荒漠草原牧草生物量的遥感估算及空间分布

Estimation and analysis of grass biomass in desert by remote sensing

应用2005年5-10月份EOS/MODIS资料，采用光能利用率算法，估算了中国西北荒漠绿洲区域NPP，并结合地上生物量观测资料，建立了基于NPP的地上生物量估算模型，同时分析了生物量和NPP时空分布特征。结果表明，2005年牧草生长期内NPP的变化基本是6、7月份最大，其它月份较小，5-6月份是牧草叶面积变化比较大的时期，也是NPP变化比较显著的时期;生物量模型估算得到的44个样本的生物量误差基本都小于20%，说明模型能够反映牧草的实际生长状况;不同荒漠牧草对光的利用能力和对CO2同化能力有很大差异，骆驼刺、红砂、黑果枸杞是荒漠牧草生物量较大的牧草类型;牧草类型、牧草盖度以及平均高度是造成不同牧草产量相差较大的重要原因。

Net Primary Productivity in desert-oasis region in Northwest China is estimated combined the model of light energy utilization with EOS/MODIS data from May to Oct.. On the basis of NPP and observed value of aboveground biomass, biomass model is also built, then, temporal and spatial distribution of biomass and NPP are analyzed. The results show that NPP is larger in June and July than other growth periods, grass LAI and NPP change rapidly from May to June. Estimated error of 44 cases by the biomass model is less than 20%, which show that the biomass model is very good , the model can describe growing status. Photosynthesis and respiration are different because of different type grass , three types grass are more adaptive to desert environment and the biomass are also big, the grass types include Alhagi sparsifolia, Lycium ruthenicum and Reaumuria songarica. The grass biomass is influenced by many factors such as grass type, total cover and plant height et al.