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Temporal-spatial Evolution Of Forest Carbon Stock In Zhejiang Based On Remote Sensing Combined With Process Model

Posted on:2020-01-13Degree:MasterType:Thesis
Country:ChinaCandidate:T Y LiuFull Text:PDF
GTID:2393330578464936Subject:Forest management
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Forest carbon stocks is not only an important indicator reflecting the basic characteristics of forest ecosystems,but also a theoretical basis for evaluating forest structural functions and production potential,and is of great significance in maintaining forest ecological balance.Generally,there are three methods in forest carbon stock estimating:plot survey,remote sensing estimation and model simulation.The ecosystem process model BIOME-BGC takes the effects of canopy photosynthesis,transpiration,and soil moisture on carbon stocks into consideration to reveal biomass growth,vegetation-environment interactions and ecosystem response to climate change.Thereby it's an important method for spatiotemporal dynamic simulation and analysis of forest carbon stocks.The remote sensing combined process model can combine the real-time,dynamic,large-scale,multi-resolution characteristics of remote sensing with process models advantages of reflecting vegetation ecological and physiological processes together,and it can simulate large-scale carbon cycle and reflect spatial distribution and dynamic changes of carbon stocks.Together with the ground data providing support for model parameter optimization and simulation result verification,the remote sensing combined process model makes the forest carbon stocks simulation coupled with“ground survey-remote sensing information-process model”become a hotspot of current research.This study takes Zhejiang Province as an example.Based on ground data collection,Landsat5 TM?1988,1992,1996,2000,2004,2008?and Landsat8 OLI?2014?remote sense data combine with data of topography,soil,meteorological,physiological and ecological parameters drive BIOME-BGC process model to simulate the aboveground carbon stocks of coniferous?broad-leaved and bamboo forest in Zhejiang Province,and analyzes the temporal and spatial distribution pattern of aboveground carbon stocks and its response to environmental factors.We forecast the future forest area of the Zhejiang province by land use transition matrix,and analyzes future trend of the potential aboveground carbon.the results would provide theoretical basis and data support for forest carbon sink management and climate change in Zhejiang Province.The main conclusions of the study include the following:?1?The temporal and spatial simulation for aboveground carbon in Zhejiang.The accuracy was verified by the forest resource inventory data from 1989 to 2014.The average correlation coefficient r between the measured and simulated values of coniferous,broad-leaved and bamboo forest are 0.69,0.81,and 0.76,respectively;the average RMSE are 11.01,15.25,7.38 Mg C·hm-2,respectively;and the average rBIAS are-1.86,-5.60,-2.74 Mg C·hm-2,respectively.These indicate that the model has higher simulation accuracy at the provincial scale in aboveground carbon stocks.?2?Temporal and spatial evolution characteristics of aboveground carbon stocks in coniferous,broad-leaved and bamboo forest of Zhejiang Province during 1988-2014.?a?Aboveground carbon stocks of coniferous forests:From the temporal point of view,the total aboveground carbon stocks showed a fluctuating downward trend,with an average annual decline of 1.78 Tg C and an average annual decline rate of 2.34%;the total aboveground carbon stocks is between 53.40 and 102.24 Tg C,the average value is 83.23 Tg C;the aboveground carbon density is between 21.44 and 30.30 Mg C·hm-2,and the average value is 26.91 Mg C·hm-2.From the spatial point of view,the coniferous forest high carbon stocks area is mainly concentrated in the forest industries developed areas of northwestern Zhejiang,southwestern Zhejiang and central mountainous areas,while the low value areas are mainly distributed in the coastal areas and Jiaxing City and so on.?b?Aboveground carbon stocks of broad-leaved forests:From the temporal point of view,the total aboveground carbon stocks fluctuated and grew at a faster rate,with an average annual increase of 2.19 Tg C and an average annual growth rate of 4.88%;the aboveground carbon density is also increasing year by year.The total carbon stocks of broad-leaved forest are between 22.57 and 81.74 Tg C,with an average of 50.62 Tg C;the aboveground carbon density is between 23.86 and 30.06 Mg C·hm-2,with an average of 28.29 Mg C·hm-2.From the spatial point of view,the high carbon stocks area of broad-leaved forest is mainly concentrated in the forestry industries developed areas such as northwestern Zhejiang and southwestern Zhejiang,while the low-value areas are mainly distributed in the northern and coastal areas of Zhejiang Province.?c?Aboveground carbon stocks of bamboo forests:From the temporal point of view,the total aboveground carbon stocks showed an increasing trend,with an average annual increase of 0.17 Tg C,an average annual growth rate of 1.36%,and total aboveground carbon stocks is between 10.46 and17.19 Tg C,the average value is 14.03 Tg C;the aboveground carbon density of bamboo is between14.34 and 17.14 Mg C·hm-2,the average value is 16.25 Mg C·hm-2,and the aboveground carbon density fluctuates after 1996.From a spatial point of view,the high aboveground carbon stocks areas of bamboo forests were mainly concentrated in areas with abundant bamboo forest resources such as Anji,Lin'an,Yuyao,Longyou and Quzhou,and bamboo industries developed.The low-value areas are mainly distributed in Zhejiang.In the central and coastal areas of the province,the area with low value range in the central region has an increasing trend.?d?Total aboveground carbon stocks of forests in Zhejiang Province during 1988-2014:From the temporal point of view,the aboveground carbon stocks fluctuated and increased,with an average annual increase of 0.60 Tg C,an average annual growth rate of 0.42%;the aboveground carbon stocks are between 134.65 and 162.44 Tg C,the average value is 148.26 Tg C;the aboveground carbon density is between 21.92 and 27.30 Mg C·hm-2,and the average value is 23.79Mg C·hm-2.From a spatial perspective,the high-value areas of the aboveground carbon stocks are mainly concentrated in the forest industries developed areas of the northwestern Zhejiang and other forest industries developed,while the low-value areas are mainly distributed in the central and coastal areas of Zhejiang Province.The area with low value range showed an increasing trend in the central.?3?The response of forest aboveground carbon stocks to environmental factors and LUCC.?a?Environmental factors have an impact on the changes of aboveground carbon stocks in forests in Zhejiang Province,with annual average temperature,annual precipitation,CO2 concentration and nitrogen deposition correlated with forest carbon stocks,and the correlation coefficient is about 0.5.They play an important role in aboveground carbon stocks.There is no correlation between annual average radiation and aboveground carbon stocks.From the partial correlation coefficient,the partial correlation coefficient between annual average temperature and forest aboveground carbon stocks is large,indicating that the annual average temperature has a more important role in the temporal-spatial evolution of forest aboveground carbon stocks.?b?Based on the land use transition matrix from 1988 to2014,three scenarios were set according to the four parameters of DAVR,DMAX,AC and AP to estimate the forest carbon stock potential of 2015-2050 in Zhejiang Province.The forest aboveground carbon stocks potential under the three scenarios are 273.21±24.31,132.67±16.23,and 238.41±19.68 Tg C,respectively.It is concluded that LUCC has a great impact on forest carbon stocks.Ensure the current forest area is unchanged for the current forest conditions in Zhejiang Province and increasing forest carbon density should be take into consideration in forest carbon sink management.
Keywords/Search Tags:forest aboveground carbon stocks, remote sense, BIOME-BGC model, temporal-spatial evolution, environmental response
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