中国沼泽湿地净初级生产力时空演变研究  

Spatiotemporal evolution of net primary productivity of swampy wetlands in China

作　　者：张猛 钟安豪 齐帅洋 刘洋[4] 张怀清[4] ZHANG Meng;ZHONG Anhao;QI Shuaiyang;LIU Yang;ZHANG Huaiqing(Research Center of Forestry Remote Sensing&Information Engineering Central South University of Forestry&Technology,Changsha 410004,China;Key Laboratory of Forestry Remote Sensing Based Big Data&Ecological Security for Hunan Province,Changsha 410004,China;Key Laboratory of State Forestry&Grassland Administration on Forest Resources Management and Monitoring in Southern Area,Changsha 410004,China;The Research Institute of Forest Resources Information Techniques,ChineseAcademy of Forestry,Beijing 100091,China)

机构地区：[1]中南林业科技大学林业遥感信息工程研究中心,长沙410004 [2]中南林业科技大学林业遥感大数据与生态安全湖南省重点实验室,长沙410004 [3]中南林业科技大学南方森林资源经营与监测国家林业与草原局重点实验室,长沙410004 [4]中国林业科学研究院资源信息研究所,北京100091

出　　处：《遥感学报》2025年第1期167-180,共14页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:41901385);洞庭湖国家真实性检验站建设(编号:30-Y30A02-9001-20/22-6);博士后科学基金(编号:2019M652815,2020T130731)。

摘　　要：针对目前中国沼泽湿地净初级生产力NPP(Net Primary Production)估算研究相对薄弱以及植被指数饱和导致NPP估算精度偏低等问题,本研究基于MODIS遥感数据产品(MOD13Q1和MCD12Q1),利用核函数RBF(Radial Basis Function)构建的核归一化植被指数(kNDVI)与CASA(Carnegie-Ames-Stanford approach)模型估算了近20年中国沼泽湿地NPP,并定量分析并探讨了2001年—2020年中国沼泽湿地时空演变及其驱动机制。研究结果表明:基于kNDVI估算得到的NPP_Kndvi(以C计)与实测值具有较高的相关性(R^(2)=0.854)和较低的均方根误差(14.46 g/m^(2)·month),与NPP_NDVI相比更接近真实值;相比于NDVI等传统植被指数,kNDVI缓解了植被指数自身的饱和效应,在一定程度上提高了植被净初级生产力NPP的估算精度;近20年中国沼泽NPP年均值变化幅度162.73—189.34 g(/m^(2)·a),呈波动上升趋势,增速为1.215 g(/m^(2)·a)(R^(2)=0.82)。此外,在空间上,中国沼泽湿地NPP增加和减少的区域比例分别为72.96%和26.27%,主要集中在东北平原、青海省东北部和西南部以及四川北部。相比于人类活动,气候变化是影响中国沼泽湿地时空演变的主要驱动因子,两者影响区域占比分别为66.23%和33.76%。本研究可为中国沼泽湿地NPP估算及时空演变研究提供技术与数据支持。Swampy wetlands(forest,scrub,and herbaceous swamps)are among the most important carbon reservoirs on earth and play a pivotal role in the global carbon cycle.The proportion of marshy wetlands in China is nearly 40%of the total wetland area,which is of great significance for maintaining regional biodiversity and ecosystem carbon balance.The Net Primary Productivity(NPP)of vegetation refers to the amount of organic matter accumulated by green plants through photosynthesis minus the remaining part of autotrophic respiration per unit of time and space.It is one of the most important indicators of the carbon sequestration potential of marsh wetlands,which plays a significant role in reflecting the ecological changes of vegetation in the context of climate change.Aiming at the relatively weak research on NPP estimation in China’s swampy wetlands and the saturation problem in the process of NPP estimation,this study estimated the NPP of China’s swampy wetlands in the last 20 years on the basis of MODIS remote sensing data products(MOD13Q1 and MCD12Q1)using the kernel Normalized Difference Vegetation Index(kNDVI)constructed by the radial basis function kernel with the CASA model.Additionally,the spatiotemporal evolution of China’s swampy wetlands and its driving mechanism from 2001 to 2020 were quantitatively analyzed and discussed.The results of the study showed that the coefficient of determination(R^(2))of NPP_kNDVI estimated using the kNDVI index with the measured value of NPP was 0.854,and the root-mean-square error was 14.46 g C/m^(2)month,which was closer to the real NPP value compared with NPP_NDVI.Compared with the saturation phenomenon of NDVI in highly vegetated areas,kNDVI mitigated the saturation effect of the vegetation index itself,adapted to densely and sparsely vegetated areas,and improved the accuracy of the estimation of NPP of vegetation to a certain extent.The regional pattern of multiyear NPP mean values in China’s swampy wetlands was obvious,showing a decreasing and then increasing trend fr

关 键 词：沼泽湿地 净初级生产力 时空演变 人类活动 气候变化 

分 类 号：P2[天文地球—测绘科学与技术]