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• 研究报告 • 上一篇    下一篇

中国西北地区NPP模拟及其时空格局

朱莹莹1,2,韩磊1,2,赵永华1,2*,奥勇1,2,李军军1,许凯波1,刘冰1,2,葛媛媛1,2   

  1. (1长安大学地球科学与资源学院/土地工程学院, 西安 710054;2陕西省土地整治重点实验室, 西安 710054)
  • 出版日期:2019-06-10 发布日期:2019-06-10

Simulation and spatio-temporal pattern of vegetation NPP in northwest China.

ZHU Ying-ying1,2, HAN Lei1,2, ZHAO Yong-hua1,2*, AO Yong1,2, LI Jun-jun1, XU Kai-bo1, LIU Bing1,2, GE Yuan-yuan1,2   

  1. (1College of Earth Sciences and Resources/College of Land Engineering, Chang’an University, Xi’an 710054, China; 2Shaanxi Key Laboratory of Land Consolidation, Xi’an 710054, China).
  • Online:2019-06-10 Published:2019-06-10

摘要: 中国西北地区MOD17A3 NPP数据产品缺失严重,影响了该区域植被净初级生产力的进一步研究。本研究利用气象数据、高程数据、NDVI和质量好的MOD17A3 NPP,构建BP神经网络模型,模拟2000—2014年西北地区植被NPP,填补数据缺失区域。利用一元线性回归分析法、R/S分析法、偏相关分析法等,分析了植被NPP的时空变化特征及其与气象要素的关系。结果表明:(1)MODIS NPP产品值与BP神经网络模拟值的决定系数R2、平均绝对误差MAE、平均相对误差MRE、均方根误差RMSE分别在0.833~0.906、25.84~40.10、0.16~0.23和34.57~59.36,满足精度要求,BP神经网络模型适用于模拟西北地区植被NPP。(2)植被年均NPP具有较强的空间差异,呈现出由东南向西北递减,而新疆西北部地区出现“条块状”高值区特征。(3)2000—2014年西北地区植被年均NPP在106.64~156.17 g C·m-2·a-1,年际变化上呈现波动下降趋势。(4)2000—2014年西北地区植被NPP变化具有空间异质性,以减少为主,仅10.79%的区域通过了显著性检验。植被NPP变化具有较弱的持续性特征,未来发展方向以不确定为主,有利和不利为辅,其中有利区域面积大于不利区域。(5)植被NPP对气温和降水的响应具有空间差异,总体上与降水关系更密切。

关键词: IPAT模型, 人文驱动力, 环境压力, 生态弹性

Abstract: The data production of MOD17A3 NPP in northwest China is seriously deficient, with consequences on further research on vegetation net primary productivity (NPP) in this region. Based on the meteorological data, DEM, NDVI, and MOD17A3 NPP with high quality, the BP neural network model was constructed to simulate vegetation NPP and fill the areas without NPP data in northwest China from 2000 to 2014. Its spatio-temporal variations and relationships with meteorological factors were analyzed using unitary linear regression, R/S analysis, and partial correlation analysis. The results showed that: (1) Coefficients of determination (R2), mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) between MODIS NPP and simulated NPP were 0.833-0.906, 25.84-40.1, 0.16-0.23, 34.57-59.36, respectively, which well met the accuracy requirements. The BP neural network model was suitable for vegetation NPP simulation in northwest China. (2) The annual mean NPP had a strong spatial variation, showing a gradual decline from southeast to northwest and a high-value block area in the northwest of Xinjiang. (3) The annual mean NPP ranged between 106.64 and 156.17 g C·m-2·a-1 from 2000 to 2014, with a slightly fluctuating downward trend in the interannual variation. (4) From 2000 to 2014, the change of NPP in northwest China had spatial heterogeneity, which was mainly reduced. Only 10.79% of the areas passed the significance test. NPP change was weakly persistent. The future change trend of NPP is mainly uncertain, supplemented by improved and declined areas, with the improved area being larger than the declined area. (5) Responses of vegetation NPP to temperature and precipitation varied spatially, which were generally more closely related to precipitation.

Key words: IPAT models, human driving force, environmental pressure, ecological elasticity.