Aims accurate remote estimation of the fraction of absorbed photosynthetically active radiation(fAPAR)is essential for the light use efficiency(LUE)models.Currently,one challenge for the LUE models is lack of knowledg...Aims accurate remote estimation of the fraction of absorbed photosynthetically active radiation(fAPAR)is essential for the light use efficiency(LUE)models.Currently,one challenge for the LUE models is lack of knowledge about the relationship between fAPAR and the normalized difference vegetation index(NDVI).Few studies have tested this relationship against field measurements and evaluated the accuracy of the remote estimation method.this study aimed to reveal the empirical relationship between NDVI and fAPAR and to improve algorithms for remote estimation of fAPAR.Methods to investigate the method of remote estimation of fAPAR seasonal dynamics,the CASA(Carnegie-ames-stanford approach)model and spectral vegetation indices(VIs)were used for in situ measure-ments of spectral reflectance and fAPAR during the growing season of a maize canopy in Northeast China.Important Findingsthe results showed that the fAPAR increased rapidly with the day of year during the vegetative stage,it remained relatively stable at the stage of reproduction,and finally decreased slowly during the senescence stage.In addition,fAPAR green[fAPAR_(green)=fAPAR_(green) -fAPAR_(green) LAI_(max))]showed clearer seasonal trends than fAPAR.the NDVI,red-edge NDVI,wide dynamic range vegetation index,red-edge position(REP)and REP with sentinel-2 bands derived from hyperspectral remote sensing data were all significantly positively related to fAPAR green during the entire growing season.In a comparison of the predictive performance of VIs for the whole growing season,REP was the most appropriate spectral index,and can be recommended for monitoring seasonal dynamics of fAPAR in a maize canopy.展开更多
Among the many approaches for studying the net primary productivity (NPP), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and ...Among the many approaches for studying the net primary productivity (NPP), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and thermal infrared band) of NOAA-AVHRR, we can get the relative index and parameters, which can be used for estimating NPP of terrestrial vegetation. By means of remote sensing, the estimation of biomass and NPP is mainly based on the models of light energy utilization. In other words, the biomass and NPP can be calculated from the relation among NPP, absorbed photosynthetical active radiation (APAR) and the rate (epsilon) of transformation of APAR to organic matter, thus: NPP = ( FPAR x PAR) x [epsilon * x sigma (T) x sigma (E) x sigma (S) x (1 - Y-m) x (1 - Y-g)]. Based upon remote sensing ( RS) and geographic information system (GIS), the NPP of terrestrial vegetation in China in every ten days was calculated, and the annual NPP was integrated. The result showed that the total NPP of terrestrial vegetation in China was 6.13 x 10(9) t C . a(-1) in 1990 and the maximum NPP was 1 812.9 g C/m(2). According to this result, the spatio-temporal distribution of NPP was analyzed. Comparing to the statistical models, the RS model, using area object other than point one, can better reflect the distribution of NPP, and match the geographic distribution of vegetation in China.展开更多
Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functi...Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics. Methods： Here, we introduce the Global LAI database： a global dataset of field-based canopy structure measurements spanning tropical forests in four continents （Africa, Asia, Australia and the Americas）. We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences. Results： Using data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active （within protected areas） and passive measures （through topography）. Once protection and continent effects are accounted for, other anthropogenic measures （e.g. human population） do not improve the model. Conclusions： We conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.展开更多
Photosynthetically active radiation （PAR） is the energy source of plant photosyn thesis, and the diffuse component can enhance canopy light use efficiency, thereby increasing the carbon uptake. Therefore, diffuse PA...Photosynthetically active radiation （PAR） is the energy source of plant photosyn thesis, and the diffuse component can enhance canopy light use efficiency, thereby increasing the carbon uptake. Therefore, diffuse PAR is an important driving factor of ecosystem productivity models. In this study, we estimated the diffuse PAR of over 700 meteorological sites in China from 1981 to 2010 using an empirical model based on observational data from Chinese Ecosystem Research Network （CERN） and China Meteorology Administration. Then we derived the spatial data set of 10 km monthly diffuse PAR using ANUSPLIN software, and analyzed the spatiotemporal variation characteristics of diffuse PAR through GIS and trend analysis techniques. The results showed that： （1） The spatial patterns of annual average diffuse PAR during 1981-2010 are heterogeneous across China, lower in the northeast and higher in the west and south. The nationwide average value for 30 years ranges from 6.66 mol m-2 d-1 to 15.27 mol m-2 d-1, and the value in summer is the biggest while the value in winter is the smallest. （2） There is an evident increasing trend of annual diffuse PAR during recent 30 years, with the increasing amplitude at 0.03 mol m-2 d-l/10a. But a significant declining trend is shown in the first 10 years, and obvious anomalies can be seen in 1982, 1983, 1991 and 1992. And there is a downtrend in spring and an uptrend in all the other seasons. （3） The spatial distribution of temporal variation rates of diffuse PAR is inhomogeneous across the country, generally decreasing in the north and increasing in the south.展开更多
植被吸收光合有效辐射(Absorbed Photosynthetically Active Radiation,APAR)是植被进行光合作用中实际吸收的太阳辐射量,是植被净第一性生产力的重要指标,也是生态系统的功能模型、作物生长模型、净初级生产力模型、气候模型等的重要...植被吸收光合有效辐射(Absorbed Photosynthetically Active Radiation,APAR)是植被进行光合作用中实际吸收的太阳辐射量,是植被净第一性生产力的重要指标,也是生态系统的功能模型、作物生长模型、净初级生产力模型、气候模型等的重要参数。因此高空间分辨率和精确性的植被吸收光合有效辐射对于高精度的区域生产力及光能利用率的研究具有重要意义。对CASA(Carnegie-Ames-Stanford Approach)模型进行了改进,利用30m×30m的数字高程模型(Digital Elevation Model,DEM)数据直接计算太阳辐射,从而将其作为CASA模型的输入参数。结合多源遥感数据、气象数据,研究2015-2020年江汉平原APAR的时空分布及其影响因素。顾及江汉平原的土地利用分布特点,着重分析了江汉平原农田APAR的时空特性,研究结果较好的反映了江汉平原APAR分布。实验结果表明:(1)2015-2020年APAR年总值在3.42×10^(13)MJ-3.73×10^(13)MJ之间,总体空间分布与植被类型的分布情况相符;(2)农田月均APAR值在4月、7月高于其他月份,表现出“双峰”的特征;(3)在空间分布上,水田APAR表现出明显的纬度地带性,而旱地APAR正好相反,这可能源于种植结构重心转移;(4)通过借助地理探测器,着重考虑与植被生长相关的12个因子(包括≧10℃积温、年总日照时数、年均气温、年总降雨量、农田种植结构、年散射辐射、农田施肥、土壤类型、土壤质地(砂土、粉砂土、黏土))进行分析,结果表明这12个因素对APAR空间变异性都具有很明显的影响。对CASA的改进方法可以适用于大范围高空间精度的计算。展开更多
地球表面的瞬时光合有效辐射(Photosynthetically Active Radiation,PAR)和植被吸收的光合有效辐射(Absorbed Photosynthetically Active Radiation,APAR)是许多集中于生物圈和大气之间交换过程研究的关键参量。光合有效辐射吸收比例(Fr...地球表面的瞬时光合有效辐射(Photosynthetically Active Radiation,PAR)和植被吸收的光合有效辐射(Absorbed Photosynthetically Active Radiation,APAR)是许多集中于生物圈和大气之间交换过程研究的关键参量。光合有效辐射吸收比例(Fraction of Photosynthetically Active Radiation,FPAR)是APAR和PAR的比值,是许多气候模型及生产力模型的基本特征参量。因此,研究PAR/APAR/FPAR的时空变化规律,对准确估算草地NPP具有十分重要的作用。本文利用MODIS遥感影像和TOMS紫外波段反射率数据,在GIS和RS软件支持下,计算分析了内蒙古草地生长季的PAR/FPAR/APAR及其时空变化,并分析了气候因子对FPAR/APAR的影响。结果表明:内蒙古草地生长季平均PAR为1973.8MJ/m2,FPAR为0.275,APAR为516.64MJ/m2。内蒙古草地生长季的PAR/FPAR/PAR时空变化明显:FPAR及APAR空间上呈东北向西南地区递减的趋势,PAR与之相反。自生长季初期(4月份),随着时间的推移PAR/FPAR/APAR都开始增加,只是出现峰值的时间不同。内蒙古草地生长季不同草地类型的FPAR及APAR差异明显,在草地NPP估算及建模时应引起重视。展开更多
考虑到植被可见光-近红外的光谱吸收特征与光合有效辐射吸收率(fraction of absorbed photosynthetically active radiation,FAPAR)有很好的关联,综合"高光谱曲线特征吸收峰自动识别法"与"光谱吸收特征参量化法",...考虑到植被可见光-近红外的光谱吸收特征与光合有效辐射吸收率(fraction of absorbed photosynthetically active radiation,FAPAR)有很好的关联,综合"高光谱曲线特征吸收峰自动识别法"与"光谱吸收特征参量化法",提取对FAPAR敏感的高光谱吸收特征参数,借鉴可见光-近红外植被指数的数学形式,尝试用优化组合后的可见光-近红外光谱吸收特征参数替代光谱反射率,构建新型植被指数估算植被FAPAR,并利用2014年和2015年内蒙古自治区中部与东部地区天然草地典型群落冠层实测光谱数据进行FAPAR估算建模与验证。结果表明:新型植被指数"SAI-VI"不仅有效提高了单个光谱吸收特征参数在高、低覆盖区域估算FAPAR的精度,而且相比五种与FAPAR有较好相关性的具有不同作用类型的可见光-近红外植被指数,其与FAPAR值的相关性更高(存在最大相关系数=0.801),以其为变量的指数模型预测FAPAR精度更高且稳定性较好(建模与检验的判定系数均最高且超过0.75,标准误差与平均误差系数也相应最小)。研究表明:融入可见光-近红外高光谱吸收特征的新型植被指数"SAI-VI",强化了可见光波段与近红外波段光谱吸收特征的差别,相较单一光谱吸收特征参数,在降低土壤背景影响的同时增强了对FAPAR变化的敏感度。同时,"SAI-VI"有效综合了对植被FAPAR敏感的光谱吸收特征信息,相较原始光谱反射率,能表达植被光合有效辐射吸收特征的更多细节信息,可作为植被冠层FAPAR反演的新参数,一定程度上弥补当前植被指数法估算FAPAR的不足。展开更多
基金National Natural Science Foundation of China(41330531)the R&D Special Fund for Public Welfare Industry(Meteorology)Project(GYHY201106027)the State Key Development Program of Basic Research(2010CB951303).
文摘Aims accurate remote estimation of the fraction of absorbed photosynthetically active radiation(fAPAR)is essential for the light use efficiency(LUE)models.Currently,one challenge for the LUE models is lack of knowledge about the relationship between fAPAR and the normalized difference vegetation index(NDVI).Few studies have tested this relationship against field measurements and evaluated the accuracy of the remote estimation method.this study aimed to reveal the empirical relationship between NDVI and fAPAR and to improve algorithms for remote estimation of fAPAR.Methods to investigate the method of remote estimation of fAPAR seasonal dynamics,the CASA(Carnegie-ames-stanford approach)model and spectral vegetation indices(VIs)were used for in situ measure-ments of spectral reflectance and fAPAR during the growing season of a maize canopy in Northeast China.Important Findingsthe results showed that the fAPAR increased rapidly with the day of year during the vegetative stage,it remained relatively stable at the stage of reproduction,and finally decreased slowly during the senescence stage.In addition,fAPAR green[fAPAR_(green)=fAPAR_(green) -fAPAR_(green) LAI_(max))]showed clearer seasonal trends than fAPAR.the NDVI,red-edge NDVI,wide dynamic range vegetation index,red-edge position(REP)and REP with sentinel-2 bands derived from hyperspectral remote sensing data were all significantly positively related to fAPAR green during the entire growing season.In a comparison of the predictive performance of VIs for the whole growing season,REP was the most appropriate spectral index,and can be recommended for monitoring seasonal dynamics of fAPAR in a maize canopy.
文摘Among the many approaches for studying the net primary productivity (NPP), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and thermal infrared band) of NOAA-AVHRR, we can get the relative index and parameters, which can be used for estimating NPP of terrestrial vegetation. By means of remote sensing, the estimation of biomass and NPP is mainly based on the models of light energy utilization. In other words, the biomass and NPP can be calculated from the relation among NPP, absorbed photosynthetical active radiation (APAR) and the rate (epsilon) of transformation of APAR to organic matter, thus: NPP = ( FPAR x PAR) x [epsilon * x sigma (T) x sigma (E) x sigma (S) x (1 - Y-m) x (1 - Y-g)]. Based upon remote sensing ( RS) and geographic information system (GIS), the NPP of terrestrial vegetation in China in every ten days was calculated, and the annual NPP was integrated. The result showed that the total NPP of terrestrial vegetation in China was 6.13 x 10(9) t C . a(-1) in 1990 and the maximum NPP was 1 812.9 g C/m(2). According to this result, the spatio-temporal distribution of NPP was analyzed. Comparing to the statistical models, the RS model, using area object other than point one, can better reflect the distribution of NPP, and match the geographic distribution of vegetation in China.
基金supported by the‘Uncovering the variable roles of fire in savannah ecosystems’project,funded by Leverhulme Trust under grant IN-2014-022 and‘Resilience in East African Landscapes’project funded by European Commission Marie Curie Initial Training Network(FP7-PEOPLE-2013-ITN project number606879)funding from Australian Research Council,IUCN Sustain/African Wildlife Foundation and University of York Research Pump Priming Fund+1 种基金funding through the European Research Council ERC-2011-St G_20101109(project number 281986)and the British Ecological Society-Ecologists in Africa programmesupport through the‘Climate Change Impacts on Ecosystem Services and Food Security in Eastern Africa(CHIESA)’project(2011–2015),which was funded by the Ministry for Foreign Affairs of Finland,and coordinated by the International Centre of Insect Physiology and Ecology(icipe)in Nairobi,Kenya
文摘Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics. Methods： Here, we introduce the Global LAI database： a global dataset of field-based canopy structure measurements spanning tropical forests in four continents （Africa, Asia, Australia and the Americas）. We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences. Results： Using data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active （within protected areas） and passive measures （through topography）. Once protection and continent effects are accounted for, other anthropogenic measures （e.g. human population） do not improve the model. Conclusions： We conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.
基金Research on the key technology of effectiveness evaluation and standardized construction of National Nature Reserve,No.201209028"Strategic Priority Research Program–Climate Change:Carbon Budget and Relevant Issues"of the Chinese Academy of Sciences,No.XDA05050600Key Projects in the National Science&Technology Pillar Program during the Twelve Five-year Plan Period,No.2013BAC03B03
文摘Photosynthetically active radiation （PAR） is the energy source of plant photosyn thesis, and the diffuse component can enhance canopy light use efficiency, thereby increasing the carbon uptake. Therefore, diffuse PAR is an important driving factor of ecosystem productivity models. In this study, we estimated the diffuse PAR of over 700 meteorological sites in China from 1981 to 2010 using an empirical model based on observational data from Chinese Ecosystem Research Network （CERN） and China Meteorology Administration. Then we derived the spatial data set of 10 km monthly diffuse PAR using ANUSPLIN software, and analyzed the spatiotemporal variation characteristics of diffuse PAR through GIS and trend analysis techniques. The results showed that： （1） The spatial patterns of annual average diffuse PAR during 1981-2010 are heterogeneous across China, lower in the northeast and higher in the west and south. The nationwide average value for 30 years ranges from 6.66 mol m-2 d-1 to 15.27 mol m-2 d-1, and the value in summer is the biggest while the value in winter is the smallest. （2） There is an evident increasing trend of annual diffuse PAR during recent 30 years, with the increasing amplitude at 0.03 mol m-2 d-l/10a. But a significant declining trend is shown in the first 10 years, and obvious anomalies can be seen in 1982, 1983, 1991 and 1992. And there is a downtrend in spring and an uptrend in all the other seasons. （3） The spatial distribution of temporal variation rates of diffuse PAR is inhomogeneous across the country, generally decreasing in the north and increasing in the south.
文摘地球表面的瞬时光合有效辐射(Photosynthetically Active Radiation,PAR)和植被吸收的光合有效辐射(Absorbed Photosynthetically Active Radiation,APAR)是许多集中于生物圈和大气之间交换过程研究的关键参量。光合有效辐射吸收比例(Fraction of Photosynthetically Active Radiation,FPAR)是APAR和PAR的比值,是许多气候模型及生产力模型的基本特征参量。因此,研究PAR/APAR/FPAR的时空变化规律,对准确估算草地NPP具有十分重要的作用。本文利用MODIS遥感影像和TOMS紫外波段反射率数据,在GIS和RS软件支持下,计算分析了内蒙古草地生长季的PAR/FPAR/APAR及其时空变化,并分析了气候因子对FPAR/APAR的影响。结果表明:内蒙古草地生长季平均PAR为1973.8MJ/m2,FPAR为0.275,APAR为516.64MJ/m2。内蒙古草地生长季的PAR/FPAR/PAR时空变化明显:FPAR及APAR空间上呈东北向西南地区递减的趋势,PAR与之相反。自生长季初期(4月份),随着时间的推移PAR/FPAR/APAR都开始增加,只是出现峰值的时间不同。内蒙古草地生长季不同草地类型的FPAR及APAR差异明显,在草地NPP估算及建模时应引起重视。
文摘考虑到植被可见光-近红外的光谱吸收特征与光合有效辐射吸收率(fraction of absorbed photosynthetically active radiation,FAPAR)有很好的关联,综合"高光谱曲线特征吸收峰自动识别法"与"光谱吸收特征参量化法",提取对FAPAR敏感的高光谱吸收特征参数,借鉴可见光-近红外植被指数的数学形式,尝试用优化组合后的可见光-近红外光谱吸收特征参数替代光谱反射率,构建新型植被指数估算植被FAPAR,并利用2014年和2015年内蒙古自治区中部与东部地区天然草地典型群落冠层实测光谱数据进行FAPAR估算建模与验证。结果表明:新型植被指数"SAI-VI"不仅有效提高了单个光谱吸收特征参数在高、低覆盖区域估算FAPAR的精度,而且相比五种与FAPAR有较好相关性的具有不同作用类型的可见光-近红外植被指数,其与FAPAR值的相关性更高(存在最大相关系数=0.801),以其为变量的指数模型预测FAPAR精度更高且稳定性较好(建模与检验的判定系数均最高且超过0.75,标准误差与平均误差系数也相应最小)。研究表明:融入可见光-近红外高光谱吸收特征的新型植被指数"SAI-VI",强化了可见光波段与近红外波段光谱吸收特征的差别,相较单一光谱吸收特征参数,在降低土壤背景影响的同时增强了对FAPAR变化的敏感度。同时,"SAI-VI"有效综合了对植被FAPAR敏感的光谱吸收特征信息,相较原始光谱反射率,能表达植被光合有效辐射吸收特征的更多细节信息,可作为植被冠层FAPAR反演的新参数,一定程度上弥补当前植被指数法估算FAPAR的不足。
