基于MODIS GPP数据产品的辽宁省碳源/汇空间格局分布研究

陆地生态系统的碳汇功能是生态系统服务功能的重要方面,在减缓气候变化中起着重要作用,准确地评估陆地生态系统碳源/汇时空变化是有效预测气候变化的重要基础。基于碳源/汇形成过程中各分量间的相互关系,结合MODIS GPP数据产品和区域统计年鉴数据,对2000~2014年辽宁省陆地碳源/汇的强度及空间格局分布进行定量化评估。结果表明：①辽宁省陆地碳源/汇呈现东部高、西部低的变化趋势,东部呈现显著的碳吸收功能,碳吸收强度超过250 gC m^-2 a^-1,但在辽宁中部、西部及北部地区则出现明显的碳排放。②沈阳的年均碳排放量（1.43 TgC a^-1）约占辽宁省各地市净碳排放总量（4.56 TgC a^-1）的三分之一,是全省碳排放的主体。③沈阳陆地生态系统总体表现为碳源,城区碳排放强度相对较弱,仅为26 gC m^-2 a^-1,近似表现为碳中性。本文基于碳源/汇形成过程定量分析辽宁陆地碳源/汇强度及其空间分布规律,为今后其他区域碳源/汇的模拟提供理论依据和方法借鉴。     

中国温带地区植被物候期时空变化特征及对总初级生产力的影响

陆地表面物候(Land Surface Phenology,LSP)被定义为陆地表面植被的生命周期事件在区域或全球尺度上的各季节时间,对于中国温带地区的植被物候,已有研究大多仅针对某一地区的单一植被类型,对长时间、大尺度的陆表物候时空变化的研究较为少见,植被物候对总初级生产力(Gross Primary Productivity,GPP)的影响也有待明确。采用2001～2014年中等分辨率成像光谱仪MODIS的MCD12Q2数据以及MOD17A3 GPP数据,利用回归分析以及相关分析的方法对中国温带地区(>30°N)植被物候期时空变化特征进行分析,并研究物候变化对GPP的影响。结果表明:我国温带地区整体植被生长季开始日期(Start of the Season,SOS)、结束日期(End of the Season,EOS)和生长季长度(Length of the Season,LOS)的14 a平均值和标准差分别为第121±10 d、第270±12 d和153±12 d;SOS提前趋势(r=-0.36,p=0.21)、EOS滞后趋势(r=0.41,p=0.15)与LOS增长趋势(r=0.51,p=0.06)均不明显;但是年均LOS与GPP相关性显著(r=0.74,p=0.002 5),且呈正相关关系。2001～2014年LOS与GPP年均值的空间分布均呈现出由西北向东南增加的趋势;研究区SOS、EOS与LOS的年际变化呈现显著变化(p<0.05)的地区分别占研究区的13%、21%、13.2%。SOS、EOS、LOS与GPP显著相关(p<0.05)的地区分别占研究区的8.31%、9.33%、8.72%,三者与GPP的相关关系均以中度相关为主(p<0.05,0.5<|r|<0.8),二者高度相关(p<0.05,|r|≥0.8)的地区很少。研究区植被物候期变化显著影响(p<0.05)植被年均GPP的地区仅有4.29%。     

Evaluation and comparison of gross primary production estimates for the Northern Great Plains grasslands

Two spatially-explicit estimates of gross primary production (GPP) are available for the Northern Great Plains. An empirical piecewise regression (PWR) GPP model was developed from flux tower measurements to map carbon flux across the region. The Moderate Resolution Imaging Spectrometer (MODIS) GPP model is a process-based model that uses flux tower data to calibrate its parameters. Verification and comparison of the regional PWR GPP and the global MODIS GPP are important for the modeling of grassland carbon flux. This study compared GPP estimates from PWR and MODIS models with five towers in the grasslands. Among them, PWR GPP and MODIS GPP showed a good agreement with tower-based GPP at three towers. The global MODIS GPP, however, did not agree well with tower-based GPP at two other towers, probably because of the insensitivity of MODIS model to regional ecosystem and climate change and extreme soil moisture conditions. Cross-validation indicated that the PWR model is relatively robust for predicting regional grassland GPP. However, the PWR model should include a wide variety of flux tower data as the training data sets to obtain more accurate results.In addition, GPP maps based on the PWR and MODIS models were compared for the entire region. In the northwest and south, PWR GPP was much higher than MODIS GPP. These areas were characterized by the higher water holding capacity with a lower proportion of C₄ grasses in the northwest and a higher proportion of C₄ grasses in the south. In the central and southeastern regions, PWR GPP was much lower than MODIS GPP under complicated conditions with generally mixed C₃/C₄ grasses. The analysis indicated that the global MODIS GPP model has some limitations on detecting moisture stress, which may have been caused by the facts that C₃ and C₄ grasses are not distinguished, water stress is driven by vapor pressure deficit (VPD) from coarse meteorological data, and MODIS land cover data are unable to differentiate the sub-pixel cropland components.     

Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration

The approach of using primarily satellite observations to estimate ecosystem gross primary production (GPP) without resorting to interpolation of many surface observations has recently shown promising results. Previous work has shown that the remote sensing based greenness and radiation (GR) model can give accurate GPP estimates in crops. However, the feasibility of its application and the model calibration to other ecosystems remain unknown. With the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) images and the surface based estimates of photosynthetically active radiation (PAR), we provide an analysis of the GR model for estimating monthly GPP using flux measurements at fifteen sites, representing a wide range of ecosystems with various canopy structures and climate characteristics. Results demonstrate that the GR model can provide better estimates of GPP than that of the temperature and greenness (TG) model for the overall data classified as non-forest (NF), deciduous forest (DF) and evergreen forest (EF) sites. Calibration of the GR model is also conducted and has shown reasonable results for all sites with a root mean square error of 47.18 g C/m²/month. Different coefficients acquired for the three plant functional types indicate that there are shifts of importance among various factors that determine the monthly vegetation GPP. The analysis firstly shows the potential use of the GR model in estimating GPP across biomes while it also points to the needs of further considerations in future operational applications.     

不同叶面积指数遥感数据模拟中国总初级生产力的时空差异

陆地生态系统总初级生产力（GPP）反映了植物吸收固定大气中CO₂的能力,是碳循环过程中的重要环节。光能利用率（LUE）模型被广泛应用于GPP模拟。叶面积指数（LAI）数据是LUE模型的重要输入数据,不同的LAI数据差异较大,从而导致GPP模拟存在很大差异。利用3种常用的卫星遥感LAI数据（MCD15、GLASS和GlobMap）和气象数据模拟中国2003~2017年的GPP,比较了3种LAI数据在中国区域的时空差异,分析不同LAI数据模拟的中国GPP的时空差异。研究结果表明：3种LAI数据在中国区域的年平均值和LAI变化趋势的空间分布格局存在明显差异,森林区域的差异较大;2003~2017年间,中国区域3种LAI年平均值均呈显著增加趋势（p<0.01）,但不同LAI数据年平均值的年际变化差异明显;站点尺度GLASS LAI模拟的GPP与观测值相关性较好;不同LAI数据模拟的中国GPP总量多年平均值差异明显,最大值为7.46 Pg C a^-1 （GLASS）,最小值为6.39 Pg C a^-1 （GlobMap）;3种LAI数据模拟的中国GPP总量在2003~2017年呈显著增加趋势（p<0.05）,但不同的LAI数据模拟的中国GPP年总量的年际变化差异明显;不同LAI数据模拟的年均GPP和GPP变化趋势的空间分布格局存在明显差异,森林和农田区域的差异较大。研究结果有助于评估由于LAI数据造成的区域GPP模拟结果的不确定性。     

Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems

One of the most frequently applied methods for integrating controls on primary production through satellite data is the light use efficiency (LUE) approach, which links vegetation gross or net primary productivity (GPP or NPP) to remotely sensed estimates of absorbed photosynthetically active radiation (APAR). Eddy covariance towers provide continuous measurements of carbon flux, presenting an opportunity for evaluation of satellite estimates of GPP. Here we investigate relationships between eddy covariance estimated GPP, environmental variables derived from flux towers, Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and GPP across African savanna ecosystems. MODIS GPP was found to underestimate GPP at the majority of sites, particularly at sites in the Sahel. EVI was found to correlate well with estimated GPP on a site-by-site basis. Combining EVI with tower-measured PAR and evaporative fraction (EF, a measure of water sufficiency) improved the direct relationship between GPP and EVI at the majority of the sites. The slope of this relationship was strongly related to site peak leaf area index (LAI). These results are promising for the extension of GPP through the use of remote sensing data to a regional or even continental scale.     

2007~2018年中国陆地植被总初级生产力与日光诱导叶绿素荧光的时空格局及其气候调控

日光诱导叶绿素荧光（SIF）作为总初级生产力（GPP）的替代指标,在区域GPP估算上表现出巨大的潜力。植被SIF和GPP具有较好的线性关系,但是不同的气候条件对SIF-GPP关系的影响仍不清晰。利用2007~2018年MODIS GPP和GOME-2 SIF以及环境条件（温度、降水、辐射等）研究中国陆地植被GPP和SIF的时空格局以及环境因子的调控。结果发现中国陆地植被GPP和SIF时空格局是一致的,但是作为表征光能分配的新指标GPP/SIF在空间分布上存在显著的差异。此外,SIF产量（SIF_Yield）受到约束GPP的环境因子（最小温度、饱和水汽压差、土壤水分和APAR）的共同调控,间接证实了SIF和GPP紧密的联系。因此,由于在时间和空间上SIF与GPP的关系受到环境条件的调控,使用基于卫星的SIF准确估算区域GPP应该考虑环境因子的约束。     

滨海湿地碳源/汇模拟系统的构建与应用

目前,针对滨海湿地生态系统碳过程模型构建的研究有一定的进展,但在如何耦合生态过程模型与遥感技术去估算湿地碳源/汇的时空格局动态方面仍处在尝试阶段。通过对湿地生态系统碳过程模型和遥感反演模型的构建,数据库技术和地理信息系统(GIS)软件的二次开发完成了"滨海湿地碳源/汇模拟系统"软件的开发。在此基础上,以区域遥感卫片、野外湿地监测和气象观测数据为主要驱动变量,模拟了崇明东滩湿地潮间带芦苇群落和旱生芦苇群落的碳收支时空格局动态。系统可为管理者估算区域尺度滨海湿地碳源/汇时空动态,预测这一类型湿地碳汇潜能在人类活动和气候变化影响下的发展趋势,为管理者提供一定的理论与技术支持。     

Estimating northern peatland CO2 exchange from MODIS time series data

Studies using satellite sensor-derived data as input to models for CO₂ exchange show promising results for closed forest stands. There is a need for extending this approach to other land cover types, in order to carry out large-scale monitoring of CO₂ exchange. In this study, three years of eddy covariance data from two peatlands in Sweden were averaged for 16-day composite periods and related to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled photosynthetic photon flux density (PPFD). Noise in the time series of MODIS 250 m vegetation indices was reduced by using double logistic curve fits. Smoothed normalized difference vegetation index (NDVI) showed saturation during summertime, and the enhanced vegetation index (EVI) generally gave better results in explaining gross primary productivity (GPP). The strong linear relationships found between GPP and the product of EVI and modeled PPFD (R² = 0.85 and 0.76) were only slightly stronger than for the product of EVI and MODIS daytime 1 km land surface temperature (LST) (R² = 0.84 and 0.71). One probable reason for these results is that several controls on GPP were related to both modeled PPFD and daytime LST. Since ecosystem respiration (ER) was largely explained by diurnal LST in exponential relationships (R² = 0.89 and 0.83), net ecosystem exchange (NEE) was directly related to diurnal LST in combination with the product of EVI and modeled PPFD in multiple exponential regressions (R² = 0.81 and 0.73). Even though the R² values were somewhat weaker for NEE, compared to GPP and ER, the RMSE values were much lower than if NEE would have been estimated as the sum of GPP and ER. The overall conclusion of this study is that regression models driven by satellite sensor-derived data and modeled PPFD can be used to estimate CO₂ fluxes in peatlands.     

数据融合技术在提高NPP估算精度中的应用

针对现有遥感数据不能同时满足在时间和空间上精确监测植被动态变化的问题,提出利用时空适应性反射率融合模型（STARFM）的方法对MODIS-NDVI和TM-NDVI影像数据进行融合处理获得30 m较高时空分辨率的融合NDVI影像,进而将多种尺度的MODIS-NDVI和融合NDVI数据分别输入到CASA模型,对锡林浩特地区进行植被净初级生产力（NPP）的多尺度估算。将不同尺度的NPP估算结果与地上生物量地面实测值进行验证比较,结果表明：随着输入NDVI空间分辨率的提高,NPP估算值与实测地上生物量之间的相关性也逐渐增大,[r]最大值达到了0.915。此外以融合NDVI影像作为输入数据之一的NPP估算值与实测地上生物量的相关性均比未融合NDVI的相关性高,说明融合NDVI估算NPP的效果较未融合NDVI好,并且以融合NDVI影像作为模型输入数据可提高NPP估算精度。     

Impact of nutrients on peatland GPP estimations using MODIS time series data

Time series of satellite sensor-derived data can be used in the light use efficiency (LUE) model for gross primary productivity (GPP). The LUE model and a closely related linear regression model were studied at an ombrotrophic peatland in southern Sweden. Eddy covariance and chamber GPP, incoming and reflected photosynthetic photon flux density (PPFD), field-measured spectral reflectance, and data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used in this study. The chamber and spectral reflectance measurements were made on four experimental treatments: unfertilized control (Ctrl), nitrogen fertilized (N), phosphorus fertilized (P), and nitrogen plus phosphorus fertilized (NP). For Ctrl, a strong linear relationship was found between GPP and the photosynthetically active radiation absorbed by vegetation (APAR) (R² = 0.90). The slope coefficient (ε_s, where s stands for “slope”) for the linear relationship between seasonal time series of GPP and the product of the normalized difference vegetation index (NDVI) and PPFD was used as a proxy for the light use efficiency factor (ε). There were differences in ε_s depending on the treatments with a significant effect for N compared to Ctrl (ANOVA: p = 0.042, Tukey's: p ≤ 0.05). Also, ε_s was linearly related to the cover degree of vascular plants (R² = 0.66). As a sensitivity test, the regression coefficients (ε_s and intercept) for each treatment were used to model time series of 16-day GPP from the product of MODIS NDVI and PPFD. Seasonal averages of GPP were calculated for 2005, 2006, and 2007, which resulted in up to 19% higher average GPP for the fertilization treatments compared to Ctrl. The main conclusion is that the LUE model and the regression model can be applied in peatlands but also that temporal and spatial changes in ε or the regression coefficients should be considered.     

稀土矿开采导致的植被净初级生产力损失遥感评估——以江西省赣州市为例

稀土矿的无序开采既造成了稀土资源的浪费,也导致了矿区及其周边生态环境的恶化。以江西省赣州市为例,建立了一套适用于稀土矿开采导致的植被净初级生产力(NPP)损失遥感评估方法,该方法充分利用了高、中、低3种分辨率遥感数据的优势,涵盖了基准参考区选择、植被受损范围界定、低分辨率植被NPP数据降尺度等关键技术环节。将该方法应用于研究区2013年的植被NPP损失评估,结果表明:1截止2013年,赣州市稀土开采造成的植被直接破坏面积为31.74km~2,间接受损面积为44.48km~2。随着距矿区的距离增大,植被间接受损面积呈指数下降(R~2=0.96,P0.01);2 2013年,赣州市稀土开采导致的植被NPP总损失量为3.87×10~(10) gC,其中直接损失占总损失的77.81%,间接损失占总损失的22.89%,说明在稀土矿开采导致的生态破坏评估中,间接受损量不容忽视。文章构建的植被NPP损失评估方法可为其他类似矿区的生态破坏评估提供解决思路,研究结果可为稀土矿区生态评估、稀土定价以及矿区的生态环境管理提供依据。     

水色水温遥感产品真实性检验误差分析

真实性检验是利用现场观测数据或其他高质量遥感产品来获取待检验遥感产品精度的技术,是遥感产品制作及其应用的前提。通过分析均方根误差、平均绝对误差和平均相对误差等多种遥感产品精度评价统计量的适用性,确定了一套水色、水温遥感产品真实性检验流程。以中分辨率成像光谱仪(MODIS)海表温度(SST)遥感产品的真实性检验实例展示了文中确定的水色水温遥感产品真实性检验流程的可行性。分析结果表明待检验产品的分布规律(样本均值和标准偏差)对检验结果的统计量会产生一定的影响,平均值对平均相对误差的影响呈现高相关性。     

环境中多溴联苯醚(PBDEs)分布特征研究进展

多溴联苯醚(PBDEs)是一类具有生态风险的新型环境有机污染物。PBDEs作为阻燃剂已经被愈来愈广泛地添加到工业产品中,对大气、水体、沉积物、土壤等环境介质产生污染,并最终危害生物和人类健康。鉴于这一环境新问题的产生,本文概述了环境介质中PBDEs的来源、含量,并对其分布特征进行了探讨。     

面向应用的可重构编译器ASCRA(英文)

在很多应用领域已经开展了可重构计算的研究,但是由于缺乏高层设计工具,设计者需要较深的软件和硬件专业知识才能开发GPP/RAU架构的程序,阻碍了其大规模应用。提出了一种面向应用的可重构编译器——ASCRA的初始架构,它可以自动将C语言映射为VHDL语言,从而解决可重构计算中自动编译工具的瓶颈。ASCRA编译器主要研究软硬件划分技术和面向硬件的优化技术,如脉动阵列、循环流水技术。在ML505开发平台上,设计实现了ASCRA编译器的验证平台,并通过实验给出了核心程序段生成VHDL代码的综合信息。     

Model-augmented methods for estimation of contact pressure distribution

On-line measurement of the contact pressure distribution (CPD) at the tool-workpiece interface during sheet metal stamping is critical to advancing the state-of-art in tool wear and product quality monitoring. Since the number of sensors that can be integrated into a tool structure is limited by concerns of structural integrity and cost, estimation of CPD through a small number of sparsely located sensors has created unique challenges in information acquisition and representation. Specifically, the problem of determining continuous CPD from discrete sensor measurements is under-constrained and thus ill-posed. A mathematical framework is needed for treating such a problem. This paper presents three mathematical approaches Regularization, Kriging, and Spatial Blending to address this problem and discusses their relative merits and limitations.     

基于垂线的WSN基站位置隐私保护算法

针对无线传感器网络基站位置隐私保护问题,提出一种基于垂线的基站位置隐私保护算法.根据源节点的位置与坐标轴上一点随机确定一条直线,过基站做直线的垂线,源节点关于该垂线对称的点为第1个预期幻影源节点,使第1个幻影源节点分布具有地理位置多样性.以第1个预期幻影源节点为垂足建立垂线,在该垂线上确定第2个预期幻影源节点,为第2个...     

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.     

A strategic analysis for successful open source software utilization based on a structural equation model

Commercial software companies face many challenges when competing in today’s fast moving and competitive industry environment. Recently, the use of open source software (OSS) has been proposed as a possible way to address those challenges. OSS provides many benefits, including high-quality software and substantial profits. Nevertheless, OSS has not been effectively utilized in real business. The purpose of this paper is to find what affects the utilization of OSS. For this study, we propose a structural equation model (SEM) to analyze the relationships between the quality factors based on ISO/IEC 9126 and OSS utilization. In addition, we suggest an open source software utilization index (OSSUI) based on the proposed SEM. The results provide us with the controllable feedback information to improve user (programmer) satisfaction during OSS utilization.