|Alternative Title||A research on quantifying ecosystem fine changes of the Zoige Plateau based on remote sensing|
|Place of Conferral||北京|
|Keyword||若尔盖高原 遥感精细表征 过水面 覆盖度 蒸散发 物候期|
With the interaction of global climate change and human activities, the change of terrestrial ecosystem is becoming more and more prominent. The terrestrial ecosystem present some characteristics such as decreasing in stability of ecosystem and diminishing of ecosystem services ability, which have seriously affected the sustainable development of terrestrial ecosystem and finally threaten the survival and further development of human society. Therefore, obtaining accurate dynamic information and achieving the effective monitor of terrestrial ecosystem is an urgent problem to be solved. In recent years, with the rapid development of remote sensing technology for Earth Observation，it has become an important way to achieve the real-time, consecution, dynamic and efficiency monitoring of the terrestrial ecosystem on a large scale. However, in present research on the method of remote sensing monitoring ecosystem, there are some limitations of single remote sensing data in the temporal and spatial expression. As a consequence, the dynamic characteristics of the terrestrial ecosystem could not be accurately and effectively expressed by the existing methods, which restricted the further development of remote sensing technology.In order to solve this main problem, the Zoige Plateau, which is located in the eastern of the Tibetan Plateau, China, was selected as a study area. The Zoige ecosystem has changed dramatically with interference from global climate change and human activities in recent years. Some severe ecological problems have emerged in the Zoige Plateau, such as marshlands shrinkage, grassland degradation and decrease of water resource. For these problems, this thesis focuses on exploring fine characterization methods with remote sensing technology for alpine wetland-grassland ecosystem in the Zoige Plateau. The specific work starts from researching on ecosystem changes with remote sensing technology on spatial fine characterization and temporal fine characterization. In study of characterization methods of spatial scale, according to the difficulty in monitoring the land-water transition zone and sparse grassland, we will carry out remote sensing sub-pixel scale research of fine characterization of subpixel inundation percentage and grassland cover in Zoige Plateau based on collaboration of the ultra-high spatial resolution unmanned aerial vehicle (UAV) data with mid and high spatial resolution remote sensing data. In study of characterization methods of temporal scale, according to monitoring the growth process of grassland and change of water resources, the phenological monitoring and evapotranspiration estimation method with remote sensing were carried out based on MODIS which has long time series and high frequency observation. Finally, we will study fine characterization with remote sensing on monitor the growth process of grassland and time series of evapotranspiration (ET) which is the key parameter of water resources under the background of climate change. Though the above research work, the conclusions are as follows：(1) In study of fine characterization of land-water transition zone with remote sensing, Sub-pixel inundation percentage (SIP) which is a comprehensive indicator of the wetland ecosystem changes was selected. We will study on the method of fine characterization on wetland SIP mapping based on UAV and Landsat-8 OLI data in this paper. The Results were as follows: Firstly, ultra-high resolution of the UAV image (0.16 m) could capture the information of wetland SIP accurately. Secondly, three typical models (linear spectral decomposition model, artificial neural network model and regression tree model) were applied to modeling wetland SIP mapping based on UAV and Landsat-8 data in 2014. Regression tree models showed the highest precision (R2 = 0.933, RMSE = 8.73%) among three methods according to the validation and comparative analysis. And this method also achieve successfully prediction when it was applied to map wetland SIP of 2013, the prediction accuracy which is high (R2 = 0.986, RMSE = 8.84%) was validated by UAV data of 2013. The results show that the regression tree model which was established in this study could be applied effectively to map wetland SIP in the long time series and to realize fine characterization of wetland SIP with remote sensing.(2) In study of fine characterization of sparse grassland with remote sensing, the grassland coverage which is an important index for monitoring changes of grassland ecosystem was selected in this paper. We will carry out the research of sub-pixel fine characterization methods of grassland coverage based on UAV and Landsat-8 OLI data. The results showed that: Firstly, the pixel dichotomy model was constructed based on the visible difference vegetation index (VDVI) of UAV, which can effectively estimate the subpixel grassland coverage of the visible light image of UAV. Secondly, three categories of typical subpixel coverage estimation models (empirical model, pixel dichotomy model and three-band gradient difference model) were selected for modeling and evaluation based on the 2014 UAV coverage and Landsat-8 OLI data. The results show that the empirical model constructed by this research has the highest estimation accuracy (R2=0.901, RMSE=6.55%), which can be used for the fine mapping of grassland coverage in Zoige Plateau. When this method was applied to monitor the grassland coverage in 2013, the prediction accuracy is high (R2=0.736, RMSE=8.48%) through the validation of UAV data. The results show that the empirical model established in this part of research can effectively monitor the change of grassland coverage in long time series and can be applied for fine characterization of grassland degradation with remote sensing.(3) In study of fine characterization of grassland growth process with remote sensing, the dynamic threshold method was adopted to monitor phenology of Zoige Plateau with remote sensing based on high temporal resolution of MODIS images. The results show that phenological monitoring method used in this study can accurately reflect the growth process of grassland and characteristics of annual dynamic in Zoige Plateau. We can ultimately realize the fine characterization of grassland growth process on the temporal scale with remote sensing. The results show each phenophase characteristics were anastomosis with the water heat conditions. Accompanying the deterioration in heat and water conditions from low altitude to high altitude, south to north and surface water from high to low, SOG (start of growing season) was delayed gradually, EOG(end of growing season) advanced slowly and LOG (long of growing season) shortened gradually. Water played an important role in the regional differentiation of phenology. The inter-annual variation of phenology also reflects the close relationship between it and key climate factors such as temperature, and precipitation.(4) In study of fine characterization of hydrothermal conditions change with remote sensing, ET which is an important parameter for water resources balance was chose. The classical ET model (SEBS) was adopted to study fine characterization of surface evapotranspiration in Zoige Plateau based on the high temporal resolution of MODIS images. Study results show that the remote sensing monitoring method can effectively reflect the distribution characteristics of ET in spatial and temporal scale. We realized the fine characterization with remote sensing on temporal scale for the study area. By monitoring the temporal and spatial distribution of ET in the study area, it was found that the ET is closely related to the surface water and heat condition. Evapotranspiration is highest in the dry hot river valley area in the southwest and eastern part of the Zoige Plateau. ET is higher along the rivers and lakes in the northern of Zoige Plateau and the minimum ET appears in the area of desertification or degraded grassland, and higher elevations mountainous. The monthly maximum and the minimum ET appeared in July and February respectively.In a word, based on fine characterization research of the Zoige Plateau ecosystem change with remote sensing, we obtained the fine characterization methods with remote sensing in land-water transition zone, sparse grassland, the grassland growth process and the change of hydrothermal conditions on the Zoige Plateau, and set up a monitoring system for plateau ecosystem changes which could effectively monitoring the ecological environmental problems faced by the Zoige Plateau. Hope to provide a scientific basis for the protection and restoration of the ecological system in the Zoige Plateau.
|夏浩铭. 若尔盖高原生态系统变化遥感精细表征研究[D]. 北京. 中国科学院大学,2016.|
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