Net Primary Productivity Estimation Of Vegetation In Hebei Province Using Remote Sensing

Vegetation, as autotrophic organism，lies in the bottom of the entire food chain, andprovides suitable accommodation and food for a variety of biology. It connects lithosphere,hydrosphere and atmosphere through carbon cycle.Vegetation net primary productivity （NPP）, which is an important part of the land sur-face carbon cycle, not only directly reflects the production capacity of vegetation under natu-ral environmental conditions, but also reflects the capacity of vegetation to fix carbon dioxidethrough photosynthesis. Net primary productivity of vegetation is considered to be an impor-tant part of terrestrial ecosystem carbon cycle and carbon balance process, and NPP is themain factor and the key indicators to determine ecosystem carbon aggregation and to regulateecological process.In this paper, the CASA model is adopted to estimate net primary productivity of HebeiProvince in2001, by using MODIS remote sensing data, SPOT-VEGETATION NDVI data,meteorological data and other relevant information in2001. Spatial variation of NPP in HebeiProvince and impact factors of NPP are analyzed.The conclusions of this paper are as follows.（1） The net primary productivity of vegetation in Hebei Province in2001is estimated,and the study shows that the maximum value of NPP is608gC/m²·a., the average NPP valueis334.305gC/m²a. and NPP values distributes from0to608gC/m²·a. NPP values in mostareas are200⁴00gC/m²·a. Regions where NPP is less than200gC/m²a are mainly in theregion of offshore, coastal wetlands and the northwest of Zhangjiakou region. Regions whereNPP is greater than500gC/m²a are Chengde, part of Tangshan and Qinhuangdao.（2） As for vegetation types, these vegetation types, including evergreen coniferous forest,deciduous broad-leaf forest, deciduous coniferous forest and annual crop dry land, accumulatemore NPP, the second is rotation dry land, sparse shrubbery, coppice and closed shrub. Waterbody, offshore and coastal wetlands almost do not accumulate NPP. As for seasons, vegeta-tion NPP accumulates the most in summer, autumn and spring follows, and it accumulates theleast in winter.（3） The net primary productivity of the area is influenced by vegetation types, tempera- ture, precipitation, vegetation index and light use efficiency. In the surrounding environmentof vegetation，the more water and heat is, the more the accumulation of vegetation NPP is. Onthe other hand, if water or heat is insufficient or too much, it will cause the ability weakeningof vegetation NPP accumulation. Under sufficient and stable conditions of water and heat, thechanges of vegetation index and light use efficiency are proportional to NPP changes. Lightuse efficiency values of vegetation in Hebei Province in2001is0⁶9×10^-4gC/MJ. Theaverage light use efficiency is35.81×10^-4gC/MJ. Light use efficiency values of vegetationin most areas is30×10^-440×10^-4gC/MJ. Water bodies and coastal areas are almostimpossible to use the light, and light use efficiency is less than10×10^-4gC/MJ. Light useefficiency is low in mountainous area in Northwest of Hebei Province, which is10×10^-430×10^-4gC/MJ. Light use efficiency of vegetation is higher in most areas of Chengde,Tangshan and Qinhuangdao, which is40×10^-470×10^-4gC/MJ, especially in the southeastof Chengde and near part of Tangshan and Qinhuangdao, light use efficiency is60×10^-470×10^-4gC/MJ.（4）In this paper, after verification, the accuracy of net primary productivity obtainedby CASA model is relatively high. However, there is a lot of uncertainty in the NPP result,such as data parameter uncertainty and model uncertainty. Data parameter uncertainty ismostly caused by spatial resolution of remote sensing data and processing methods, differentremote sensing data classification system and classification accuracy, interpolation methods,etc. Model uncertainty is mainly because of the choice of some parameters in the model itselfand the model formula.