Study On Interaction Remote Sensing Diagnosis Between Snow And NPP In Tibetan Plateau

The average elevation of the Tibetan Plateau is about 4 000 meters,covered with a large amount of snow in winter,and the hydrothermal condition caused by snow cover is an important factor for the vegetation growth.Alpine meadows,grasslands and shrubs lie the largest proportion among all the vegetation on the Tibetan Plateau.The Net Primary Productivity(NPP)is one of the most important parameters of grassland ecosystem.The Tibetan Plateau is one of the sensitive regions of global change.Small fluctuations in climate change will produce strong responses in plateau ecosystems,leading to changes in the pattern,process and function of plateau vegetation.Over the past few decades,great changes have taken place in the climate of the Tibetan Plateau(The average temperature rises 1.4? annually.),resulting in significant changes in snow cover and alpine vegetation on the plateau.Therefore,under the background of such climate change,it is of great significance to study vegetation productivity status on the Tibetan Plateau and analyze the response relationship and response mechanism of snow cover to NPP changes.The main content of this study is based on the subject idea of remote sensing for environmental health diagnosis.In view of the net primary productivity —— one of the indicators of ecosystem health,the advantages of time-series remote sensing data are exerted.NPP and snow parameters were quantitatively and qualitatively analyzed.Based on this,the influence of snow cover and other climatic factors on the changes of vegetation NPP was quantitatively analyzed,and the contribution rate of NPP changes in each snow cover parameter was analyzed.The main conclusions of this thesis include the following four aspects:(1)NPP and snow cover datasets from 1983 to 2012 in the Qinghai-Tibet Plateau.In this study,the long-time datasets——GIMMS3g-NDVI and LTDR-AVH09C1 were used as the basic data.CASA model and multivariate multi-temporal data were used to extract the NPP and snow information.The NPP dataset was simulated by solar radiation data and meteorological data to drive the CASA model to estimate the vegetation NPP.Compared with the measured biomass data,the results show a better precision.AVH09C1 from LTDR was first used to make snow products based on multi-temporal empirical model.The datasets further extracted two snow cover parameters of winter snow depth(SD)and snow melting period(SCM),and were verified by the comparison with MODIS data.(2)The monitoring of vegetation changes in NPP and snow cover on the Tibetan Plateau from 1983 to 2012.The spatio-temporal features of monthly average and annual average distribution of NPP and snow cover were analyzed.The results showed that the NPP of the vegetation on the Tibetan Plateau reached the maximum in August and minimum from November to April and spatial distribution showed an obviously increasing trend from the northeast to the southwest,contrast to elevation trend.The time series showed an overall increasing trend especially in the northern Qilian mountain and the northern part of the Nyainqentanglory.The snow cover reaches the lowest in September every year and the highest in January and March.The spatial distribution mainly concentrates on Tanggula,Nyainqentanglha and Kunlun Mountains as to the variation trend of elevation.The distribution of less snow occured in the southern Tibetan Plateau and western Sichuan.The snow cover in 1998 is the largest of all years,the overall snow cover on the Tibetan Plateau showed an increasing trend,but not significantly and heterogenicity is obvious.(3)Study on the relationship between single climate factors and vegetation NPP response.The effects of snow parameters and other climatic factors on the significant changes of vegetation on the Tibetan Plateau are distinguished.Two snow parameters are extracted respectively to the spatial distribution of significant changes of NPP on the Tibetan Plateau.Combined with vegetation type classifications and topographic data,the spatial variability of the driving force for the significant changes of NPP on the Tibetan Plateau from 1983 to 2012 was analyzed.The results showed that the areas of significant correlation between NPP and temperature on the Tibetan Plateau decreased with the vegetation growth period,and gradually decreased from west to east.Significant positive correlation was found in the alpine meadow tundra in the plateau hinterland.The areas of significant correlation between NPP and precipitation on the Tibetan Plateau increased with the vegetation growth period.The spatial distribution of the correlation area that passed the test mainly concentrated in southern Tibet Valley area and southern Qilian Mountains.The area of significant correlation between NPP and soil moisture showedan increasing trend with the growth of vegetation.The spatial distribution of NPP is mainly concentrated in the areas of southern Tibet Valley and western Sichuan.The NPP of vegetation and winter snow depth are only in some specific areas showing a significant positive correlation,the region mainly concentrated in the southern Tibetan valley Region,other regions of the correlation is not obvious;vegetation growing on snow NPP response relationship is affected by climatic factors,topography and ecological factors geographic partitions.There was no significant correlation between NPP and snow cover in areas with annual average temperature of less than-9 ? and annual precipitation of less than 150 mm.NPP had a significant negative correlation with snow in areas with temperature between-8? to 0?.The correlation between NPP and snow is gradually weakened with an increasing temperature.The NPP with annual precipitation of 200-500 mm is significantly affected by the change of snow,while the area with annual precipitation of more than 500 mm is weakly affected by the snow.In terms of ecological zonation,the NPP of HIC1,HIC2 and HID1 showed a slight postponement trend.The NPP of other regions showed different degrees of advancement.The variation of snow varies greatly in different ecological units;NPP in the semi-arid subtropical zone of the plateau is obviously more sensitive to the change of snow cover than other regions.From the perspective of vertical terrain,the NPP and snowmelt gradually delays and the snow depth gradually increases with the altitude increasing.The NPP within the range of 4 700-5 400 meters was significantly affected by snow cover.(4)Remote sensing diagnosis of NPP responses of vegetation to snow was driven by multi-factors based on path analysis.In this study,the average temperature of vegetation growing season was chosen as the temperature index.By comparing the effects of precipitation on the spatial distribution of NPP,we selected the soil moisture(SM)data of vegetation growing season as the intermediate parameter of the impact of snow cover on vegetation.We select the last winter snow melting date and snow depth as snow parameters.By analyzing the normalized multiple linear regression analysis of NPP and four climatic factors(two response paths),the synergistic effect of subsequent factors on vegetation changes and the relationship between the various factors and vegetation changes were studied.Finally,the distribution of the dominant factors influencing the NPP changes of the vegetation on the Tibetan Plateau from 1982 to 2012 were obtained.The results showed that the temperature-related area with the highest contribution to the change of vegetation NPP was the largest in any path,while the response area with precipitation and soil water as the main factors increased gradually during the vegetation growth period.Furthermore,the path analysis method was used to diagnose the effect of snow cover on vegetation NPP based on remote sensing data and related meteorological data.Based on the two pathways of snow cover on vegetation NPP: snow-SCM-vegetation growth and snow cover-SM-vegetation growth,the main pathways affected by snow cover on vegetation were diagnosed by path analysis.The results showed that the impact of snow-soil moistureNPP response of HIC1 and HIIC2 eco-zoning was more obvious while the more significant impact of snow-thaw-NPP response path was found in HIIAB1 ecological zoning.No matter which path of other eco-zoning response is not obvious.Main Innovations:(1)For the first time,the snow inversion model building based on LTDRAVHRR was completed.(2)30-year term dataset of NPP and snow cover in the Tibetan Plateau was completed.(3)For the first time,the relationship between snow cover and vegetation NPP in the Tibetan Plateau was analyzed based on the 30-year scale.(4)For the first time,the remote sensing diagnosis of snow cover and vegetation NPP response mechanism based on the path analysis method was implemented.