农业工程学报Issue(13)：130-141,12.DOI:10.3969/j.issn.1002-6819.2013.13.018
基于地形校正的植被净初级生产力遥感模拟及分析
Simulation by remote sensing and analysis of net primary productivity of vegetation based on topographical correction
摘要
Abstract
The study on simulation of the net primary productivity (NPP) was significant in monitoring carbon balance and understanding deeply the global carbon cycle. Remote sensing image data of a high spatial resolution and short revisit cycle and topographical correction should inevitably be the choice for accurately simulating mountain net primary productivity. On the base of topographical correction for the total solar radiation and the air temperature by DEM data using geographic information system (GIS) technology, hotosynthetically active radiation absorption, the temperature stress factors, the moisture stress factor and the max light use efficiency of typical vegetation types were estimated in this paper. Then an improved Carnegie Ames Stanford Approach model was built and used with HJ-1 data to simulate the net primary productivity of the Dabie Mountain region in 2009, and the temporal and spatial variation characteristics of the net primary productivity were discussed. The results showed that: 1) By analyzing the accuracy of test results between the simulated NPP in this paper and MOD17A3 product value, a conclusion should be drawn that the CASABTC model and HJ-1 remote sensing image data were suitable for accurately simulating the net primary productivity of mountain vegetation. The net primary productivity in the study region in winter more than in spring, autumn, summer was affected by topographic relief.2) The annual average of simulated NPP in this paper was about 413.7 gC/(m2·a) and smaller than that of MOD17A3 4.9%. More details on the spatial distribution and surface features of the former were more obvious than the latter. 3) The average of simulated NPP in study region in 2009 was from 0 to 1143.6 gC/(m2·a), and the range of NPP in 66.1%of the total area was from 200 to 600 gC/(m2·a). Total NPP in the study region was 9.891×106 tC and constituted approximately three thousandth of total NPP throughout the country. On the whole, the spatial distribution of annual net primary productivity was irregularly staggered by high and low net primary productivity.4) Monthly NPP value varies with the season. The seasonal change of net primary productivity of all vegetation types manifested typical unimodal distribution curves and their range of the seasonal change differed from each other. The seasonal change of monthly NPP was in agreement with that of the temperature, the solar total radiation and normalized differential vegetation index (NDVI). However, the uneven distribution of precipitation was not related to the net primary productivity.5) Monthly NPP for all vegetation types and total NPP increased gradually with increasing altitude. For the former, according to the change in size, their order was:evergreen broad leaf forest, deciduous broad leaf forest, mixed broadleaf conifer forest, deciduous needle leaf forest, evergreen needle leaf forest, shrublands, crops vegetation and grasslands, but the latter peaked as the altitude ascended to 1100 meters and remained constant around 600 gC/m2 when altitude went on. This study could provide the reference to further the net primary productivity simulation of mountain vegetation based on HJ-1 remote sensing image data and topographical correction.关键词
CASABTC模型/地形/植被/净初级生产力(NPP)/地形校正/季节变化Key words
CASABTC models/topography/vegetation/NPP/topographical correction/seasonal change分类
信息技术与安全科学引用本文复制引用
刘玉安,黄波※,易成功,程涛,余健,曲乐安..基于地形校正的植被净初级生产力遥感模拟及分析[J].农业工程学报,2013,(13):130-141,12.基金项目
国家863高技术研究发展计划（2009AA12200）；国家自然基金项目 （）
