| As the most important part of the ecosystem,surface vegetation cover assumes many functions such as climate regulation,wind and sand control,soil and water conservation,air purification,soil improvement,etc.It plays an irreplaceable role in the global energy balance,biochemical cycle and water cycle,and is the background foundation of the ecological environment,and is also the primary issue in protecting and managing the ecological environment.Although the surface vegetation coverage in southwest China is high,the ecological problems are becoming more and more prominent with the intensification of human activities,and the special topographic structure and fragile ecosystem of the mountain plateau are highly vulnerable to destruction,so it is more important to strengthen the protection and management.Yunnan Province is a typical mountainous plateau terrain in China,and it is especially important to strengthen the protection and management of ecological environment,and the national and local governments are particularly concerned about the ecological environment in Yunnan.This study aims to analyze the ecological background of Yunnan Province,grasp the differentiation,distribution and change patterns,study the driving factors of surface vegetation cover change and the improvement effect on ecological environment,and provide basic data and reference for the decision of ecological environment protection and management and ecological civilization construction in Yunnan Province.This paper is mainly based on MODIS-EVI data from 2000 to 2020,and uses methods like elementary dichotomy,linear regression equation,coefficient of variation,Hurst index and spatial analysis to systematically analyze the characteristics of spatial and temporal changes of surface vegetation cover in mountainous plateau areas;combines 14 kinds of data such as climate,soil,topography,population and economy,etc.,and uses geographic probes and partial correlation analysis to explore the factors affecting The driving factors and driving effects of surface vegetation cover changes and analyze the correlation degree between climate factors and vegetation cover;use FVC,LAI,GPP,WET and LST data to construct a comprehensive remote sensing ecological index,and use spatial analysis,regression analysis and geographic probes to study the changes of ecological environment quality and the improvement effect of surface vegetation cover on ecological environment.The main conclusions are as follows:(1)In the past 21 years,the overall vegetation cover in Yunnan Province showed a fluctuating trend of increase,with an average annual increase of 0.0026.The average annual increase of each state and city was ranked as follows: Zhaotong > Qujing >Wenshan > Puer > Lijiang > Lincang > Chuxiong > Baoshan > Nujiang > Honghe >Dehong > Kunming > Dali > Xishuangbanna > Yuxi > Diqing.The overall vegetation cover in Yunnan improved year by year from 2000 to 2020,and the vegetation cover of different land types increased significantly,and the overall vegetation cover quality improved significantly.The overall vegetation cover in July-August>SeptemberOctober>May-June>March-April>January-February>November-December,and the overall vegetation cover in all seasons is better in the south than in the north;the overall vegetation cover in all seasons is better in summer>autumn>spring>winter,and also in the south than in the north.(2)From 2000 to 2020,the vegetation cover in the study area gradually increased mainly from the east,south and west,especially in the areas of Zhaotong,southern Qujing,Wenshan,southern Honghe,Puer,Lincang,Dehong and Baoshan,where vegetation cover improved significantly.The area of improved and significantly improved areas of vegetation cover(76.79%)was significantly larger than that of degraded and significantly degraded areas(19.81%),and the area of stable and mildly fluctuating areas(64.72%)was significantly larger than that of heavily fluctuating areas(7.71%),so the overall vegetation cover of the region showed a stable growth trend.The persistence analysis showed that the reverse persistence(73.53%)was stronger than the positive persistence(26.47%),and the percentages of the areas with weak persistence increasing and decreasing,strong persistence increasing and decreasing trends were 36.15%,59.66%,1.20%,and 2.99%,respectively,and the overall vegetation cover would have a slight decreasing trend in the future.(3)The driving effect of climatic factors on causing vegetation cover changes in the study area is higher than that of geographic and anthropogenic factors,and the driving effect of geographic factors is higher than that of anthropogenic factors,and the specific driving force magnitudes are: annual cumulative precipitation > elevation >average annual temperature > soil type > land use > clay soil > population > annual cumulative sunshine hours > sandy soil > GDP > silt soil > average annual wind speed >slope degree > slope direction.The two different drivers are more likely to show an interaction enhancement(92.31%),and only a very small proportion of the drivers show a weakening interaction.The risk detection showed that the classification of each driver was reasonable and scientific;the range of the most suitable drivers for vegetation growth was derived.Ecological detection shows that the amount of significant difference between any two drivers on the spatial distribution of vegetation cover in the study area(74%)is significantly larger than that without significant difference(26%);the average annual temperature,cumulative annual precipitation,elevation and soil type of drivers are the most important factors affecting the spatial distribution of vegetation cover in the study area.(4)The correlation between vegetation cover and annual cumulative precipitation in the study area was higher,which also proved that the driving effect of annual cumulative precipitation factor on causing vegetation cover changes was higher than that of annual mean temperature.The linear correlation between monthly vegetation cover and cumulative monthly precipitation was higher in the study area,and the area of its partial correlation coefficient passing the significance test reached 79% with a mean value of about 0.7;the area of its partial correlation coefficient value in the range of 0.7<r≤1 was about 56.85%,which was mainly distributed in the central part of the region.However,in the northwestern,Zhaotong,and some parts of the southeastern part of the region,the monthly vegetation cover was significantly more correlated with the average monthly temperature.The climate factors in the study area have a high degree of correlation with vegetation cover,and the overall monthly vegetation cover correlates with monthly climate to a higher degree than the interannual vegetation cover correlates with interannual climate.(5)The average comprehensive remote sensing ecological index in the study area from 2000 to 2020 showed an increasing trend,and the spatial distribution showed a spreading change from the central part to the surrounding area,and the overall ecological environment quality gradually developed in a good direction.The percentage of the area where the annual average ecological environment quality grade declined and rose was 9.53% and 22.12%,respectively.The declining areas were mostly distributed in Baoshan,Dali,Yuxi,Honghe,Xishuangbanna,Diqing and other regions;the rising locations were mainly distributed in the central and eastern parts of the region as well as Lijiang and Dehong.The categories of ecological environment grade change are mainly worse(9.36%)and better(21.74%),while the area sum of obviously worse and obviously better is only 0.55%,and the area of unchanged grade accounts for the largest percentage,about 68.35%.(6)Regression analysis showed that vegetation cover and remote sensing ecological index showed a significant positive correlation,and the regression coefficients were all greater than 0.75;for every 10% increase in vegetation cover in the study area,the remote sensing ecological index increased by at least 7.5% and by7.9% on average.The geographic detector analysis showed that the independent variable vegetation cover largely explained the spatial heterogeneity of the dependent variable ecological environment;the classification of the independent variable was scientific and reasonable,and the average remote sensing ecological index of vegetation cover areas from category 1 to 10 gradually increased.In a comprehensive manner,the ecological environment quality of the study area from 2000 to 2020 increased significantly with the increase of vegetation cover,and the increase of vegetation cover had a significant improvement effect on the ecological environment quality,and the increase of vegetation cover could effectively improve the ecological environment quality. |
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