集成遥感数据的陆地净初级生产力估算模型研究综述

净初级生产力(NPP)是衡量碳循环、指导土地利用、评估生态安全、指示环境变化、反映粮食安全等的重要参量,其估算受模型构建机理和生态系统关键地表参数输入的影响。近年来,随着遥感数据的不断丰富和遥感处理技术的快速发展,集成遥感数据的NPP估算模型相较于仅采用气候、土壤等传统观测数据的非遥感模型,在分析时空异质性等方面的优势日益凸显。本文基于Web of Science和CNKI两大数据库,采用文献统计分析方法,系统回顾NPP研究概况及国内外集成遥感数据的NPP估算模型的近期进展;并将集成遥感数据进行NPP估算的模型分为统计模型、光能利用率模型、过程模型及耦合模型四类;重点阐述了各类遥感估算模型的机理、差异性、适宜性及局限性;最后,在分析NPP遥感估算面临困境和科学挑战的基础上,从机理与影响因素、数据基础、参数反演、时空尺度拓展、软硬件支撑等方面对未来研究进行了展望。     

城市绿量测算模式及信息系统

作者提出了以彩红外航片判读和计算机模拟技术测算绿量、建立绿量数据库、及对该数据库的GIS化开发形成绿量信息管理系统的一整套理论技术与方法。     

Dynamic change of net primary productivity and fractional vegetation cover in the yellow river Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.     

Dynamic change of net primary productivity and fractional vegetation cover in the Yellow River Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.     

中国陆地植净第一性生产力及季节变化研究

利用植被指数与植被吸光合有效辐射比例之间的线性关系。由１９９２年４月～１９９３年３月１２个月的１ｋｍ ＡＶＨＲＲ ＮＤＶＩ资料及同期地面气象资料确定地表植被吸收的光合有儿辐射,然后由光能利用率得到植被净第一性生产力（ＮＰＰ）。为了更准确计算ＮＰＰ,本文还考虑了温度及土壤水分条件对光能利用率的影响,最后得到我国陆地植被所ＮＰＰ分布图,并对中国陆地植被净第一性生产力分布情况的季节变化及不同匠ＮＰＰ季节     

基于植被动态模式预估中国植被净初级生产力变化格局

本文选用部门间影响模式比较计划（ISI-MIP）提供的6个植被动态模式数据,对比遥感反演值计算了各模式在中国不同植被区的拟合优度,评估了模式的适用性;并提出了以拟合优度为权重的区域年均净初级生产力（NPP）算法,有效解决了已有研究由于数据和方法的不同而对中国NPP估算效果较差的问题。结合两种浓度路径下（RCP2.6和RCP6.0）的模式估算结果,评估了未来30 中国NPP的变化格局。结果表明：单个模式数据对中国大部分区域NPP的拟合效果较差（R² < 0.4）,所计算的中国平均NPP整体偏高33%~97%,但能较为准确地反映空间上从东南向西北递减的趋势。通过加权合成的新序列整体拟合优度为0.86,在单一植被区的拟合优度也基本大于0.3,能更好地反映未来NPP的变化格局。未来中国平均NPP仍将保持由东南向西北递减的分布,中国均值呈波动增长状态,在2035年达到8.8 μg/(m² s),2050年达到9.7 μg/(m² s)左右。随着时间的推移,RCP2.6路径下主要增长区将由南方地区向北偏移,在华北地区增长变显著,在西南、中南地区增速变慢,显著增长的面积变小;在RCP6.0路径下主要增长区将向东北、东南和西部地区退缩,中东部地区增长变不显著。研究发现高浓度路径对2016—2025年间植被NPP的增长主要起促进作用,但在2035—2050年间开始起抑制作用。同时,高浓度路径下NPP的空间分布将变得更加极端,特别是位于青藏高原西北部的高寒荒漠、温性荒漠及灌木半灌木荒漠将增长缓慢或不增长。     

Estimation of regional evapotranspiration over Northwest China using remote sensing

1 IntroductionThe method for estimating evapotranspiration (ET) was first given by Dalton in 1802, and a number of models for ET estimation have been presented since then. Those models, from the experiential and semi-experiential models[1,2] and physical models[3,4] to the models in terms of the mechanism for energy and water fluxes in soil-vegetation-atmosphere transfer system such as SiB, have improved the precision of ET estimation. It is, however, difficult to calculate regional ET by …     

Estimation of regional evapotranspiration over Northwest China using remote sensing

It is a very complicated problem to estimate evapotranspiration (ET) over a large area of land surface. In this paper, the evapotranspiration estimation models for dense vegetation and bare soil are presented, based on the information of parameters like vegetation cover-degree and surface albedo. Combined with vegetation cover-degree data, a model for regional evapotranspiration estimation over the heterogeneous landscape is derived. Through a case study using remote sensing data over Northwest China, the accuracy of the model for regional evapotranspiration estimation is checked. The result shows that the accuracy of the model is satisfactory. The features of evapotranspiration over Northwest China are also discussed with the application of the model.     

Carbon uptake and change in net primary productivity of oasis-desert ecosystem in arid western China with remote sensing technique

Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity (NPP). We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement (R2 = 0.85, P<0.001) between the estimates and the ground-based measurement was obtained. The spatial distribution of mountain-oasis-desert ecosystem shows an obvious heterogeneous carbon uptake. The results are applicable to arid ecosystem studies ranging from characterizing carbon cycle, carbon flux over arid areas to monitoring change in mountain-oasis-desert productivity, stress and management.     

干旱生态系统净初级生产力估算及变化探测

1 Introduction Arid western China stretches from west of Helan Mountains to south of the piedmont of Kunlun Mountains, covering about 2.50×106 km2 or 26.08% of the total territorial area of China. Its unique geographic location in the hinterland of Euras…     

气候变化和人类活动对盐池县植被净初级生产力的影响

为定量区分退耕还林还草背景下北方典型农牧交错带植被变化过程中气候变化和人类活动的相对贡献率,以宁夏盐池县2000—2020年植被变化为研究对象,基于MODIS13Q1-NDVI数据、地表覆盖数据和气象数据,采用Thornthwaite纪念模型和CASA（Carnegie-ames-stanford approach）模型分别估算了逐年的潜在净初级生产力（Potential net primary productivity, PNPP）和实际净初级生产力（Actual net primary productivity, ANPP）。综合运用趋势分析、相关分析和差值比较法分析了2000—2020年盐池县净初级生产力（Net primary productivity, NPP）时空变化特征及其驱动力,并定量确定了气候因子和人类活动对盐池县植被变化的相对贡献率。结果表明：（1） 在2000—2020年盐池县NPP总体呈上升趋势,但存在着显著的空间异质性,主要表现为植被NPP改善区面积远大于NPP退化区面积,且改善或退化程度也存在显著的空间分异。植被改善区主要分布于荒漠、荒漠草原等退耕还林还草工程区域和灌溉区,而植被退化区则分布于荒漠和荒漠草原的边缘地带。（2） 植被变化归因分析表明,在植被改善区,气候变化和人类活动共同主导驱动了植被的改善,但气候变化的相对贡献率（59.77%）大于人类活动的相对贡献率（40.23%）,而在植被退化区,人类活动的相对贡献率（91.77%）则显著高于气候变化的相对贡献率（8.23%）。（3） 驱动力分析表明,研究区植被NPP变化与降水量呈显著正相关,而与气温的相关性较弱;而人类活动是驱动植被退化区NPP下降的主要原因,但负向影响力有所减弱。总体而言,气候变化是植被改善区的主要驱动力,而人类活动是植被退化区的主要驱动因素,两者共同作用则使盐池县整体生态环境得以改善。     

Modeling net primary productivity of the terrestrial ecosystem in China from 1961 to 2005简

Net primary productivity （NPP） is the structure and function of the ecosystem. NPP can most important index that represents the be simulated by dynamic global vegetation models （DGVM）, which are designed to represent vegetation dynamics relative to environ- mental change. This study simulated the NPP of China＇s ecosystems based on the DGVM Integrated Biosphere Simulator （IBIS） with data on climate, soil, and topography. The appli- cability of IBIS in the NPP simulation of China＇s terrestrial ecosystems was verified first. Comparison with other relevant studies indicates that the range and mean value of simula- tions are generally within the limits of observations; the overall pattern and total annual NPP are close to the simulations conducted with other models. The simulations are also close to the NPP estimations based on remote sensing. Validation proved that IBIS can be utilized in the large-scale simulation of NPP in China＇s natural ecosystem. We then simulated NPP with climate change data from 1961 to 2005, when warming was particularly striking. The following are the results of the simulation. （1） Total NPP varied from 3.61 GtC/yr to 4.24 GtC/yr in the past 45 years and exhibited minimal significant linear increase or decrease. （2） Regional differences in the increase or decrease in NPP were large but exhibited an insignificant overall linear trend. NPP declined in most parts of eastern and central China, especially in the Loess Plateau. （3） Similar to the fluctuation law of annual NPP, seasonal NPP also displayed an insignificant increase or decrease; the trend line was within the general level. （4） The re- gional differences in seasonal NPP changes were large. NPP declined in spring, summer, and autumn in the Loess Plateau but increased in most parts of the Tibetan Plateau.     

基于遥感-生态过程的绿洲-荒漠生态系统净初级生产力估算

针对干旱区特有的气候-植被特征,利用卫星遥感混合像元分解技术对干旱区植被进行了光合作用植被和非光合作用植被区分和组分解析,尝试通过对于旱覆被植被灌层结构进行解析而解决因植被光能吸收的估算问题,并参考国际上遥感-生态模型GLO-PEM和CASA,借助遥感生态反演的物理分析,初步构建起基于遥感与生态过程的干旱区适用的光能利用率模型NPP-PEM,并以ERDAS IMAGINE为平台,实现了模型可视化模型界面,可用于中国西部干旱区山地-绿洲-荒漠生态系统年净第一性生产力的估算.由于考虑了干旱植被生理特征和灌层结构的光能利用模型,模拟结构与原理更加合理完善,为引入其他生态模型应用或移植到干旱区提供借鉴,从而为中国干旱区陆地生态系统碳循环研究开辟了途径.     

Assessment of biochemical concentrations of vegetation using remote sensing technology

The main biochemicals (such as lignin, protein, cellulose, sugar, starch, chlorophyll and water) of vegetation are directly or indirectly involved in major ecological processes, such as the functions of terrestrial ecosystems (i.e., nutrient-cycling processes, primary production, and decomposition). Remote sensing techniques provide a very convenient way of data acquisition capable of covering a large area several times during one season, so it can play a unique and essential role provided that we can relate remote sensing measurements to the biochemical characteristics of the Earth surface in a reliable and operational way. The application of remote sensing techniques for the estimation of canopy biochemicals was reviewed. Three methods of estimating biochemical concentrations of vegetation were included in this paper: index, stepwise multiple linear regression, and stepwise multiple linear regression based on a model of the forest crown. In addition, the vitality and potential applying value are stressed.     

Assessment of biochemical concentrations of vegetation using remote sensing technology

The main biochemicals (such as lignin, protein, cellulose, sugar, starch, chlorophyll and water) of vegetation are directly or indirectly involved in major ecological processes, such as the functions of terrestrial ecosystems (i.e., nutrient-cycling processes, primary production, and decomposition). Remote sensing techniques provide a very convenient way of data acquisition capable of covering a large area several times during one season, so it can play a unique and essential role provided that we can relate remote sensing measurements to the biochemical characteristics of the Earth surface in a reliable and operational way. The application of remote sensing techniques for the estimation of canopy biochemicals was reviewed. Three methods of estimating biochemical concentrations of vegetation were included in this paper: index, stepwise multiple linear regression, and stepwise multiple linear regression based on a model of the forest crown. In addition, the vitality and potential applying value are stressed.     

青藏高原主要生态系统净初级生产力的估算

利用青藏高原贡嘎山、海北、五道梁、拉萨等4个野外台站2000~2002年的观测数据、陆地生态系统模型与2001年MODIS遥感数据相结合的方法来估算青藏高原区域的净初级生产力。结果表明:青藏高原区域的净初级生产力空间分布趋势表现出由东南向西北逐渐递减的梯度,该趋势也与水热梯度表现基本一致;整个青藏高原的净初级生产力为302.44×1012 gC yr-1,其中森林的净初级生产力最高,120.11×1012 gC yr-1,占整个高原净初级生产力的39.7%;全年中夏季(6~8月) 的净初级生产力最高,246.7×1012 gC yr-1,约占全年总净初级生产力的80%。用实测数据验证模拟结果表明,二者非常相符。     

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.     

东海初级生产力遥感反演及其时空演化机制

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for Case I and Case Ⅱ water bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m^2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m^2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.     

中国陆地净初级生产力的季节变化研究

了解不同季节陆地净初级生产力(NPP)的变化及与气候的相互关系以及在不同地类的差异对深刻理解我国陆地生态系统对全球气候变化的响应和陆地碳循环研究具有重要意义。本文使用1981～2000年间GLO-PEM模型模拟的我国陆地NPP数据和同期气温、降水以及土地利用数据, 研究不同季节我国陆地植被NPP的变化。结果表明,在1981～2000年期间,四个季节的NPP都呈显著增加趋势,春季是NPP增加速率最快的季节,夏季是NPP增加量最大的季节。耕地在春、夏和秋季NPP增长和增长率最高,林地冬季NPP增长最多而水域冬季NPP增长率最高。夏季NPP增长最高的区域分布于我国东部的多数地区、内蒙古东部、四川盆地、贵州东部、藏南和新疆西部;夏季NPP降低最多的区域分布于在呼伦贝尔高原、鄂尔多斯高原、黄土高原、青藏高原东部和新疆西北部。