Study on Estimation of Net Primary Productivity Based on High Resolution Remote Sensing Image and Its Influencing Factors in Yinchuan City
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摘要: 植被净初级生产力(NPP)是监测区域陆地生态系统碳循环过程，评估区域碳源、汇的重要因子。估算植被NPP，揭示其演变特征及其对自然人文因子的响应对于区域生态系统可持续发展具有重要意义。以银川市为例，基于CASA模型利用亚米级高分辨率遥感影像、气候、土地利用等数据估算研究区2015年和2021年不同季度植被NPP并分析其时空演变特征，采用梯度提升决策树(GBDT)模型揭示自然因子、人类活动以及土地利用对植被NPP的非线性响应和阈值效应。结果表明： 1)2021年银川市植被NPP在0-753.951 g C·m-2·a-1，高值区集中在黄河沿岸农业灌溉区。利用高分辨率影像估算植被NPP，可得到田块尺度和城市街区尺度植被NPP空间分布的细节图，提高估算精度。2)银川市植被NPP随季节的变化趋势与植被物候和农作物生长周期一致。2015-2021年第三季度植被NPP整体呈增加趋势，但城市扩张占用耕地导致局部NPP下降显著，而生态保护区内植被NPP上升显著。3) NDVI、土壤有机碳密度、高程、气温和降雨等自然因子对植被NPP存在显著阈值效益，其中NDVI的相对贡献最大，但超过0.6后，对植被NPP的提升作用不明显。不同土地利用类型对植被NPP的非线性影响存在差异，如旱地对NPP的影响阈值高于水田，建设用地中城市绿色基础达到一定比例时对植被NPP起正向作用，即调控土地利用结构和布局对于植被NPP的提升至关重要。当人类活动在一定范围内时对植被NPP有一定程度的促进作用，而当人口数超过阈值后，人口越大，生态承载力越低，植被NPP则会下降。Abstract: Objectives: Net primary productivity (NPP) of vegetation is an important factor to monitor the carbon cycle process of regional terrestrial ecosystem and regional carbon sources and sinks. Estimating NPP of vegetation and revealing its evolution characteristics and its response to natural and human factors are of great significance to the sustainable development of regional ecosystem. Methods: Taking Yinchuan as an example, based on Carnegie-Ames-Stanford Approach(CASA) model combined with sub-meter high-resolution remote sensing images, climate, land use and other data, the NPP of vegetation in different seasons from 2015 to 2021 in the study area are estimated and its temporal and spatial evolution characteristics are analyzed. Gradient Boosting Decision Tree (GBDT) model is used to reveal the nonlinear response and threshold effect of natural factors, human activities and land use on NPP of vegetation. Results: 1) The NPP of vegetation in Yinchuan was 0-753.951 g C·m-2·a-1, and the high value areas were concentrated in the agricultural irrigation areas along the Yellow River. The detailed spatial distribution maps of NPP of field scale and urban block scale were obtained with high-resolution images used in the estimation of NPP, which also improves the estimation accuracy. 2) The seasonal variation trend of vegetation NPP in Yinchuan was consistent with vegetation phenology and crop growth cycle. In the third quarter of 2015-2021, the NPP of vegetation showed an overall increasing trend, while the local NPP decreased significantly due to the occupation of cultivated land by urban expansion, while the NPP of vegetation in ecological protection areas increased significantly. 3) Natural factors such as NDVI soil organic carbon density, elevation, rainfall, etc. had significant threshold effects on NPP, and the relative contribution of NDVI is the largest, when it exceeded 0.6, it had no obvious promotion effect on NPP of vegetation. The threshold of NPP of dry land was higher than that of paddy field, and construction land played a positive role in NPP when urban green foundation in the construction land reaches a certain proportion. When human activities are in a certain range, they can promote NPP of vegetation to a certain extent. When the population exceeds the threshold, the larger the population, the lower the ecological carrying capacity, and the lower the NPP of vegetation. Conclusions: In this study, high-resolution images are used to estimate vegetation NPP, which improves the refine degree of spatial distribution of vegetation NPP. The seasonal characteristics of vegetation NPP in Yinchuan city are significant, and the changing trend of NPP with seasons is consistent with vegetation phenology and crop growth cycle. Natural factors, land use and human activities in Yinchuan city have significant effects on vegetation carbon sink with significant threshold effects. Natural factors have a greater relative contribution to vegetation NPP than the other two factors.
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Keywords:
- Yinchuan City /
- net primary productivity /
- CASA model /
- nonlinear relationship
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