基于无人机影像的北部湾典型岛群红树林生态系统净初级生产力估算
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摘要
提出以无人机季节航拍影像为数据源,采用ENVI5.3软件中的CART方法对广西北部湾的典型岛群红树林景观类型进行解译,借助于Python语言实现CASA模型并将其引人到对岛群红树林生态系统的研究中,得出了不同海岛和红树林生态系统净初级生产力(NPP)的空间分布特征。结果表明:1)可见光波段差异性植被指数(VDVI)可以很好地区分海岛及红树林植被等典型地物,可应用在岛群红树林生态系统NPP的估算上;2)研究区NPP的总量为127.09 t·C/a,NPP的年均碳密度值介于0～1 437.12 g·C/m~2,年均碳密度为399.85 g·C/m~2。红树林生态系统的NPP值较高,而海岛生态系统的NPP值较低;3)季节尺度上NPP碳密度的大小与年内太阳辐射有直接的关系,夏季的NPP碳密度最大,冬季最小;4)白骨壤的单位面积NPP最大,为1 123.09 g·C/m~2,而桐花树最小,为649.65 g·C/m~2。红树林生态系统NPP平均碳密度低于实测样地和深圳福田红树林计算结果,这与不同红树林群落的植被光谱特征有关。
The net primary productivity(NPP)of vegetation is an important component of the carbon cycle and carbon budget balance in global ecosystems.Its accurate assessment depends on high-resolution satellite data.Previous studies have mostly estimated NPP using remote sensing data from moderate resolution imaging spectroradiometers(250-8000 m)and thematic mappers(30 m).Due to the limitations and influences of spatial resolution and weather factors in the Beibu Gulf,it is difficult to accurately assess the NPP of mangrove and archipelago ecosystems.This study is the first to use aerial images from unmanned aerial vehicles(UAV)as a data source and to use the CART method in ENVI5.3 to interpret the landscapes of mangrove and archipelago ecosystems.Using python language,the CASA model was implemented and introduced in our study to obtain spatial NPP distribution characteristics in different islands and mangrove ecosystems.We found that:1)The VDVI index ranged from-1 to 1 and its vegetation index form was similar to the normalized differential vegetation index(NDVI).The threshold value for vegetation and non-vegetation segmentation was 0,which should be selected as the input parameter for the vegetation index in the CASA model.2)The NPP carbon density in the study area ranged from 0 to 1437.12 g·C/m~2,with an average value of 399.85 g·C/m~2.NPP spatial distribution was divided by the mangrove ecosystem in the north and Guixian island in the south.The NPP of the mangrove ecosystem in the north was higher than that of the south,3)The seasonal order of NPP carbon density was as follows:summer(191.35 g·C/m~2)>autumn(116.55 g·C/m~2)>spring(62.98 g·C/m~2)>winter(28.94 g·C/m2).The percentage of the average annual NPP for each season was 47.86%,29.15%,15.75%,and 7.24%,respectively.4)The maximum carbon density per unit area of mangrove ecosystem in the study area was 545.56 g·C·m~2,followed by Leeward Pier Island(535.90 g·C/m2),whilst Guixian Island was the lowest with a value of413.54 g·C·m2.The average NPP carbon density in typical mangrove and archipelago ecosystems estimated by this method was similar to the national average,lower than that of coastal provinces on the same latitude,but higher than that of provinces such as Hunan and Yunnan.The results of this study provide a reference and basis for further small-scale studies of NPP and its rapid estimation and also provide a new international research perspective.In the future,the Li-6400 XT portable photosynthesis measurement system could be used to determine the maximum light use efficiency of different vegetation types to examine the NPP of mangroves in island groups and accurately assess the model.At the same time,high resolution satellite data and UAV data could be used to combine spatial and temporal data,thus improving both the spatial resolution and range of the vegetation index.
The net primary productivity(NPP)of vegetation is an important component of the carbon cycle and carbon budget balance in global ecosystems.Its accurate assessment depends on high-resolution satellite data.Previous studies have mostly estimated NPP using remote sensing data from moderate resolution imaging spectroradiometers(250-8000 m)and thematic mappers(30 m).Due to the limitations and influences of spatial resolution and weather factors in the Beibu Gulf,it is difficult to accurately assess the NPP of mangrove and archipelago ecosystems.This study is the first to use aerial images from unmanned aerial vehicles(UAV)as a data source and to use the CART method in ENVI5.3 to interpret the landscapes of mangrove and archipelago ecosystems.Using python language,the CASA model was implemented and introduced in our study to obtain spatial NPP distribution characteristics in different islands and mangrove ecosystems.We found that:1)The VDVI index ranged from-1 to 1 and its vegetation index form was similar to the normalized differential vegetation index(NDVI).The threshold value for vegetation and non-vegetation segmentation was 0,which should be selected as the input parameter for the vegetation index in the CASA model.2)The NPP carbon density in the study area ranged from 0 to 1437.12 g·C/m~2,with an average value of 399.85 g·C/m~2.NPP spatial distribution was divided by the mangrove ecosystem in the north and Guixian island in the south.The NPP of the mangrove ecosystem in the north was higher than that of the south,3)The seasonal order of NPP carbon density was as follows:summer(191.35 g·C/m~2)>autumn(116.55 g·C/m~2)>spring(62.98 g·C/m~2)>winter(28.94 g·C/m2).The percentage of the average annual NPP for each season was 47.86%,29.15%,15.75%,and 7.24%,respectively.4)The maximum carbon density per unit area of mangrove ecosystem in the study area was 545.56 g·C·m~2,followed by Leeward Pier Island(535.90 g·C/m2),whilst Guixian Island was the lowest with a value of413.54 g·C·m2.The average NPP carbon density in typical mangrove and archipelago ecosystems estimated by this method was similar to the national average,lower than that of coastal provinces on the same latitude,but higher than that of provinces such as Hunan and Yunnan.The results of this study provide a reference and basis for further small-scale studies of NPP and its rapid estimation and also provide a new international research perspective.In the future,the Li-6400 XT portable photosynthesis measurement system could be used to determine the maximum light use efficiency of different vegetation types to examine the NPP of mangroves in island groups and accurately assess the model.At the same time,high resolution satellite data and UAV data could be used to combine spatial and temporal data,thus improving both the spatial resolution and range of the vegetation index.
引文
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池源,石洪华,王晓丽,李捷,丰爱平.2015.庙岛群岛南五岛生态系统净初级生产力空间分布及其影响因子.生态学报,35(24):8094-8106.[Chi Yuan,Shi Honghua,Wang Xiaoli,Li Jie and Feng Aiping 2015.The Spatial Distribution and Impact Factors of Net Primary Productivity in The Island Ecosystem of Five Southern Islands of Miaodao Archipelago.Acta Ecologica Sinica,35(24):8094-8106.]
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池源,石洪华,王晓丽,李捷,丰爱平.2015.庙岛群岛南五岛生态系统净初级生产力空间分布及其影响因子.生态学报,35(24):8094-8106.[Chi Yuan,Shi Honghua,Wang Xiaoli,Li Jie and Feng Aiping 2015.The Spatial Distribution and Impact Factors of Net Primary Productivity in The Island Ecosystem of Five Southern Islands of Miaodao Archipelago.Acta Ecologica Sinica,35(24):8094-8106.]
Field C B,Randerson J T and Malmstrom C M.1995.Global Netprimary Production-Combining Ecology and Remote Sensing.Remote Sensing of Enviro,nment,51(1):74-88.
Groot R S D,Wilson M A and Boumans R M J.2002.A Typology for the Classification,Description and Valuation of Ecosystem Function,Goods and Services.Ecological Economics,41(3):393-408.
何勇,董文杰,季劲均,丹利.2005.基于AVIM的中国陆地生态系统净初级生产力模拟.地球科学进展,20(3):345-349.[He Yong,Dong Wenjie,Ji Jinjun and Dan Li.2005.The Net Primary Production Simulation of Terrestrial Ecosystems in China by AVIM.Advances in Earth Science,20(3):345-349.]
江洪,汪小钦,吴波,陈芸芝.2010.地形调节植被指数构建及在植被覆盖度遥感监测中的应用.福州大学学报(自然科学版),38(4):527-532.[Jiang Hong,Wang Xiaoqin,Wu Bo and Chen Yunzhi.2010.A Topography-Adjusted Vegetation Index(TAVI)and Its Application in Vegetation Fraction Monitoring.Journal of Beijing Forestry University,38(4):527-532.]
柯金虎,朴世龙,方精云.2003.长江流域植被净第一性生产力及其时空格局研究.植物生态学报,27(6):764-770.[Ke Jinhu,Piao Shilong and Fang Jingyun.2003.NPP and Its Spatio-temporal Patterns in the Yangtze River Watershed.Acta Phytoecologica Sinica,27(6):764-770.]
柯丽娜,王权明,宫国伟.2011.海岛可持续发展理论及其评价研究.资源科学,33(7):1304-1309.[Ke Lina,Wang Quanming and Gong Guowei.2017.Evaluation of Island Sustainable Development and Its Applications.Resources Science,33(7):1304-1309.]
Li Jia,Cui Yaoping,Liu Jiyuan,Shi Wenjiao and Qin Yaochen.2013.Estimation and Analysis of Net Primary Productivity by Integrating MODIS Remote Sensing Data with A Li:ght Use Efficiency Model.Ecological Modelling,252:3-10.
罗艳,王春林.2009.基于MODIS NDVI的广东省陆地生态系统净初级生产力估算.生态环境学报,18(4):1467-1471.[Luo Yan and Wang Chunlin.2009.Valuation of the Net Primary Production of Terrestrial Ecosystems in Guangdong Province Based on Remote Sensing.Ecology and Environment,18(4):1467-1471.]
Melillo J M,Mcguire A D,Kicklighter D W,Moore B,Vorosmarty C J and Schloss A L.1993.Global Climate Change and Terrestrial Net Primary Production.Nature,363(6426):234-240.
Prince S D and Goward S N.1995.Global Primary Production:A Remote Sensing Approach.Journal of Biogeography,22(4/5):815-835.
潘竟虎,文岩.2015.中国西北干旱区植被碳汇估算及其时空格局.生态学报,35(23):7718-7728.[Pan Jinghu and Wen Yan.2015.Estimation and Spatial-Temporal Characteristics of Carbon Sink in the Arid Region of Northwest China.Acta Ecologica Sinica,35(23):7718-7728.]
潘耀忠,李晓兵,何春阳.2000.中国土地覆盖综合分类研究——基于NOAA/AVHRR和Holdridge PE.第四纪研究,20(3):270-281.[Pan Yaozhong,Li Xiaobing and He Chunyang.2000.Research on Comprehensive Land Cover Classification in China:Based on Noaa/Avhrr and Holdridge PE Index.Quaternaryences,20(3):270-281.]
彭聪姣,钱家炜,郭旭东,赵何伟,胡娜胥,杨琼,陈长平,陈鹭真.2016.深圳福田红树林植被碳储量和净初级生产力.应用生态学报,27(7):2059-2065.[Peng Congjiao,Qian Jiawei,Guo Xudong,Zhao Hewei,Hu Naxu,Yang Qiong,Chen Changping and Chen Luzhen.2016.Vegetation Carbon Stocks and Net Primary Productivity of The Mangrove Forests in Shenzhen,China.Chinese Journal of Applied Ecology,27(7):2059-2065.]
Ruimy A and Kergoat L Bondeau.2010.Comparing Global Models of Terrestrial Net Primary Productivity(NPP):Analysis Of Differences in Light Absorption and Light-Use Efficiency.Global Change Biology,5(S1):56-64.
Running S W.2012.A Measurable Planetary Boundary for the Biosphere.Science,337(6101):1458-1459.
Running S W,Thornton P E,Nemani R and Glassy J.2000.Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System.Methods in Ecosystem Science,44-57.DOI:10.1007/978-1-4612-1224-9_4.
孙红雨,王长耀,牛铮,布和敖斯尔,李兵.1998.中国地表植被覆盖变化及其与气候因子关系——基于NOAA时间序列数据分析.遥感学报,2(3):204-210.[Sun Hongyu,Wang Changyao,Niu Zheng,Bukhosor and Li Bing.1998.Analysis of the Vegetation Cover Change and the Relationship between NDVI and Environmental Factors by Using NOAA Time Series Data.Journal of Remote Sensing,2(3):204-210.]
Torres-Sanchez J,Pena J M,De Castro A I and Lopez-Granados F.2014.Multi-temporal Mapping of the Vegetation Fraction in Early-Season Wheat Fields Using Images from UAV.Computers and Electronics in Agriculture,103:104-113.
陶波,李克让,邵雪梅,曹明奎.2003.中国陆地净初级生产力时空特征模拟.地理学报,58(3):372-380.[Tao Bo,Li Kerang,Shao Xuemei and Cao Mingkui.2003.Temporal and Spatial Pattern of Net Primary Production of Terrestrial Ecosystems in China.Acta Geographica Sinica,58(3):372-380.]
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