Knowledge Resource Center for Ecological Environment in Arid Area
| 西北干旱区植被净初级生产力的遥感估算及时空格局研究 | |
| 其他题名 | Estimation and analysis the Spatial-temporal pattern of the Net Primary Productivity in the Arid Region of Northwest China |
| 焦伟 | |
| 出版年 | 2017 |
| 学位类型 | 硕士 |
| 导师 | 陈亚宁 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 摘 要在过去的半个多世纪，全球几乎所有的地方都经历了升温过程，并由此产生了一系列生态环境问题。不同形式的气候变化都在以不同的方式、方法对生态系统中的碳循环产生影响。植被作为碳循环过程中的重要一环，也对对气候变化产生深刻的响应。植物的光合作用过程，就是碳由气态向固态转化的过程。固定的碳又将会在不同的时间尺度上，进一步通过呼吸作用和其他扰动过程，最终以气体CO2的形式返回大气中，这就完成了碳的循环，而这整个过程必须有植物的参与，才得已进行。植被净初级生产力（Net Primary Productivity，NPP）反映的是植被固定碳的能力。有助于深入了解碳循环过程，是一个重要生态指标，可用以监测自然资源、生态环境的变化。西北干旱区的生态环境比较脆弱和敏感，较小的气候波动可能会引起较大的生态环境的改变，进而得到国内外学者的广泛关注。研究区气候属于干旱性的大陆性气候，地貌形态复杂，高山和盆地相互交错，土壤植被类型特殊，这一系列特征使得这一地区的生态环境与我国其他地区有很大的差异。气候变化使研究区水资源的空间分布更加不均衡，水资源矛盾更加突出，生态系统脆弱性加剧。选取植被NPP这一个具有代表意义的指标实时的动态监测和评估这一地区的生态环境具有重要的现实意义。因此，本研究以西北干旱区的气象站点的数据以及2000-2014年的MODIS NDVI为基础数据，对CASA模型中的部分参数进行本地化率定，引入土地利用数据，利用ARCGIS、MATLAB、ENVI等软件，对西北干旱区植被NPP进行了估算，并分别对不同植被类型的生物量变化进行了定量分析，试图回答在全球气候一系列变化的情况下，西北干旱区植被是怎样分布的，变化趋势如何，不同植被类型之间NPP有何差异性、NPP对气候变化的响应有何空间差异性以及土地利用/土地覆被的变化（LUCC）对植被NPP的影响。研究结果表明：1. 本研究构建了遥感统计模型（多元逐步回归、主成分回归、偏最小二乘回归和岭回归模型）和本地化率定的CASA模型，分别估算西北干旱区2000-2014年植被NPP。通过对两类估算模型的估算结果进行对比分析发现，在模型参数较容易获得的情况下，CASA模型的模拟结果更接近于实测数据，模拟效果更好。2. 西北干旱区多年平均植被NPP为191.63gC/m2，多年平均植被NPP的分布具有明显的区域差异，总体上呈现出西北、东南高，中间低的特征，在阿尔泰山、伊犁河谷、天山北坡、昆仑山西段以及甘肃的河西走廊部分地区生物量较高；中部的沙漠区植被覆盖率极低，一般低于30gC/m2。3. 在年际变化趋势上，2000-2014年研究区植被NPP总体上为增加的趋势，线性增长率为2.98 g C m-2 a-1 （p<0.01），2000-2009年变化比较平稳，线性增长斜率为2.30 g C m-2 a-1，2009年以后迅速增加，线性增长斜率为6.60 g C m-2 a-1；在年内变化上，植被NPP在七月份达到最大，之后出现减少的趋势。经计算，西北干旱区2000-2014年，6月至8月NPP的积累量占整个生长季的64.9%。4. 从研究区NPP变化的空间分布上看， 2000-2014年整体上植被NPP呈现改善的趋势，82.84%呈现出不同程度的增长趋势。且与降水的相关性高于气温，植被生物量与气温的相关系数为0.394，呈弱的正相关，与降水的相关系数为0.538（p<0.05），通过95%的显著性检验，且不同植被类型与气候因子的相关性具有差异性。5. 通过分析土地利用/覆被的特征和对植被NPP的影响发现，2000-2014年间，西北干旱区的LUCC以未利用土地面积减少和林地、耕地、灌丛、草地增加为主要特征，其中林地变化率最大，草地变化率最低。各植被类型中平均植被NPP增长最快的是耕地，每年增加6.34gC/m2·a，其次是灌丛，每年增加4.40 gC/m2·a，林地增长速度最慢，为0.53 gC/m2·a。2000-2014年植被NPP总量由2.89×105G gC/a 增加到3.26×105G gC/a，增加量为3.69×104 G gC/a，变化率为13%。 |
| 英文摘要 | Abstract Over the past half-century, almost all parts of the world have experienced warming process, resulting in a series of ecological and environmental problems. Different forms of climate change have different effects on the carbon cycle of terrestrial ecosystems. As an important part of the carbon cycle, vegetation has a profound response to climate change. The vegetation fixed CO2 and synthesized the organic material through photosynthesis. Through respiration and other disturbances in different time scales, the carbon can be returned to the atmosphere. Thus, the carbon cycle is a dynamic equilibrium process, and the whole process must have the participation of plants. Net primary productivity (NPP) represents the carbon sequestration capacity of vegetation. The NPP is an integral part of understanding the carbon cycle process, an important ecological index to monitor the changes of natural resources and ecological environment. The ecological environment in arid area of Northwest China is fragile and sensitive, and the smaller climate fluctuation may cause the change of ecological environment, so the arid region of Northwest China has been widely concerned by scholars Arid continental climate, landforms of mountains and basins and the special characteristics of the soil and vegetation have made significant different vegetation types and ecosystems between these areas with other regions in our country. Climate change has further aggravated the unbalanced distribution of the water resources in the study area. The contradiction of water resources is more prominent, and the vulnerability of ecosystem is more serious. Therefore, it has a profound and far reaching significance for select vegetation NPP as a representative index to monitor and evaluate the ecological environment in this area. Based on MODIS NDVI data and Meteorological station data from 2000-2014 in arid region of Northwest China, this paper improved CASA model with land cover type, and then estimated and quantitative analyzed the changes of NPP in different vegetation types by using the ARCGIS, MATLAB, ENVI and other software. Under the background of climate change, this paper trying to answer some question of what are the distribution of vegetation, the trend of the vegetation, the difference of the biomass in different land cover types, the difference of the effects of climate change on vegetation NPP and the effects of different land use / land cover on vegetation NPP. Results show:1. In this paper, the remote sensing statistical models, including multi-stepwise regression model, principal components regression model, partial least-squares regression model and ridge regression model, and the CASA model were constructed. The vegetation NPP was estimated by these models. Through the comparison and analysis of the two kinds of estimation models, it is found that the simulation results of the CASA model are closer to the measured data and the simulation results of the CASA model are better than the remote sensing statistical model when the model parameters are easily obtained.2. The mean annual vegetation NPP of this area is 191.63gC/m2, There is an obvious regional difference in NPP distribution in arid area in Northwest China, basically high in the northwest and southeast and low in the center. In the Altai Mountains, Ili River Valley, Tianshan Mountains, west of Kunlun Mountains and some areas in Hexi Corridor, the biomass is high; in the Central of desert, the vegetation NPP is very low, generally less than 30gC/m2.3. There is increasing trend in annual NPP with an annual rate at 2.98 gC/m2 (p<0.01). The trend is relatively stable from 2000 to 2009 with the annual rate at 2.30 g C m-2. After 2009, the annual NPP increased rapidly with the rate at 6.60 g C m-2 a-1. The trend differs for vegetation types with largest increase in cropland(6.34gC/m2·a), followed by shrub(4.40 gC/m2·a), and least increase in woodland(0.53 gC/m2·a). In the seasonal changes, the vegetation NPP is high in July, and then shows s downward trend. By calculation, the NPP from June to August accounted for 64.9% of the whole growth season in the acid region of Northwest China from 2000 to 2014.4. On the spatial distribution of NPP in the study area, overall vegetation NPP has showed a tendency to improve. The vegetation NPP in 82.84% areas was appeared an increased tendency, 3.05% areas remained relatively stable, and 14.11% areas appeared slightly decreased since 2000. Vegetation NPP has a significant correlation with precipitation (r=0.538) and not so significant correlation with temperature (r=0.394), indicating vegetation NPP is more highly correlated with precipitation than temperature, and the correlation coefficient differs for different vegetation types.5. By analyzing the characteristics of land use/land cover and the effects between the land use/land cover with the vegetation NPP, The change of land use / land cover in the arid area of Northwest China was characterized by the decrease of unused land area and the increase of forest land, cultivated land, shrub and grassland from 2000 to 2014. The trend differs for vegetation types with largest increase in cropland (6.34gC/m2·a), followed by shrub (4.40 g C/m2·a), and least increase in woodland (0.53 gC/m2·a). The total amount of vegetation NPP increased from 2.89 × 105G g C / a to 3.26 × 105G g C /a from 2000 to 2014. The increase was 3.69 × 104 G g C / a and the rate of change was 13%. |
| 中文关键词 | 关键词：净初级生产力 ; 西北干旱区 ; CASA模型 ; 时空分布格局 ; 土地利用/覆被 |
| 英文关键词 | Key word: net primary productivity the Arid Region of Northwest China the model of CASA temp-spatial distribution patter Land use / cover |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 自然地理学 |
| 来源机构 | 中国科学院新疆生态与地理研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287996 |
| 推荐引用方式 GB/T 7714 | 焦伟. 西北干旱区植被净初级生产力的遥感估算及时空格局研究[D]. 中国科学院大学,2017. |
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