A new estimation model of vegetation net primary production (NPP) based on remote sensing data and climatic data was presented, with which, the NPP of China terrestrial vegetation in 1982-2000 was estimated, and the intra- and inter- annual variation patterns of the NPP and its responses to climate factors were studied. The results showed that there was an obvious seasonal regularity in the intra-annual variation of the NPP. In 1982-2000, all the terrestrial vegetation types presented an increasing annual NPP, with the greatest increment for deciduous needle leaf forests and the smallest one for grasses. Evergreen broadleaf forests had the largest inter-annual variation, while grasses had the smallest one. Comparing with temperature, precipitation played a stronger driving role in the intra-annual variation of the NPP, and the effects of precipitation and temperature were more obvious in North China than in South China. The driving roles of the climate factors varied with season and latitude.

在GIS系统的支持下，利用卫星遥感资料和地面气象观测资料，构建了基于光能利用率的植被净初级生产力(NPP)遥感模型，估算了我国陆地1982—2000年1—12月植被NPP，分析了1982—2000年我国不同植被类型NPP的季节性和年际性变化规律，基于像元空间尺度讨论了植被NPP对气候的响应关系.结果表明，我国植被NPP年内季节性变化规律明显；我国主要植被类型年NPP在1982—2000年基本呈上升趋势，增长幅度最大的是落叶针叶林，增长幅度最小的是草地；1982—2000年，NPP年际间波动最大的植被类型是常绿阔叶林，年际间波动最小的植被类型是草地.通过NPP对气候因子(降水、温度)变化的响应分析表明，我国降水对植被NPP季节性变化的驱动作用高于温度，气候因子(降水、温度)对北方植被NPP季节性变化的驱动作用高于南方；我国气候因子(降水、温度)对NPP年际变化的驱动作用(强度、方向)随季节 及纬度的不同而不同.

Based on the MOD17A3 data of NASA EOS/MODIS(Terra),the terrestrial NPP in the source regions of Yangtze and Yellow Rivers during 2000 to 2004 is analyzed.The annual NPP of the regions is 82.04 gC·m -2 during the five years,with the maximum of 85.44 gC·m -2 in 2002,and minimum of 78.04 gC·m -2 in 2001.The NPP in the region of Yellow River is higher than that of Yangtze River,and the maximum,exceeding 250 gC·m -2 ,occurs in the southeastern area of the source region of Yellow Rivers,and the minimum,less than 50 gC·m -2 ,appears in the northwest of the source region of Yangtze River.The annual NPP is changing from year to year.The annual NPP of alpine meadow is the highest among all vegetations in the regions,and of course,an annual fluctuation appears.Regression analysis shows that temperature is the key factor controlling the terrestrial NPP in the source regions Yangtze and Yellow Rivers.

基于EOS/MODIS卫星遥感资料的分析表明,2000-2004年江河源地区陆地植被平均年NPP为82.04 gC·m -2 ,相当于同期全国陆地植被年NPP的23%,其中2001年的年NPP最小,只有78.04gC·m -2 ,2002年最大,为85.44 gC·m -2 .根据年NPP分布显示,黄河源区的植被生长状况要好于长江源区,其中在黄河源东南部陆地植被的年NPP>250 gC·m -2 ,为江河源区植被年生长最大的区域;该地区的植被年NPP最小值的区域分布在长江源的西北部地区,年NPP大部分 -2 .江河源地区植被的年NPP表现为显著的年际变化特征,不同地区年NPP的变化特征各不相同;高寒草甸的年NPP为该地区所有陆地植被年NPP中最大,其5 a平均值为89.38 gC·m -2 ,其次为高寒草原和灌木及草本植被;由于地处高寒地区,温度成为影响该地区陆地植被净初级生产力的主要因素.

In this paper we used an Atmosphere-Vegetation Interaction Model (AVIM) that has been validated at regional and global scales to estimate the NPP (net primary production) variation of modern Chinese terrestrial ecosystems and its responses to the climate change. AVIM consists of two inter-coupled components: physical process and eco-physiological process, involving the mater and energy balance between the atmosphere, vegetation and soil. Chinese vegetation is classified 9 types and soil texture is classified into 6 types. The parameters of eco-physiological processes for each vegetation type for AVIM are collected. Daily weather data for 0.5×0.5 grid cells as the forcing of the model are generated from the monthly climate data, coming from the climate research unit, University of East Anglia, UK. The estimated NPP of chinese vegetation changes from 0 to 1 389 gC/(cm 2 ·a), averaging 355 gC/（cm 2 ·a）. Vegetation from the rain forest has the high NPP value, and the low NPP corresponding to the shrub with no cover. The NPP decreases from east to west in China, with the highest NPP occuring at the south area of Yunnan Province, and the lowest appearing at Tibet and Xinjiang areas. Total NPP of the terrestrial ecosystems is 3.33 Pg C, suggesting that such amount of carbon is absorbed from the atmosphere by the vegetation in China. Our work also shows that precipitation is the main factor affecting the NPP of terrestrial ecosystems in China.

利用AVIM（植被与大气相互作用模式）模拟了现代中国陆地生态系统NPP的分布并计算了全国NPP的碳总量。研究结果表明我国现代陆地生态系统的年NPP变化范围在0~1 389 gC/m 2 之间，年平均值为355 gC/m 2 ，年吸收3.33 Pg的大气碳。中国陆地植被NPP呈现自东向西逐渐减小的趋势，NPP的最大值出现在云南西双版纳地区，最小值分布于青藏高原以及新疆地区。中国现代陆地植被NPP主要分布于小于100 gC/(m 2 ·a)、300~500 gC/(m 2 ·a)以及500~700 gC/(m 2 ·a)3个区间，其占总计算值的比例都超过了20%以上；大于1 000 gC/(m 2 ·a)的NPP最少，只占总数的2.15%。对中国陆地植被NPP与气候的相关性分析表明，降水是影响我国陆地生态系统NPP的主要原因。

利用MODIS传感器的MOD17A3数据,通过处理获取了广东省的NPP(植被净初级生产力)分布图;同时,根据Landsat获取的广东省土地利用类型图,提取出广东省水稻的空间分布图.将两者叠加并进行相关运算和分析,得到全省水稻生物量的分布图及其统计数据.同时,进行野外测量并参考已有的研究成果,取稻草和稻秆产量与水稻产量的重量比为0.623,获得水稻总的农作物残余.除去还田、造纸及用做牲畜饲料的那部分,仍有三成左右的可用生物量.研究表明:珠江三角洲经济发展迅猛的城市,水稻生物质能的占有量较少;而在一些边远山区,水稻生物质能占的比重明显偏大.本文通过定量化的研究,为以后广东省水稻生物质能的开发提供了有价值的参考信息.

Vegetation is an important component of terrestrial ecosystems and plays an important role in global matter and energy cycles, as well as carbon balance and climate change. Net Primary Productivity (NPP) is the accumulation of organic matter by green plants per unit of space and time. NPP indicates the growth status of vegetation, and provides information for the management of renewable biological resources. Study of changes in vegetation NPP and the relationship with climatic change is significant in Northeast China, a region which is sensitive to global change. We analyzed spatio-temporal characteristics of vegetation NPP and influencing factors in Northeast China from 2000 to 2006 based on MOD17A3 data from EOS/MODIS (TERRA). Results showed that the range of NPP in the northeast was mainly between 200 and 400gC/( m2 ·a), and average annual NPP in the northeast (400.85gC/( m2 ·a)) was higher than the national average during the same period (360.97gC/( m2 ·a)). The average annual NPP in the forested areas of the Changbai Mountains, Greater Hinggan Mountains and Xiaoxing'anling Mountains, with values from 400 to 600gC/( m2 ·a), was higher than NPP values for the agricultural areas of the Liao River Plain, Songnen Plain and Sanjiang Plain and the eastern Hulunbuir Grasslands((200～400)gC/( m2 ·a)). The lowest NPP values were in the western part of the temperate tufted grass steppes of Hulunbuir and the mixed farm-pasture area of the western Songnen Plain and Chifeng in the Inner Mongolia Autonomous Region, which ranged from 0 to 200gC/( m2 ·a). In terms of the average annual NPP of the main vegetation types in the Northeast, mixed needleleaf-broadleaf forest had the highest value, of 572.56gC/( m2 ·a). Other vegetation types (broadleaf forests, needleleaf forests, marsh, cropland and scrub) had decreasing NPP values in that order, of 473.93gC, 454.42gC, 432.90gC, 378.21gC and 377.33gC/( m2 ·a) respectively. The lowest value was found in grassland (312.45gC/( m2 ·a)). Univariate linear regression was used to simulate the trends of change in average annual NPP in Northeast China from 2000 to 2006. The overall trend for the entire area showed very little change, but area with increased NPP accounted for 30.51% of total area in Northeast China, and area with decreased NPP accounted for 27.43%. Land cover change was an influential factor affecting changes in vegetation NPP in Northeast China during the study period. Regression analysis of vegetation NPP and climate factors showed that precipitation was the key factor controlling terrestrial NPP in the region.

东北地区作为全球变化的敏感区域，分析其植被生产力变化特征及其对气候变化的响应具有重要意义。本文基于EOS/MODIS卫星遥感资料，对东北地区植被净初级生产力（NPP）变化的时空特征及主要影响因素进行分析。结果显示，2000年～2006年，我国东北地区植被年NPP主要集中在(200～400)gC/(m 2 ·年)区间，平均值为400.85gC/(m 2 ·年)，高于同期全国植被年平均NPP（360.97gC/(m 2 ·年)）11.02%。长白山地、大兴安岭和小兴安岭等森林分布区年平均NPP较高，辽河平原、松嫩平原和三江平原农业区及呼伦贝尔草原东部草原区次之，而呼伦贝尔草原西部草原区，松嫩平原西部的农牧交错区及内蒙古赤峰市农牧交错区年平均NPP最小。对东北地区主要植被类型的年均NPP分析，针阔叶混交林年均NPP最大，草地年均NPP最小。一元线性回归分析表明，东北地区2000年～2006年年均NPP变化特征以基本不变的趋势为主，年均NPP增加的面积略高于减少的面积，占东北地区总面积的30.51%，减少地区的面积占总面积的27.43%。土地覆被变化是影响植被NPP变化的重要影响因素之一。植被NPP与气候因子的相关性分析表明，降水是影响东北地区陆地植被净初级生产力的主要因素。

Terrestrial carbon cycle has been the focus in global change research. Simulating net primary production of terrestrial ecosystems has been very important in carbon cycle research for evaluating primary production at global or regional scale; simulating the growth of crop; estimating the spatial pattern of carbon flux and its interaction with climate; and predicting the variation of ecological environment. This study aims to simulate China's terrestrial NPP in 2003 using a remote sensing-based region-scale parametric model (C-Fix model) to explore the tempo-spatial patterns of China's terrestrial net primary production; and to reveal the mechanisms of their responses to various environmental factors in the light of resources balance. C-Fix model is advantageously simple and easy to be established. For these purposes, a national input database has been set up on a 1day-1km tempo-spatial resolution. Data used in this study includes: Leaf Area Index (LAI), daily temperature grid data, daily precipitation grid data and daily solar radiation grid data. The results show that, in 2003, China's total and average terrestrial NPP were 4.37 Pg C and 640.32 g C/(m 2 ·a), respectively. The spatial pattern of NPP is: NPP gradually decreased from southeast of China to northwest of China; the value of NPP are greatest in tropical rainforest and monsoon forest of south of Hainan Island, southwest and south of Yunnan province and southeast of Qing-Tibet Plateau, it is between 1 800 and 2 500 g C/(m 2 ·a), the maximum value is 2 743 g C/(m 2 ·a). The NPP value is below 100 g C/(m 2 ·a) in most parts of Qing-Tibet Plateau and Xinjiang province. The vegetation is sparse in Taklimakan Desert and its NPP is no more than 5 g C/(m 2 ·a). The total NPP value derived from this study is consistent with (2.24～6.13 Pg C) or close to results of other relevant researches, convinced this study's reliability. Moreover, the spatial pattern of NPP simulated by C-Fix model is in accordance with the results of other similar models. This indicates that C-Fix model is appropriate to be applied in China. Future work involves the consideration of the variations in the biophysical and biogeochemical attributes of different land cover types (i.e. forest, grassland, cropland and so on) to reduce the uncertainty of the model.

本研究利用基于光能利用率理论的区域尺度遥感参数模型(C-Fix模型)估算了2003年中国陆地生态系统NPP，并对其空间格局进行了分析。模型输入数据包括叶面积指数数据(LAI)、中国地面气象站的逐日气温数据、逐日降水数据和太阳总辐射数据、数字高程模型(DEM)等，模型输出数据的空间分辨率均为1km 2 ，时间步长为1天。模拟结果表明：2003年中国陆地总NPP和平均NPP分别为4.37 Pg C和640.32 g C/(m 2 ·年)，NPP的主要分布趋势是：从东南沿海向西北逐渐减小；其中海南岛南部、云南西南部和南部、青藏高原东南部的热带雨林和季雨林地区年NPP最大，在1 800g～2 500g C/(m 2 ·年)之间；青藏高原和新疆绝大部分地区，一般在100 g C/(m 2 ·年)以下；西部塔克拉玛干沙漠地区植被稀疏，植被NPP不足5 g C/(m 2 ·年)。C-Fix模型进一步发展需要考虑不同土地覆被类型（比如，森林、草地、农田等）的生物物理和生物地球化学性质的变异性，以减少模型估算结果的不确定性。