZER K,LUCIER A.Forest Carbon Management in the United States[J].Journal of Environmental Quality,2006,35(4):1461-1469.
[4]陶玉华.森林生态系统碳储量研究的意义及国内外研究进展[J].现代农业科技,2012,(9):205-212.
[5]韩爱惠.森林生物量及碳储量遥感监测方法研究[D].北京:北京林业大学,2009.
[6]谷勇,殷瑶,齐泮伦,等.森林碳储量研究进展[A].经济发展方式转变与自主创新-第十二届中国科学技术协会年会,2010.
[7]李雷达,方晰,李斌,等.湖南省2014年森林植被碳储量、碳密度及其区域空间分布格局[J].中南林业科技大学学报,2017,(01):69-77.
[8]杨洪晓,吴波,张金屯,等.森林生态系统的固碳功能和碳储量研究进展[J].北京师范大学学报(自然科学版),2005,41(2):172-177.
[9]SPENCER R D,GREEN M A,BLGGS P H.Integrating eucalypt forest inventory and GIS in Western Australia[J].Photogrammetric Engineering&Remote Sensing,1997,63(12):1345-1351.
[10]FRIEDL M A,DAVIS F W,MICHAELSEN J,et al.Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables:an analysis using a scene simulation model and data from FIFE[J].Remote Sensing,1995,54:233-246.
[11]陆新.保护森林资源改善生态环境[J].自然科学:全文版,2016(1):17.
[12]兰斯安,杜虎,曾馥平,等.不同林龄杉木人工林碳储量及其分配格局[J].应用生态学报,2016,27(04):1125-1134.
[13]郭焱,周旺明.长江上游天然林资源保护工程区森林植被碳储量研究[J].长江流域资源与环境,2015,24(1):222-228.
[14]FOODY G M,BOYD D S,CUTLER M E.Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions[J].Remote Sensing of Environment,2003,85(4):463-474.
[15]李海奎,雷渊才.中国森林植被生物量与碳储量评估[M].北京:中国林业出版社,2010.
[16]黄从德,张健.四川省及重庆地区森林植被碳储量动态[J].生态学报,2008,(3):966-975.
[17]施鹏程,彭道黎.三峡库区乔木林生物量和碳储量的估算[J].长江流域资源与环境,2015,24(6):1053-1059.
[18]李涛,李曼.多元线性回归与logistic回归分析的正确应用[J].临床荟萃,2009,24(15):6.
[19]刘常瑜,冯仲科,葛忠强,等.崂山林场林分生物量遥感反演估算研究[J].山东林业科技,2014(3):1-5.
[20]黄从德.四川森林生态系统碳储量及其空间分异特征[D].成都:四川农业大学,2008.
[21]徐新良,曹明奎,李克让.中国森林生态系统植被碳储量时空动态变化研究[J].地理科学进展,2007,26(6):1-10.
[22]李海奎,雷渊才,曾伟生.基于森林清查资料的中国森林植被碳储量[J].林业科学,2011,47(7):7-12.
[23]刘建泉,李进军,邸华.祁连山森林植被净生产量、碳储量和碳汇功能估算[J].西北林学院学报,2017,32(02):1-7.
[24]杨传金,杨帆,梅浩,等.区域森林碳储量估算方法概述[J].中南林业调查规划,2012,31(3):62-66.
[25]HAME T,SALLI A,ANDERSSON K,et al.Anew methodology for the estimation of biomass of coniferdominated boreal forest using NOAA AVHRR data[J].Int.J.Remote Sensing,1997,18(15):3211-3243.
[26]徐婷,曹林,佘光辉.基于Landsat 8 OLI的特征变量优化提取及森林生物量反演[J].遥感技术与应用,2015,(02):226-234.
[27]王新云,郭艺歌,何杰.基于HJ1B和ALOS/PALSAR数据的森林地上生物量遥感估算[J].生态学报,2016,36(13):2-13.