文献类型：期刊文献

英文题名：Estimation and Spatiotemporal Variation Analysis of Net Primary Productivity in the Upper Luanhe River Basin in China From 2001 to 2017 Combining With a Downscaling Method

作者：Liu, Qinru[1,2] Zhao, Liang[1,2] Sun, Rui[1,2] Yu, Tao[3] Cheng, Shun[4] Wang, Mengjia[1,2] Zhu, Anran[1,2] Li, Qi[1,2]

第一作者：Liu, Qinru

通信作者：Sun, R[1]

机构：[1]Beijing Normal Univ, State Key Lab Remote Sensing Sci, Fac Geog Sci, Beijing 100875, Peoples R China;[2]Beijing Normal Univ, Beijing Engn Res Ctr Global Land Remote Sensing P, Fac Geog Sci, Beijing 100875, Peoples R China;[3]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[4]Saihanba Machine Forest Ctr, Chengde 068450, Peoples R China

年份：2022

卷号：15

起止页码：353-363

外文期刊名：IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING

收录：;EI(收录号：20215111368357);Scopus(收录号：2-s2.0-85121348221);WOS:【SCI-EXPANDED(收录号:WOS:000735511300006)】；

基金：This work was supported by the National Key R&D Program of China under Grants 2017YFA0603002 and 2016YFB0501502 and in part by the National Natural Science Foundation of China under Grant 41531174.

语种：英文

外文关键词：Forestry; Vegetation mapping; Productivity; Remote sensing; Biological system modeling; Rivers; Spatiotemporal phenomena; Climate controls; downscaling; net primary productivity (NPP); spatiotemporal variation; the upper Luanhe River basin

摘要：The upper Luanhe River Basin is a significant ecological barrier guarding the Beijing-Tianjin-Hebei region in China. Quantitative measures of vegetation productivity can be used to assess ecosystem carbon sequestration capacity and monitor regional ecological environmental health. Although several vegetation productivity products have been generated, poor spatiotemporal resolution limits their application in ecosystem service assessment. In this article, vegetation net primary productivity (NPP) from 2000 to 2017 with a resolution of 30 m in the upper Luanhe River Basin was generated based on a data fusion model and the multisource data synergized quantitative (MuSyQ) NPP model. Then, the variation trend of NPP and its climate controls were analyzed. Compared with forest NPP observation data, we derived an R-2 of 0.68 and the root-mean-square error of 81.70 gC(.)m(-2.)yr(-1). Annual NPP had a fluctuating increasing trend from 2001 to 2017, with values ranging between 3.43 and 5.00 TgC(.)yr(-1), with an annual increase trend of 0.04 TgC(.)yr(-1). Precipitation was significantly correlated with NPP in the upper part of the Luanhe River basin, which is an important reason for the interannual variation of NPP. Grassland had a stronger correlation to precipitation than forest because it is more sensitive to precipitation. The area where the temperature is significantly correlated with annual NPP only accounts for 2% of the study area, indicating that temperature has a weak influence on NPP. Furthermore, human activities, such as forest management, fertilization, and irrigation, can change the trend of annual NPP.